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EMN 6th Annual Conference, 4-5 June 2009, Milan, Italy


EUROPEAN MICROCREDIT RESEARCH AWARD 2009 –

Fundación Nantik Lum

EMN and Fundación Nantik Lum (Spain) are pleased to announce the re-

launch of the European Microcredit Research Awards at the 6th Annual EMN

Conference this June 4-5 in Milan. Following the 2008 inaugural ceremony of

the European Microcredit Research Awards at EMN’s 5th Annual Conference in

Nice, the awards will again recognize the year’s most outstanding researchers. This

year’s award has a €1000 endowment.

Research Papers examine one of the topics of the EMN Working Groups: Legal

Environment and Regulation; Growth, Expansion, Sustainability and Funding; or,

Social Performance. All papers are practitioner oriented. Additionally, papers

presented by young researchers were especially valued in the selection processes.

The Selection Committee—made up of representatives from Fundación Nantik

Lum, the EMN Secretariat and Board, as well as members of the EMN’s Research

Working Group—has picked the three finalists of which the winner will be

chosen during the course of the Conference. The three finalists will present their

papers at the Conference’s Research Strand Workshop moderated by Fundación

Nantik Lum. During the Workshop, attendees will have the opportunity to vote on

their favourite. Finally, based on the Selection Committee’s decision and the

public’s vote results from the Workshop, one outstanding paper will be awarded

the 2009 European Microcredit Research Award!


INDEX

Arvind Ashta/Djamchid Assadi -

An Analysis of European Online micro-lending Websites…….……….page 4

Altin Muça –

Customer Desertion in fondiBESA, factors and their analysis…….….page 28

Alexander S. Kritikos/Christoph Kneiding/Claas Christian Germelmann -

Demand Side Analysis of Micro-lending Markets in Germany……….page 54


AN ANALYSIS OF EUROPEAN ONLINE MICRO-LENDING

WEBSITES

Lead Author: Arvind Ashta (Professor, Burgundy School of Business, CEREN)

29 rue Sambin, 21000 Dijon, France - 33(0)3 80 72 59 66, [email protected]

Co-author: Djamchid Assadi (Professor, Burgundy School of Business, CEREN)


ABSTRACT

Type of Paper: Research Paper

Purpose of the paper: With the development of web 2.0, a new kind of lending is taking place

on the internet, termed peer-to-peer lending or social lending. In Europe, this includes

commercial lending websites such as Zopa, smava, boober, Kokos, Monetto. At the same time,

following the lead of Kiva in the US, European microcredit web platforms are coming up

including MyC4 and Babyloan in Europe. The paper examines how the legal design of the online

websites differs from the microcredit websites in Europe and how this impacts social

performance issues of the different models.

Design/Methodology/Approach: Since the population size of these websites is rather small,

we use a comparative case study approach. The case study approach is the most adapted to

studying small samples in more detail. The case studies are based on exploration of websites and

review of academic literature and press reports.

Key results: We find that although web 2.0 permits platform models, most sites (commercial or

micro-lending) have retained intermediary roles and have not permitted direct peer-to-peer

contact. The paper will outline the advantages to both borrowers and lenders in the different

models and their motivations. Challenges for expansion, such as trust-building as well as a

marketing analysis will also be presented.

Impact: The findings would lead microfinance institutions to lobby for specific laws, and invest

in online lending solutions to radically reduce operating costs as well as to increase outreach.

Value: This research would add value to those who are operating in or launching new online

microcredit platforms to understand this young and fast changing marketplace.

Key Words: online lending, regulation, social performance, microfinance


AN ANALYSIS OF EUROPEAN ONLINE MICRO-LENDING

WEBSITES

Introduction

Since the early 1970s, Microfinance is growing at 30% per annum, but the vast majority of the

poor are still underserved. Moreover, most of them are being served at interest rates significantly

over commercial lending rates, owing to small loan sizes leading to high transaction costs. The

CGAP (Rosenberg et al, 2009) reports that operating costs are probably the main area to further

reduce microfinance costs.

In addition to reducing operating costs, financing costs can and are being reduced owing to the

reduction of spreads possible through peer to peer (P2P) online lending. In addition, online

lending offers an increased outreach to people living in isolated rural areas. This increased

outreach would further reduce both transaction costs from economies of scale and financing

costs through larger loan negotiations.

This paper looks at this relatively new phenomenon of online micro-lending which targets both

needy entrepreneurs and individuals looking for small financial solutions to their liquidity

problems.

Kiva, an American company, started an online micro-lending model in 2005 to target mainly the

needy entrepreneurs in the developing countries. This too was duplicated, with variations and

adaptations by many operators. In Europe, we find MyC4 and Babyloan. However, models are

mushrooming all over the world, with a number of them in India alone.

Although traditional microfinance has developed in poor countries, today many developed

countries are also using the system with adaptations based on local cultural differences. The

online lending movement started in March 2005 with a European firm called Zopa, UK. Since

then Zopa has gone to the the U.S., Italy and Japan. Its model, with variations, has also been

copied and adapted by many other competitors. Today, there are more than a dozen for-profit

commercial operators in the online Peer-to-peer lending market. In Europe these include

operators such as Zopa, smava, boober, Kokos, and Monetto.

In poorer countries, online micro-lending may have a more difficult future since most poor

people are illiterate and do not have access to Internet via a computer. In such countries, mobile

banking is considered the best solution. In India, for example, 37 million people have access to a

computer but 370 million people would have access to a mobile telephone. In fact, the number


of mobile connections outstrips landlines. Therefore, outreach of mobile banking has greater

potential than that of online microfinance. As opposed to this, in developed countries, access to

computers is far greater and using a computer to make financial transactions is far more

comfortable than pressing small buttons on a telephone. Therefore, the future of online lending

is probably more important than that of mobile banking in the developed world, especially

European, context. Perhaps the two will converge as satellite connections permit mobile web

based access to computers.

The paper reviews the leading issues with the most significant impacts on the entrepreneurial

business of peer-to-peer (P2P) micro-lending on the Internet. Accordingly, we will first study the

legal environment of the sector and de facto forms of intermediation adopted by both

commercial lending sites and micro-lending websites in Europe. Secondly, we will comment on

social performance issues of the different models- as this business is essentially a matter of

interactions and relations between individuals, not only for giving and getting loans, but also for

marketing and promoting them. Because trust is a critical issue in a sector whose mission is to

promote transactions between individual strangers, we will devote the third section of this paper

to the strategies used to enhance trust and overcome information asymmetry related issues. We

will finally proceed to a comparative analysis of the marketing strategies of the sample’s members

to provide insights for entrepreneurs who may consider to launch or to modify their strategies in

the field.

Table 1 – Sample’s members: P2P and social micro-lending websites and launch dates 2005 2006 2007 2008 2009

U.K. Zopa March

U.S.A. Kiva November

Germany Smava February

Netherlands Boober February

Denmark MyC4 May

Italy Boober November

Poland Kokos February

Poland Monetto March

France BabyLoan January


A case study approach, through review of academic literature and press reports, is adopted to

explore European websites. Some non-European examples are presented when the model

adopted is notably different. In our sample represented in table 1, Boober, aimed initially to

build a European network through Netherlands, Italy, Belgium, Germany and Spain. Boober in

the Netherlands has apparently ceased operations, while Boober in Italy, a joint venture between

Centax and Boober International, is currently operating. Since the size of our sample is rather

small, we use a comparative case study approach which is the most adapted to studying small

samples in more detail.

This paper is addressed to practitioners who are considering adopting online lending solutions to

reduce financial costs, to increase funding sources, to reduce transaction costs and get economies

of scale through this process.

Legal design of the different websites

As explained in the introduction, there are two major kinds of online lending websites:

commercial and microfinance. There are others which are slightly different, such as MicroPlace

which is actually a broker for security issuers lending to Microfinance Institutions. However, we

will not go into this for the limited purpose of this paper.

Legal forms of commercial online lending

The legal form of all the commercial lending websites are for-profit companies. This is brought

out in table 2. They all use auction mechanisms to ensure that borrowers and lenders get the best

rates based on market competition. Zopa was the first one in 2005. It took two years for others

in Europe to enter the market1, indicating that even in highly visible high technology sectors like

internet, there is a time lag between innovation and competition coming in.

A prominent quirk is that these are all essentially domestic operations. When Zopa wants to enter

a new market, such as Italy, it starts a new company. This is done essentially because legal

regulations including contract laws in different countries are complicated enough and private

international law rules are unclear in cross-border litigations, thus increasing risk significantly.

1 Donjoy in Korea and Propser in the US entered in 2005 and 2006 respectively, but we are looking only at

Europe.


Although US Aid considers these direct P2P lending sites, our detailed examination of the cash

flow movement indicates that cash does not move from lender to borrower for loans and vice

versa for repayments. Indeed, each of these players is an intermediary, taking a commission for

its operations.

The only exception to this intermediary role that we have found so far is the US based Virgin

Money. Virgin Money took over what used to be called Circle Lending. This site is essentially the

only facilitator that we have found which permits direct movement of funds between borrowers

and lenders. This is because the borrowers and lenders already know each other before coming to

Virgin Money. They come to Virgin Money's platform only to obtain legal documentation and to

build credit histories of loan repayments.

Legal Forms of Microcredit Online lending

There are a number of differences between Commercial online lending and microfinance online

lending, as embodied by the US based Kiva, probably the only well-known model.

The first and most obvious difference is that as opposed to the for-profit commercial online

lending, Kiva introduced a not-for-profit model for microfinance online lending.

The second difference is that Kiva operated as an international operator, transferring funds from

US based individuals to the rest of the world. Obviously, this introduced asymmetric information

based issues relating to trust which are greater in international capital movements than in

domestic movements, because legal and cultural institutions differ.

This led to a third difference: Kiva added a second intermediary in the supply chain of funds

from the US based lender to the poor borrower in the developing country. This intermediary was

the local Microfinance Institution. It is expected that the local MFI has more information on the

local borrower and this would overcome barriers to trust. Moreover, as opposed to borrowers in

developed countries, ultimate borrowers in developing countries do not have a computer. As a

result, they need a local bank who would receive the money for them. If they do not have access

to a bank, this function needs to be performed by a local MFI.

To overcome domestic legislation on protecting small savings, Kiva informs its borrowers that

the loans are interest free in any case, but it's better than giving outright donations because

interest free loans come back and can be reutilised for giving loans again to other needy

borrowers. It also presents to the borrower that its loans are interest free loans to MFIs, but that


MFIs would normally charge interest to their ultimate borrowers to meet their own operating

costs. Thus a fourth difference in the Kiva model is that lenders are not motivated by commercial

profits.

Since the loans are interest-free, Kiva does not require an auction mechanism and this is a fifth

difference between Kiva and the commercial online lenders.

European microfinance lending institutions have followed some features of the Kiva model and

have ignored other features.

As indicated in table 2, Both MyC4 and Babyloan, the two European Microfinance lending

institutions we are studying are for-profit institutions set up as companies. Thus, they are not

looking for donations, but are looking at a sustainable model of online microfinance lending. In

this they follow the same principles as other models such as MicroPlace or Intestros Without

Borders in the US and Rangle and GlobeFunder in India. The only other non-profit models we

have found are Dhanax in India and Wokai in China.

Table 2 – Legal design typology of online social micro-lending websites in Europe

Legal status

Non-profit For profit

Geographic

coverage

International Kiva BabyLoan, MyC4 (Sub-Saharan

Africa), Smava (Germany)

National Boober (Netherlands, Italy),

Kokos (Poland), Monetto

(Poland), Zopa (UK, Japan, Italy)

Again, we note that there was a two year gap in following the first-mover, indicating that the first-

mover advantage is again two years.

The second observation is that they are all following the Kiva lead by using local intermediaries

to help screen the ultimate borrowers and to help in collecting repayments.

One legal problem is that while France has allowed Babyloan to provide French savers money to

MFIs and borrowers in other countries, it has not allowed ADIE, a domestic French MFI to

collect small savings to onlend to French borrowers. Thus, it is clear that French laws are


providing protection from competition to French banks and they don't really care whether

individual French savers/lender are provided protection.

Social Impact

The comparative analysis of social impact of commercial online lending models and that of

microfinance online lending models has shown similarities and differences. Before discussing

these social impacts, a brief reminder of microfinance definitions may be in order.

A narrow definition of Microfinance is that of productive loans of small amounts to poor people.

Thus, this includes only business loans to help them improve their businesses, leading to higher

income out of poverty. A wider, intermediate definition, now gaining ground in Euopean

countires is that of social microfinance, which includes loans given to poor people for housing,

cars, education or anything which would permit the poor person to increase his productivity.

Finally, we have the widest definition which includes consumption loans, recognizing that money

is fungible and that if a person takes loans for any purpose, his welfare is increasing.

If the last definition is accepted, any loan to anybody has a positive impact. If it is traded through

a market mechanism such as auctions, evidently, the positive impact is on both the borrower and

the lender who makes a profit. Since Marginal Utility is positive for both parties, ethical questions

can be ignored to some extent as this is the basis of social exchange. Therefore, all commercial

online lending sites involve gains both for lenders and borrowers: otherwise they would not

participate.

In fact, participation of lenders has increased to include small savers since there is practically no

minimum lending amount: some sites allow even USD 25. These small savers therefore no longer

need to go to banks and get low interest on deposits or no interest on their checking accounts.

Of course, to some extent risk increases, but the high interest rate ensures that the Reward to

Risk ratio remains within the acceptable zone for the lender.

Similarly, participation of borrowers, who may not have got loans from banks, has also gone up

because the lower transaction costs imply that they pay lower interest rates on loans they take.

Therefore people have benefitted more than going to banks.

The social impact of loans from Microfinance online lending includes all the above advantages as

far as inclusive finance aspects are concerned. People who could not participate as lenders or

borrowers owing to small sizes can now do so. However, we would expect that financial


advantages are now skewed in favour of borrowers who get loans at lower interest than they

would from a bank or even a brick-and-mortar MFI. However, research results indicate that in

reality this is not true. The only significant experience is with Kiva. It is found that the second

intermediary, the local MFI has new transaction costs with this type of financing, which are the

costs of writing and uploading biographies of poor people onto websites. These costs

compensate for the interest free loans that they get from Kiva. As a result, no extra lowering of

interest cost goes to the borrower. The social surplus lost by the Kiva lender (who lends interest

free) is captured by the MFI or the people who are free lance writers. Therefore, to some extent,

employment may go up in a poor country.

MyC4 also indicates that it is financing smaller SMEs who are just beyond the Mcirofinance

limits. These small SMEs have no alternative source of financing. Thus, MyC4 manages to

include them too.

The social impact of online Microfinance has also helped growing awareness of the needs and the

rights of poor people to financing. This needs to be captured, at some stage, by brick and mortar

MFIs who could then accompany the entrepreneurs in a more human way than a website.

Trust Building: Three sources of trust in transactions

The review of the etymological roots and the related literature supports that three different

factors, or a combination of them, explain the making of trust: personality of the one who trusts,

competence and reputation of the one who inspires trust and finally the governance of a legal,

auto-regulated or cultural third party that enforces trust.

Specific disciplines tend to privilege some of this trilogy’s elements. Psychological literature

stresses rather on the personality of trustor. Marketing puts emphasis on the competence and

reputation of the trustee, a brand for example. Legal and economic theories consider that trust

can be built through the governance of the complying third parties, which regulate the relations

between the agents of exchange and conduct them to respect their promises and engagements.

The above tripartite typology corresponds approximately to typologies suggested by different

authors. Zucker (1986) identifies personal characteristics, institutions and the process of

relationships as sources of trust. McKnight and Chervany (2000) underlie three dimensions that

lead to trust and the willingness to depend on the others: a person’s disposition to trust, institution

which provide the needed conditions for a successful outcome in an effort, and the other party


with reliable traits such as competence, benevolence, integrity, and predictability. Adler has also

distinguished tripartite sources of trust: Familiarity through repeated interaction, assessment of

vulnerability and trustworthy values and norms (Adler, 2001). For a comprehensive review of

literature on sources of trust, one should refer to Assadi and Oleysker (2006) who adhere also to

the same trilogy of sources of trust.

We will also adopt the tripartite model of trust sources for analyzing the generators of trust on

the different peer-to-peer lending websites. However, the first source of trust, personality of

trustor, will not be included here because investigation on personality requires personal interview

of lenders and borrowers which goes beyond the cadre of our observational method of case

studies.

Trustee as the source of trust

Trust can emerge from a perception of partner’s competence, dedication, benevolence, honesty,

available means, absence or limitation of opportunism and resistance to outside shocks. The

counterpart is believed to behave in accordance with prior commitments and avoidance to take

excessive advantage of an exchange partner even if the opportunity manifests.

Here, trust has a cognitive basis: knowledge, impression or inference that the partner has the

ability and intention to perform according to expectations, and to refrain from opportunistic

behavior. However, one might ask how does the trusting party finds out that his/her counterpart

is worth trusting? The answer is: the trustor comes across the other party’s trustworthiness, either

directly thought relational experience, or indirectly via reputation, as a consumer may find out

about a brand’s competence through direct usage or word-of-mouth communication.

Trust acquired by relations is seldom spontaneous. It is often progressive, adaptive and evolves in

a slow process, starting with minor transactions in which little trust is required because little risk

is involved and in which partners can prove their trustworthiness, and consequently expand their

relation and engage in major transactions (Shapiro 1987). As the relationship develops,

knowledge about the other party fosters the predictability.

“Relational signaling” (Lindenberg, 2000), a special type of relational experience, means the

observation of actions and expressions, aimed not only at the observer, but also at others, as

when the latter can infer something from the way a partner treats his colleagues and employees.

Due to a lack of direct relational experience, one might rely mainly on the other party's

reputation, originating from experiences and judgments issued by informal sources such as peers


and friends. The role of reputation to engender trust is noticeably emphasized in marketing

(Doney and Cannon, 1997) as well as in economics (Williamson, 1991). If a customer perceives

that other people think that a brand is fair, just, and good, s/he may trust the brand enough to

purchase it (Anderson and Weitz 1992).

Reputations emerge as a result of social network effects, when information on an actor’s

behaviour in one relation spreads to others via an information network (Granovetter, 1985). It is

this social or collective nature that gives reputations the power to reduce uncertainty and serve as

a means to engender trust. Electronic markets with their particular network characteristic can be

seen as important facilitators for the diffusion of reputation (Einwiller and Will, 2001).

For a social lending website to be trusted by both lenders and borrowers, satisfaction and

excitement of individuals who have used the site are important (relation-based trust), and who

subsequently share the idea with others (reputation-based trust). Word of mouth and popularity

are exceedingly important for attracting peers and convincing them to proceed to transactions.

Once trusted, a P2P website investors consider repayment behavior, reputation, relational

signaling, along with borrowers’ projects. MFI or field partners do the same.

Third Party Institutions as the source of trust

Even if there are many relationships in which trust is grounded in mutual assessments, there are

many others in which the trusted person does not honor his promises. The possibility of

opportunistic behavior, defined as self interest seeking with guile and incomplete or distorted

disclosure of information with calculated efforts to mislead, disfigure, disguise or obfuscate

(Williamson, 1985), creates a major source of uncertainty about a partner’s trustworthiness and

consequently raises the transaction costs actors on monitoring others parties’ behavior

(Williamson, 1975). In addition to the risk of partners’ opportunism, people do not have ongoing

relationships in a complex society to judge others’ trustworthiness. Strangers or people who

encounter each other infrequently need to be assured more for cooperation than people who

interact frequently and repeatedly.

In the case of trust deficiency, and when people do not know each other enough, they may look

for the third institutional parties to sponsor trust through coercion by rules and sanctioning the

partners who do not live up to their promises. The third parties as sponsors or enforcing agents

of trust can emerge from cultural, politico-legal or non-governmental organizations.


Compliance with cultural norms of honesty and non-malfeasance is secured by arranging

incentives for observing obligations and the threat of exclusion or non-inclusion (Kandori, 1992).

For example, on Smava.de group belongingness, in addition to conventional criteria, is

considered as an important element for having access to loans.

Trust can also be created between parties thanks to reliable and safeguarding politico-legal

systems which support and enforce contracts (Lyons and Mehta, 1997). For example, to become

a Kiva’s "Field Partner", the postulating microfinance institution must currently serve at least

1,000 active microfinance borrowers, have a history of at least 2-3 years of lending to poor

and/or vulnerable people for the purpose of alleviating poverty or reducing vulnerability, be

registered as a legal entity in its country of operation and be able to show at least one year of

financial audits and preferably be registered on the MIX Market (www.mixmarket.org).

Agents might also rely on a third party agency to verify the credentials of their partners. Third-

party endorsements and expert endorsements (Dean & Biswas, 2001), can possibly change

opinions (McGinnies & Ward, 1980) and influence purchase intentions (Ohanian, 1991). For

example, the Polish websites in our sample, Kokos and Monetto, verify not only borrowers’

profiles through confirmed bank personal data, ID and income statement evidence along with

telephone proof; but also consult all different third party certifiers such as credit bureaus (BIG),

debtors’ registry (KDR), and Infomonitor which is an economic information bureau. They also

have agreements with collection companies and provide loan insurance options as well

(Owczarek et al.).

Marketing analysis of the European micro-lending peer-to-peer websites

Enterprises achieve, knowingly or not, their marketing and commercial goals through a

combination of four elements of the marketing-mix, product, price, place and promotion. In the

following we comparatively analyse how the members of our sample apply their marketing

strategies.

Product Policy Analysis of Online P2P Lending Websites in Europe

A product is “anything that is offered to a market to satisfy a want or need” (Kotler, 1997).

Correlatively, in a market of financial services, the motivating reason for buying a product resides

in its benefit solving a user’s need or want, and provides value (Ledgerwood and White, 2006).


Micro-lending as a product is a small loan offered to a person outside of the conventional

banking and financial sector. The benefits of these loans are higher returns for lenders and the

ability to obtain loans for borrowers.

The Internet increases benefits in many ways to its users: convenience, personalization, and most

importantly, knowledge enabling consumers to shop by comparison and competition (Frost and

Strauss, 2001).

There is a sustainable relationship between the customer value hierarchy and the economic status

of countries. Currently, most customer-value in developed countries such as in Europe resides in

the product-plus services level, while in developing countries it is mostly based on the basic

expected benefit of the product. These differences in the focus of product marketing levels have

been influential in the development of micro-lending in both developed and less developed

countries. Simply obtaining the loan is almost all that is expected of the micro-lending companies

in underdeveloped countries, not much online convenience services.

In Europe, the competition between online P2P lending websites is considerably based on the

support services. Customer support can actually be one of the main reasons a consumer chooses

one online firm over another, especially when the product is sophisticated and confusing, a good

quality firm will have customer support services that are easily accessible, available continuously,

and facilitate customer usage. The exception is logically MyC4 which targets the needing

entrepreneurs, out of Europe, in Sub-Saharan African entrepreneurs.

For example, Kokos.pl position itself as not only as being able to offer a much more beneficial

interest range for both the lenders and borrowers, but also a higher level of security than on

other web based auction systems (Janik, ). Higer return on investment (ROI) is also the value that

the German Smava promises to lenders: Despite the current credit crisis, 99% of the

approximately 2500 Smava’s active lenders earned a total profit of 210,861 Euro in 2008, while

the 1% who did incur a loss, lost only 60 Euro. For that period, the ROI ranged from 5 to 10%.

While the biggest loan volumes are generated in the US market, many p2p lending websites have

been established in other markets such as in Europe. The following table overviews loan volumes

operated by the members of our sample. Still, the reader should remember that they are not

directly comparable for they are cumulative since launch of each service and represent different

time spans.


Since its launch in 2007, Smava, the German p2p lending service, has funded, up to March 2009,

1350 loans for a total loan volume of about 7.9 million Euro, approximating 10.7 million US$

(P2P-Banking.com , 2009). In 2008, the average loan requested and granted was between 6,000

and 7,000 Euros (Earlybird.com, 2008).

On our Polish websites, the minimum amount of loan is $25, while the maximum amount is

$125,000 on Kokos and $50,000 on Monetto. Both of them consider monthly installment for

repayment, but while the payment term is 12 months on Kokos, it is 36 months on Monetto

(Owczarek et al.).

Table 3: Loan volumes of P2P Lending Sites, Million US $, January 30th, 2009

Boober 3.3

BabyLoan 0.8

Kiva 0.1

Kokos 57.9

Monetto 1.5

MyC4 0.9

Smava 9.0

Zopa 45.6

Source: P2P-Banking.com, P2P lending companies by loan volume - Jan 09

Kokos.pl has now extended its product lines to insurance options for borrowers, in cooperation

with Cardif Polska S.A and Cardif Assurances Risques Divers S.A.. Insurable risks include death,

disability to work and unemployment. There is a choice of eight different insurance packages.

Monetto.pl, offers also offers new products, in addition to P2P lending, such as financial facilities

on some e-commerce websites in Poland such as Kupujemy.pl (P2P-Banking.com, 2008).


Pricing Analysis of Online P2P Lending

For customers, interest rates represent the cost or price of loans. This price, like other types of

price, is influenced by factors such as: competitor’s pricing, profitability targets, consumer’s price

sensitivity, cost of supplying the product to the market, and especially risks, regulations, and

economic and social considerations within the banking industry.

There is usually high consumer demand elasticity for low interest rates. Charitable organizations

such as Kiva, do not charge a rate at all, while Zopa sets their own interest rates. On Monetto.pl,

the interest rate is fixed, always annually, betwwen lender and borrower directly. Still, lenders

often declare the lowest levels at which they might accept to lend (company’s site). On

Monetto.pl, the interest rate varies 1 to 22%. According to Smava.de in April 2009, the borrower

pays a fee only upon successful completion of a credit contract: For a period of 36 months, the

borrower pays a fee of 2.0% of the loan, alike 0.66% per year (minimum 40 Euros); while for a

period of 60 months, the fee amounts to 2.5% of the loan or 0.5% per term year (at least 60

Euros).

1 to 22%. Table 4 shows the average interest rates being provided by our sample websites which

are always higher than the conventional rates. Still, one should notice that the higher interest rates

on the online lending websites cover the cost of petty loans and high risk of some borrowers’

credit record. Studies show that people interested in borrowing through social lending are

distinguished by significantly higher risk having more often problems with payments on their

liabilities in the past. Main reasons for interest in social lending are related to more favorable

interest rate compared to the banks, inability to obtain loan at the bank and cumbersome bank

formalities (Owczarek et al.).

Table 4: Prime Rates and Social Lending Sites’ Interest Rates: Europe and United States

Prime Rate Interest Rate

September 2008 January 2009 Online Social Lending Site (%)

Britain 5.00% 5.00% 8.75 to 16.99% (Zopa)

Germany 4.00% 3.75% 4 to 18% (Smava)

Poland 5.48% (31/12/06) 1 to 22% (Monetto)

United States 5.00% 3.25% 0% (Kiva)


The cost of producing online P2P services encompasses: Programming fees for updating

products, services, and security; maintenance of the site; marketing of the site and Salaries

(Prosper Lending Review, 2007). They might also charge lenders for the same online services.

The following table shows the comparison of the priced charged to each party in our sample.

Investing in the platform is free of charge. MyC4, however, charges the African business two fees

for providing the infrastructure. One flat fee of two percent payable is charged when the loan is

disbursed and another fee of two percent of the amount repaid on the basis of a declining

balance. Loans are repaid by the African entrepreneur on a monthly basis, with the incentive to

repay as quickly as possible because the interest rate is applied on a declining balance basis. The

currency used at MyC4 is typically the Euro, however, the local currency may be used depending

on the amount of the loan issued.

Table 5: Fees of Using Social Lending Sites: Lenders and Borrowers

Cost for Lender

Servicing fee % of loan

Cost for borrower

% of loan

Boober (Italy) - 19.95 €

BabyLoan 1€ per 100€ Free

Kiva Lender fixes price, upon repayment lender chooses whether to donate funds, re-lend, or

withdraw.

N/A

Kokos - 0.5%

Monetto 0.5 to 1.5% 0.5 to 1.5%

MyC4.com No fee for lenders 2% upon disbursement, then additional 2% of total when loan is

completed

Smava 4 € per successful transaction 2 to 2.5%

Zopa No– users buy a Zopa CD Depending on CD

Source: Corresponding websites


There are also some non-pecuniary psychic costs such as confusing websites, slow Internet,

service speed, or other technical frustrating problems (Frost and Strauss, 2001). While

administrative and financial costs usually provide the foundation for interest rates at a banking

firm by using a percentage markup associated with the costs, risk is a large influencing factor in

lending (Ledgerwood and White). In order to offset the psychic cost of risk, banks charge interest

rates at different levels corresponding to the market.

One can logically expect that when online interest rate, along with all other pecuniary and non

pecuniary costs, is lower than that of conventional banks, more consumers shift from traditional

channels to more affordable option of online social lending. The contrary is also true. As the

state and financial environments in different countries reduce basic interest rates to face the

current financial crisis, one might wonder if the online P2P lending websites will remain attractive

as lending and borrowing prospects.

The pricing objective and approach varies from company to company. Considering the small

amount of fees and commissions, the P2P social lending websites need to multiple the volume of

transactions, and accordingly accelerate growth. Some site charge membership fees while others

implement a percentage by transaction approach.

Table 6: Price Settlement on Social Lending Websites

Boober P2P Auction

BabyLoan Two intermediaries

Kiva Two intermediaries

Kokos P2P Auction

Monetto P2P Auction

MyC4 Two intermediaries

Smava P2P Auction

Zopa P2P Auction


Distribution Analysis of Online P2P Lending

Place, another element of the four P’s, encompasses the various activities the company undertakes

to make the product available to target customers, through channels of interdependent

intermediaries, such as suppliers, wholesalers, brokers, resellers, agents, retailers, merchants,

agents, facilitators, and so on (Kotler, 1997). Internet has pushed the high-tech strategy further

resulting in market deconstruction, and types of new intermediaries (Frost and Strauss, 2001).

For a social lending site to be available to the public, it needs to have suppliers, which are also

known in this type of industry as capital providers or investors. Charitable social lending

organizations (such as Kiva) are funded by grants and group or individual philanthropic

donations while many others funded by private lenders or investors.

On the borrowers' side, Kiva works with "Field Partners" which are local existing microfinance

institutions; usually short on funds, but with the access and ability to choose qualified

borrowers/entrepreneurs from world-wide impoverished communities.

On the lender side, Kiva encourages potential loan givers to choose directly among entrepreneur

profiles uploaded onto the site and subsequently sponsor their business. On listings borrowers

are presented in terms of name, age, country, business, conditions of repayment, etc. Lenders are

also given the option to present themselves on the site. The course of a loan is usually between

six to twelve months and its amount can be as little as $25 at a time. Once a loan is repaid, the

lender can withdraw the funds or re-loan them to a new entrepreneur.

Boober.it does not intervene to establish automatic matching. Parties select their partners.

Borrowers decide about the conditions of the loan that they need: Amount, duration and,

especially interest rate and then publish on-line with your request. Lenders decide also about

amount of loan and risk profile among requests published online: The transfer of money takes

place only when a loan request is fully funded. Boober.it does not ask lending investors to

transfer money to a bank account waiting to be affected to borrowers. Thus, the money stays at

lender’s disposal until the transfer.

On Smava.de borrowers declare the amount of money that they aim at - compulsory between

1,000 and 25,000 Euros, the purpose of loan and the interest rate that they are ready to pay.

Borrowers with a credit grade of at least “H” and a sufficient income, have good chances for

obtaining a loan. As 95% of the German population has credit grades between “A” and “H”;

only about 5% are excluded on Smava because of the credit records. Between 2007 and 2009,


about 60 percent of the listings were funded (P2P-Banking.com , 2009). Almost half of the

borrowers on Smava are self-employed persons and freelancers (Earlybird.com, 2008). The share

of online transactions in the overall credit market of 60 billion Euros per year is 4 percent in

Germany. Smava capitalizes on a growth rate of 30 percent per annum of this sector in the years

to come (Earlybird.com, 2008).

The first fifty Smava lenders funded about 1,690,000 Euro, representing around 21% of total

loan volume (P2P-Banking.com , 2009). Lenders on Smava might consider an investment line

from 250 up to 100,000 Euros at a desired interest rate. In addition to traditional investment

criteria such as risk and repayment profile of a borrower, investors will receive supplementary

information on borrowers such as membership in a group. Each group is formed according to

the repayment behavior, and so the reliability of its members. Smava groups are thus an

important element for having access to lower interest rates.

Kokos.pl checks primordially borrowers’ credit history through Biuro Informacji Gospodarczej

(BIG) to assign them rating in the system. The borrowers with higher rankings are more likely to

find lenders and better interest rates. Kokos.pl offers two ways of lending: "borrow now" feature

and auctions. The choice between these options depends on the conditions of the loan and the

intended purpose of the credit. For ensuring security, Kokos.pl spreads each loan across a large

number of lenders to offset the risks taken on by any single lender. Since Kokos.pl has access to

no more than polish credit rating institutions, only residents of Poland may use the system at this

moment. It does not make contact between lender and borrower. It administers and transfers the

funds. The users always transfer funds to Blue Media’s account which is then sent out to the

appropriate recipients.

On Monetto.pl, another Polish P2P website, borrowers and lenders have interestingly dissimilar

sociological profiles. Borrowers are usually aged 35 to 50, and live in rural areas or small cities,

while lenders on the other hand are typically aged 25 to 30 and live in the major cities (P2P-

Banking.com, 2008). On Monetto.pl, one can borrow USD 25 000 at once and 100 000 USD in

total (company’s site).

When an individual borrows a Zopa loan, s/he or she can publish a profile and explain the

reasons of the loan request to the potential lenders who might choose to lend (help) by buying a

Zopa CD. To invest (lend) and buy a Zopa CD in the United States, lenders must be over 18,

U.S. citizen or permanent U.S. resident, and fit Zopa's underwriting requirements. In March

2008, those requirements meant: (a) a minimum credit score (FICO) of 640; (b) income of $2,000


per month; and (c) a few years of credit history. In the U.S., those who invest in a Zopa CD get a

guaranteed, federally insured investment. Buyers of a Zopa CD can choose whoever they'd like to

help based on where they live, what happened to them, a shared interest, or by loan purpose.

Investors decide how much to they want to help (loan rate) which means a reduction in the net

monthly loan payment that a borrower needs to pay. The bigger their Zopa CD, and the lower

the rate they choose to receive the more help they give.

Focusing on Sub-Saharan Africa, MyC4 allows African entrepreneurs of small and medium size

businesses to obtain loans through a network of local providers. All applicants must undergo a

screening process before they are accepted into the MyC4 network.

MyC4 allows investors to see all potential borrowers, a description of the business, the amount of

loan needed, and the maximum interest rate that can be afforded. Then a Dutch-style auction

takes place among lenders who would like to provide the loan. This process ensures that the

African entrepreneur is receiving the best deal possible.

According to its website, the distribution channel of Babyloan is composed of four levels: Social

lender credits Babyloan’s bank account for the amount of loan, plus one Euro. Babyloan retains

the one Euro to cover money transfer costs and the website operating expenses and send the

money to a specific local Microfinance Institution (MFI) partner. The MFI affects finally the

money to an entrepreneur of the initial lender’s choice. This latter receives the loan to launch or

develop his/her project. Since Babyloan works as a REfinancing platform and not as a direct

financing system, it can happen that the MFI already "advances" the loan to the entrepreneur at

the moment of the lender’s commitment earlier than the effective reception of money.

When the entrepreneur pays back, then money travels back too. The entrepreneur reimburses the

loan to the MFI which then transfers the money into the lender’s account at Babyloan piggy

bank. The lender finally decides to take back the loan or to support another project.

Communication and Promotion Analysis of Online P2P Lending

The fourth of the four P’s is promotion, also known as communication, encompasses all activities

such as advertising, promotion, direct marketing and public relations that the company

undertakes to communicate and promote its products to the target market (Kotler, 1997). We will

now consider the types of promotion being used by social lending sites.


Despite continuous growth, the P2P micro-lending market is still relatively modest compared to

its potential. For example, Smava’s market is still composed of less than 5000 active users (P2P-

Banking.com, 2009). Internet is the primary media for the respective websites to attract new

customers through advertising, news stories on financial websites, propagating press releases,

links to other sites, and especially registering with search engines.

However, a short survey 2009 by the authors discovered that the P2P social lending websites do

not exploit the potential of Internet, for example online indexation, to promote their services. On

April 30th, the authors analyzed the performance of the research sample’ members on the most

important search engines Google and Yahoo, for the some relevant keywords: P2P lending, social

lending, peer lending, micro-lending, microlending, micro-credit, microcredit, microfinance, and

personal loans. The objective was to check if the sample’s members appear on the first page of

results, containing 10 links, for each keyword.

The observation was unexpected: none of our European members appeared, while the American

websites, not for profit such as Kiva, or especially for profit such as LendingClub, PertuityDirect

and Prosper came into view most often.

It seems that the European websites privilege most likely some other innovative methods. In

2008 for example, Smava sent its lenders an email asking them to produce short videos telling

their personal experiences using the site. The German P2P lending website remunerated by 50

Euro (approximately 75 US$) for each posted user-generated video (P2P-Banking.com , 2008).

Kokos.pl, as the first Polish social lending site, capitalized on a large coverage by mainstream

media, including the major newspapers, magazines and 2 TV stations, all within the first week of

the launch in February 2007. At present the system is largely discussed on the forums, industry

portals and blogosphere.

Conclusion

We have endeavored to study the leading issues with the most significant impacts on the

entrepreneurial business of online P2P micro-lending in Europe. The legal environment

examination firstly revealed that all sample’s members is rather for profit and national-market

oriented companies. Those which go international create independent operations in each new

market. The differences between not-for-profit Kiva and European for-profit P2P social lending

websites were also widely discussed.


Secondly, the social impact analysis revealed that investors and borrowers consider the P2P social

lending websites as an appropriate channel to reintegrate into loan-related transactions instead of

the conventional financial institutions which discourage some by low interest rates, and discard

some others because of modest credit records.

Trust issue was thirdly discussed and divulgated the importance of satisfactory relations, positive

reputation, but also the third parties such as group belongings, legal instances and independent

certifiers. Finally, a comparative analysis of the marketing strategies of the sample’s members

provided insights about similarities and differences between different websites in terms of

product, price, distribution and communication of their P2P lending operations.

The limitations of this study should also be mentioned. They might orient further research:

Comparative analysis between websites of different national origins, mainly American and

European, and dissimilar missions, non-for-profit or commercial to better understand possible

strategies and operations in the field. A more important sample than the one used in this study

should then be envisaged.

The basic intermediation role of social lending sites is exchange facilitation, while many more

roles are played by them as the research in hand showed. As a result, the intermediation roles of

the P2P lending websites can also be an axis of research.

Finally, a research project might investigate lenders and borrowers personality and collaborative

attitude in the process of trust building which is necessary for P2P transactions. The personality-

based trust, as a psychological trait, is sometimes prior to relationship and without complete or

prior knowledge about others. What is the psychological profile of those who prefer to lend and

borrow money out of conventional channels? The answer provides insights for better

segmentation and targeting.


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“CUSTOMER DESERTION IN fondiBESA, FACTORS AND THEIR

ANALYSIS”

Dr. Altin Muça

Director of Marketing Department

“fondiBesa”

Rr. “Brigada VIII”, P.5, Tirana, Albania

Tel: +35542253841/2,

E-mail: [email protected]

www.besa.org.al


ABSTRACT

Type of Paper: Research Paper

Purpose of the paper: Considering that customer desertion has several negative effects in

financial institution self-sufficiency, efficiency and productivity, I carried out this study aiming at

identifying factors that influence the quality of the client-MFI relationship and finding ways how

management might effectively use its influence to make necessary improvement and adaptations.

This study follows a few modest research studies on separate cases of client desertion. The main

contribution of this research is to Albanian and similar South-East Europe MFIs. It will also be

of benefit to researchers who need to measure customer desertion rates and find ways to build

customer loyalty.

Design/Methodology/Approach: Methodology used is "survey", as a way to achieve the best

result, closer to reality. The survey was performed through individual interviews, fully/partially

structured questionnaires, and phone calls/questionnaires filled in by clients. It was achieved by

defining the "sample", which should represent, without any "deviation", the targeted clientele for

this study. All respondents have been customers of fondiBESA, but are not at present. Two main

formulas were used in analyzing the data: Formula–Waterfield, considered the most suitable

completed formula, accepted by the majority of microfinance researchers, simple and easy to use,

and Formula ACCION.

Key results: The study outlines factors that influence fondiBesa customer desertion: “resters” -

need for loan later (i.e. considered as potential clients), dissatisfied lost to competition-need for

bigger loan amount than offered by fondiBesa, dissatisfied with credit terms and conditions.

Results are important because they show that there is a need to build the loyalty of “resters”,

understand which products need to be refined, new products to be provided to ensure they will

return to us latter; see how many clients went to competitors, why and what they are looking for,

in order to develop competition survival strategies; see what are our competitive advantages and

build on them, understand what type of support credit officers need to be more effective in

reaching lost clients. These are the final results of the study. This study will be followed by other

studies because our clients’ needs, preferences and behaviours change and our main goal is to

respond them in the best way possible.


Impact: By understanding the complexity of factors influencing customer desertion, fondiBesa

will be able to improve its products for the target group. This will have a direct impact on client

satisfaction and improvement of retention rates, which further on will have a beneficial impact

on overall sustainability of the institution. Being the first study of this kind in our institution, it

will serve as a tool for further research.

Value: This research is unique and original because it is focused on that group of people who

used to be clients of fondiBesa.

Key Words: loyalty, desertion, retention, fondiBesa


GENERAL DESCRIPTION

fondiBESA started its activity in February 1994 as a department of the Albanian Development

Fund under the authority of the Council of Ministers, to implement the urban microcredit

project, funded by the World Bank.

In May 1999, with the Decision of the Council of Ministers, No. 207, dated 28.04.1999, this

project was transferred from the Albanian Development Fund to fondiBESA with OSFA as the

Founder.

fondiBESA is a legal entity operating as a non-government, non-political and non-profit

organization, in compliance with Albanian legislation.

The mission of fondiBESA is to support the country in its economic growth and poverty

reduction in urban and semi-urban areas, by promoting the micro, small and medium-sized

enterprise sector in Albania, through the creation of a private self-sustaining Albanian

microfinance Foundation.

The goal of fondiBESA is:

Promotion of small private microentrepreneurs, who want to develop and extend their existing

activities or start up activities, including here the self-employed that manage small activities, as

well as the support of further development of medium-sized enterprises in Albania.

By achieving this goal, fondiBESA aims to:

• Reduce poverty.

• Promote job creation opportunities

• Promote self employment

• Assist micro and small enterprises in developing their businesses

Based on these objectives, fondiBesa:

• Provides funding for these businesses, based on market conditions

• Provides technical assistance for these businesses based on the practices of business

management

• Trains and educates new managers on up-to-date concepts and practices of business

management.


fondiBESA finances every type of legal micro, small and medium-sized business that generates

income such as:

• trade and services

• production or processing activities

• handicrafts

• family tourism

• construction (especially repairing)

• transport

• Bills or custom tax payment, etc.

Actually, two particular projects for the promotion of self-employment are under way:

• Funding of new businesses for young people

• Funding of new business women victims of trafficking

ACTIVE CLIENTELE BY GENDER

MALE80%

FEMALE20%

ACTIVE CLIENTS BY SECTOR

Trade69%

Construction2%

Service18%

Tourism1%

Transport3% Other

3%

Prod& Handycraft

4%


General Data on fondiBESA activities

Cummulative Disbursement (in million $US) 156

Cummulative number of disbursed loans 31,785

Loans Outstanding (in million $US) 31

Active clients 8,075

Average active loan (in $US) 3,853

Portfolio at risk (in %) (> 30 days) 0.62%

Actually fondiBESA operates out of

31 Offices and covers about 80% of

the urban and semi-urban areas of

Albania.


Main Indicators as of end of March 2007 Indicators

Indicators of portfolio quality

Portfolio at risk (>30 days) 0.62%

Profitability Indicators

Return on assets (annualized) 9.39%

Return on Equity (annualized) 18.50%

Productivity Indicators

Operational self-sufficiency 163.3%

Financial self-sufficiency 126.1%

Yield on Portofolio (annualized) 23.84%

Capital/Portfol 50.89%

Capital/Liabilities 102.31%

DR

2001

In %

RR

2001

In %

DR

2003

In %

RR

2003

In %

DR

2004

In %

RR

2004

In %

DR

2005

In %

RR

2005

In %

DR

2006

In %

RR

2006

In %

Total 47.40% 73.26% 41.56% 73.08%

20%

84%

23%

83%

16% 88%


STUDY STRUCTURE

This study is structured as follows:

1. A general analysis of the DR and RR indicators for all Regional Offices of fondiBESA for

the period 2000-2006.

2. On the basis of the results, the definition of an office that will serve for the "pilot study",

where the study will be performed.

3. Elaboration of a questionnaire to identify reasons for customer desertion.

4. Carrying out the study through questionnaires in the Regional offices in Tirana, Vlora,

Korca and Shkodra.

5. Processing of questionnaires.

6. Findings and Recommendations.

Funding sources of fondiBESA

are:

• Equity of Fondi “BESA”

• “SOROS” Foundation

• World Bank

• Albanian Government

• Spanish Government

• Etc.


STUDY OBJECTIVES

This study aims to identify clearly some of the tangible reasons that the management staff may

use to influence most effectively for immediate improvement or adaptation.

On this basis, this study aims to identify the following categories of clientele:

a. No need for a second loan

b. There is a need for a second loan, but later

c. There is a need for a second loan, but the client will choose a bank or another

microcredit institution

d. There is a need for a second loan of a much larger amount than fondiBESA offers

e. The client is not satisfied with the terms of credit offered by fondiBESA

f. The client is not satisfied with the level of service offered by fondiBESA staff

g. Other reasons that may be specified by the interviewed person.

METHODOLOGY

The methodology to be used will be the "survey" as a way to achieve the best result closest to

reality.

Primary research through the "survey" is seen as structured in a summary form to identify only

those elements that have functional value for the study.

“SAMPLE”

In our opinion, the most delicate issue in this study is the definition of the "sample", which

would serve as the basis of the study. This “sample” should represent, without any "deviation",

the targeted clientele category for this study.

We believe that a "sample" of 3% of active clients, that is about 212 clients, that will be included

in the survey is a representative "sample" to produce "findings" and the appropriate conclusions.


Calendar of Study Week 1 Week 2 Week 3 Week 4 Preparation and approval of study structure

Collection of the information from the questionnaire

Initial processing of the results

Presentation of the study. Improvements afer potential suggestions and remarks

Preparation of questionnaire

Initial processing of the results of the questionnaire and preparation of the Draft-Study

Preparation of questionnaire

Delivery of questionnaire

I. A general analysis of the indicators DR and RR for all Regional Offices of

fondiBESA, for the period 2000-2006.

Improvement in the level of reliable clientele through monitoring and knowing its desertion rate

is one of the indicators that should be considered by microfinance institutions.

Analysis of this indicator is important because it will also affect the long-term success of the

institution that relies on the "loyal" clientele.

This "loyal" clientele is the "core" for new products or services that might be offered by

fondiBESA within the framework of a different status and the expansion of the range of its

products and services in the future.

The influence of customer desertion on the activity of the Microfinance Institution should be

carefully analysed because it has several negative effects such as:

• negative influence on financial self-sufficiency

• reduces the efficiency and productivity

• missing profits

• additional marketing efforts are required

• negative influence on social issues

• a greater chance of losing the poorest customers

• limited time to have a positive impact


Definition of customer desertion

Customer desertion has to do with the rate at which active clients do not renew a loan, through

receiving a new loan.

Although this is a general definition, measuring customer desertion is estimated:

• According to the time period

• According to the nature of financial services

• According to institutional procedures

Measuring the customer desertion rate

Measuring the customer desertion rate is done by means of several calculation techniques that, on

the whole, are based on information according to the following indicators:

Explanation of key terms

• DR: Desertion Rate

• LP: Number of Loans paid off during the period

• WO: Number of Loans written off during the period (or

otherwise classified difficult or unlikely to be paid)

• FL: (follow-on loans) – Number of repeated loans during the period

• AC begin: Number of active clients at the beginning of the period

• NC: Number of new (first time) clients during the period

• AC end: Number of active clients at the end of the period

• L: Number of loans disbursed during the period

• Formula – Waterfield – Standard of CGAP

• This formula focuses on the key decision of the client – that means in the decision of the

client, who after the repayment of the current loan, he/she "receives or wishes to receive

a subsequent loan”.

• When a client chooses to receive another loan he/she is considered as a repeat customer,

regardless of whether there is a period of "rest" ie distance in time between the repaid

loan and the subsequent loan.

• RR = FL (formula Waterfield)

LP


Some limitations of this formula

• This formula provides RR for a credit cycle.

• To calculate the customer desertion and retention (repeat loan) rate for a year in a

microfinance institution, the average loan duration should be taken into consideration.

• For example, assume that RR under this formula is 0.8 (80%). If we think that the loan does

4 cycles during the year, then (0.8x 0.8x 0.8x 0.8) = 0.41 (41%) of clients are repeated

customers.

• When RR> 100%, we must deduct the customers who are expecting to receive the loan.

Formula 2

� RR= (L-NC)____________

(AC begin + NC – AC end)

� RR = FL___

(LP+WO)

Formula ACCION

� DR = (AC begin + NC – AC end)

AC begin

� This indicator is estimated for activities that have not just started.

� It primarly indicates the client retention for the institution

� It is used for certain periods of time.

� RR = ____AC end_____

(AC begin + NC)

� DR= (AC begin+NC+R–AC end)

AC begin

R - “Resting” clients: Number of clients who, after the repayment of a loan, do not receive a

second loan though being satisfied with the service. They do not need a second (other) loan or

expect to receive a second (other) loan after a short time.

• This is the most completed formula accepted by the majority of microfinance researchers.

• No formula may show us what will be the eventual reaction of customers (mainly those who

do not repeat the loan).


• When, from the calculations, the number of repeat customers is considerable, then it results

that RR is approximately 100%. But, in order to obtain a more reliable level of this indicator,

it is necessary that the calculations should be done for longer periods of time.

• The longer the period for which this indicator is calculated, the more complete and near to

reality this indicator is.

Measuring the customer desertion rate, seen from an analysis of factors influencing this

indicator

Last type of product used

• Use of services

• Poverty situation

• Level of customer loyalty

• Seasonality

• Level of loan payments

• Business variables

• Household economy variables

• Characteristics of Individuals (geographic)

• Use of credit

How to identify the customer desertion rate

In order to identify and analyze the customer desertion rate we used the following tools:

• Individual interviews

• Levels of RR counted as not reliable

• Taking signal for further analysis

• Fully or partially structured questionnaires

• Phone calls / face to face interviews / questionnaires completed by the clients themselves

• Staff involvement.


The Data of this indicator in fondiBESA

REGIONAL

OFFICES

AC-BEGINNING 2005

NEW COMMERS YR 2005

AC-ENDING YR 2005

DR

2005

RR

2005

AC-BEGINNING 2006

New Comers

Jan-Sep 2006

AC-ENDING SEP 2006

DR

JAN-SEP

2006

RR

JAN-SEP 2006

Shkodra 525 178 579 24% 82% 579 139 596 21% 83%

Korce 701 258 762 28% 79% 762 320 935 19% 86%

Tirana 1072 442 1303 20% 86% 1303 438 1581 12% 91%

Vlora 416 173 455 32% 77% 455 144 504 21% 84%

Elbasan 900 302 1002 22% 83% 1002 228 1105 12% 90%

Gjirokastra 376 128 375 34% 74% 375 91 393 19% 84%

Berat 755 187 835 14% 89% 835 216 924 15% 88%

Durres 688 179 685 26% 79% 685 187 761 16% 87%

Peshkopi 9 53 72111% 116% 72 36 92 22% 85%

TOTAL 5,442 1,900 6,068.00 23% 83% 6,068 1,799 6,891 16% 88%

Given the above-mentioned data, it results that the level of client repetition is about 88%, while the customer desertion rate is about 16%.


II. Summary of the results: Regional Offices of Tirana, Korca, Shkodra and Vlora

(Number of questionnaires 212)

Key Findings of Study

The main findings of the study would be identified entirely based on results of the standard questionnaire and on

possible links and correlations among different responses in the standard questionnaire

A. General data about businesses interviewed.

1. Gender.

About 73% of the interviewed persons were male and 27% female.

It is noted that the biggest role and weight stands for males, but when compared to previous

years, we see that the role of women is always increasing. This is more evident in the Tirana area,

where this percentage is 68% for males against 32% for females.

In the area of Korca and Vlora the growing role and weight of women are also evident.

It is not the same in Shkoder, where we have 92% males and 8% females.

Active clients according to gender

2002-2006 2002 2003 2004 2005 2006

Quarter I

2007

Males 79% 83% 83% 81% 80% 80%

Females 21% 17% 17% 19% 20% 20%

The results of the study show that this division between males and females is similar to the

distribution of active clients according to gender in fondiBESA.


Charting the distribution according to gender in years, it is seen that there are almost the same

levels: 17-20% female and 80% -83% male.

Regarding this indicator, the “sample” is considered representative.

2. Age

Though this is not an important indicator for this study, we believe that, in itself, it gives an idea

of the different age groups involved in the businesses we are financing.

The data show that the people interviewed belong to different age categories. According to the

results obtained, the majority of the people interviewed belong to the following age categories:

• age 40-44: about 28%,

• age 45-49: about 22%,

• age 35-39: about 15 %,

• age 55-59: about 14 %,

while the remaining percentage belongs to other age categories.

Without going into a detailed analysis, which is unnecessary for the level of our study, we may say

that this age group represents the category of businessmen who have sufficient experience, a

relatively good knowledge of the market where they operate and, on this basis, they are able to be

efficient in decision making.


So, they are a category that considers loans as a supporting element in their business and are

responsible for their obligations and difficulties when receiving a loan.

2Age structure

Age 0-14: 24.1% (male 454,622/female 413,698)

Age 15-64; 66.6% (male 1,228,497/female 1,170,489)

Age 65 and over: 9.3% (male 154,352/female 178,865) (2007 est.)

The above structure gives us the age group structure in Albania. It is evident that the age group

of 15-64 years makes up about 67% of the population.

This phenomenon matches with our study, where the highest percentage belongs to the age

group from 35-60 (about 90%), which generally coincides with the age structure of fondiBesa

clients.

3. Business type or category

Regarding the business type, the trade sector is dominant and counts for 45% followed by the

sector of services with 28 % (Bar Restaurants + handicrafts).

The production and transport sectors respectively count for 7% and 2%, while construction and

mechanics count for 1% and 3%. The other activities count for about 14%.

2 Data according to INSTAT for the age group based on the last population registration .


Outstanding by sectors 2002 2003 2004 2005 2006 Quarter I: 2007

Trade & Services

(as % of outstanding) 87% 82% 85% 89% 89%

87%

As can be seen, the dominant number of businesses belongs to services and trade with about

73%, a figure that matches businesses that have received a loan from fondiBESA

4. Secondary activities

Regarding having a second activity, only 39 of the persons interviewed or 19% of them declared

that they have a second business.

Seen as a whole, it might be considered that this level of diversification of activities is satisfactory.

Regarding the lending activity, it can be considered as an opportunity for mitigating the risk.

Although it is a low level, it corresponds to the nature of businesses that we finance which, in

general, are small and micro businesses that may be considered family businesses.

In this respect, we may say that this level of diversification of activities coincides with the nature

of businesses that we finance.

5. Age of Businesses

Regarding this indicator, we make a division into two groups based on the starting year of the

business, as follows:

• Year 1990-2000: about 47% of businesses have started their activitiy

Year 2000-2006: about 53% of businesses have started their activity

In total, we may say that we have to deal with consolidated businesses as well as with start-up

businesses, which have just started their activity.

By analyzing the progress of the businesses and their consolidation in Albania, we may say that

the data of this indicator match Albanian business reality.


B. Cases of borrowing

6. Amount of loans received from fondiBESA.

Based on the data, it turns out that the majority of the persons interviewed, about 74% of them,

received a loan of an amount ranging from 50,000 - 500,000 ALL, and 26% of them received

500,000-2,500,000 ALL. The average loan amount received was 500,000 ALL.

7. Loan duration

The loan duration is up to 24 months.

The majority of the persons interviewed, about 53% of them, repaid their loans 5-12 months

after they received them.

About 47% of the persons interviewed repaid their loan 12-24 months after they received it.

It is clear that many loans are paid off well before the end of the loan term, including here large

loan amounts. This is observed more in those clients who have secondary activities.

8. Causes for not applying for a second (successive) loan from fondiBESA.

Obviously, the answer to this question gives several reasons why some clients did not apply for a

second (successive) loan from fondiBESA.


It is worth underlining and carefully analyzing the fact that 56% of respondents declared that they

did not need another loan and 15% of them declared that they will need a loan later.

The average need for another loan is 3 years.

In short, we may say that 71% of respondents (150 interviewed persons out of 212) belong to the

category, which might come back as borrowers from fondiBesa at a later time.

About 6% of those interviewed declared that they need a second loan, but that they would

choose another microcredit institution.

Another 6% of those interviewed declared that they would need loans in greater amounts than

those offered by fondiBesa. The amount required is an average of 5,075,000 ALL.

About 13% of those interviewed declared that they are unhappy with conditions of credit offered

by fondiBESA: 17 of them declared that they are not happy with the duration of the loan, 18

others are not happy with the interest rate and only one person is not happy with the duration of

the loan approval.

9. Applying for loans at other analogous institutions.

76% of those interviewed declared that they had not applied for a loan at any bank or analogous

institution. In general, this figure refers to the category of those customers who are satisfied with

the level of service offered by fondiBesa and consider fondiBesa as a potential source for future

loans.

In our opinion, this customer category is a potential group to be considered as future borrowers

from fondiBesa.

Only 24% of those interviewed had applied for loans from other microfinance institutions or

banks.

Tirana is a city where only 12 out of the 95 interviewed had applied to other analogous

institutions.

10. Possibility of getting a second loan from a bank, agency or another microcredit

institution

Out of 52 interviewees who stated that they had applied for loans from banks, agencies or other

microcredit institutions, 47 of them qualified to get a loan and only 5 of them didn’t get a loan.


The fact that the majority qualified to get a loan from other microcredit institutions or banks

makes evident the fact that, at present, a broad operational and competitive market exists. This

phenomenon is more evident in Shkoder, where about 50% of those interviewed (18

interviewees) had applied for credit at other institutions and all 18 of them received a loan.

The reason for not receiving the credit at other institutions was that the five interviewed did not

have sufficient assets to guarantee the loan.

11. Information about the other microcredit institutions currently operating

With regard to this question, we may say that 78% of respondents know the other institutions

operating in microcredit. Almost all respondents cite PSHM and ProCredit Bank and other

banks, which have recently started a microcredit service, like Raiffeisen Bank and National

Commercial Bank (BKT).

This fact should be analyzed in two perspectives:

First: The fact that interviewed customers said that they know other institutions operating in the

market has to do with an already consolidated market and with a clientele that carefully considers

all the terms and conditions of loans of all operators in the market.

At the same time, it means that fondiBesa should follow step by step the eventual changes of the

competititors, because the clientele is in contact with these possible changes. So the loyalty of our

clientele would remain as long as we're flexible to changes in microcredit market conditions.

Second: That the interviewed customers know to the greatest extent the competitors of

fondiBesa, but at the same time 71% (150/212) can be considered as potential customers who

will potentially return as customers of fondiBESA, is a fact that these clients consider fondiBesa

as a competitive opportunity that provides satisfactory services and offers its product "at least at

market conditions" - ie a product, which is at the level of its competitors or has a remarkable

advantage for its customers.


12. Consideration for lending institutions (banks or other non-banking institutions).

Although the data obtained from responses to this question are not directly related to the

purpose of our study, they give a general idea of the level and quality of service of these

institutions.

Thus only 38% of respondents declare that these institutions are very effective and offer very

good services and 31% of them declare that they provide services of an average quality.

So, in total, about 69% of lending institutions provide good services (optimal).

SUGGESTIONS & RECOMMENDATIONS

In general, our opinion is that the conclusions were obtained, because they rely on a

representative "sample". We emphasise this fact because we think that a "representative sample"

is very important to produce valid conclusions, when we consider the limited number of the

respondents, only 212.

We consider that the main characteristics of the respondents are within the range of fondiBESA

characteristics.

So, out of all the interviewed persons, about 73% of them were male and 27% female, which is

within the average of fondiBESA (male/female is respectively 80%/20%).

Regarding another important characteristic, which is the division of the credited business sector,

the dominant weight with 45% is the trade sector, followed by services with 28% (Bar

Restaurants + handicrafts). This data is approximately level with that of fondiBESA, where 88-

90% of businesses belong to the trade + services sector.

Finally, another characteristic, that would be a complete argument on how representative the

selected "sample" is, is the average loan received by the group of interviewed persons, which is

about 500,000 ALL. So, based on this indicator and the other above-mentioned indicators we are

convinced that the selected "sample" is fully representative of the whole clientele of fondiBESA.

As a conclusion: all the data, information, features derived from analysis of the data from the

questionaries can be considered entirely representative. This is why the conclusions and

recommendations resulting from these data are completely valid.


All respondents belonged to the category of clients who have been customers of fondiBESA but,

at present, they are not clients of fondiBESA and their analysis is extended in several directions.

First of all, the analysis aims to distinguish and clarify the reason why these customers have not

applied for successive loans (second loans, third, etc.).

It is noted that about 56% of the interviewed persons do not need a second loan, while 13% need

a second loan at a later time.

About 71% of interviewed persons are those who think that will return for a second loan at a

time later, while 6% are in need of a loan, but their need is at a level beyond the maximum loan

amount offered by fondiBESA.

A fact, which is worthy of being analyzed, is that 13% of respondents are in general unhappy

with the terms of loans offered by fondiBESA., 8% are unhappy with the loan duration, 8% with

the interest rate, and only one client is unhappy with the terms of loan approval.

Given the above data, we can make the following recommendations:

First: The theoretical assessment according to the chosen formula, where RR in 2006 was 88%,

is a very positive indicator considering that the customer desertion rate DR of 16% includes over

70% of customers who potentially could return as customers of fondiBESA (about 11% within

the 16% belong to the category that might return as borrowers).

This category belongs to customers who have not applied for a second loan because they do not

need a loan for the moment or will receive it at a later time.

Second: Most of the respondents belong to the category of customers that have a relatively

gradual progress in their business, so they think of satisfying their need for credit from

fondiBESA. Thus 76% of respondents said that they did not apply for credit from any other

bank or institution.

This indicator, seen in correlation with the indicator that 78% of respondents know other

institutions operating in microcredits, such as PSHM, ProCredit Bank and other banking

institutions which have recently started a microcredit service such as Raiffeisen Bank and

National Commercial Bank (BKT), is an indirect indicator that they are satisfied with the level of

service and the microcredit product provided by fondiBESA.

So, as a conclusion we may say that they are satisfied with the level of service and terms of our

loans (70% correlates with 64%).


In our opinion, an analysis of the 24% of respondents, who have applied for loans in other

institutions, shows that more than 13% of respondents are entirely unhappy with the terms of the

credit offered by fondiBESA. This makes us think that we should perform an in-depth analysis of

this fact.

Valid recommendations for management could be:

Application of preferential interest rates will help the quality improvement of the analyzed

indicator and, at the same time, will support the consolidation of the current clientele.

We would recommend the application of a preferential interest rate of 1.9%; 1.85% for clients

who reapply for the third or fourth loan.

The fact that 78% of respondents had knowledge of analogous institutions (mainly ProCredit,

PSHM, BKT, Raiffeisen) means that the promotion of this activity is high. Seen from this point

of view, a valid recommendation for management would be the organization of a "more

effective" publicity campaign that means a more complete analysis of this element.

The fact that all these institutions have massive promotional campaigns (in all the mass-media)

and that a detailed analysis of all their micro and small loan products shows that their interst rates

are at the level of 2% per month ("flat "or" declining "), while for SME loans they apply interest

rates from 1.5-1.8%, makes us seriously take this fact into consideration. Currently, 38% of

fondiBESA’s outstanding loans are loans for an amount over 1,400,000 ALL.

Regarding the promotional campaigns in the mass-media, we consider them as a very important

element, based on the following arguments:

The market segment of loans over 1,400,000 ALL is becoming "very preferable” not only for

banks, but even for the other microfinance institutions. In the situation where 38% of

fondiBESA’s outstanding loans belong to this segment, an "aggressive" promotional campaign,

mainly through informational promotion on national/local TV would serve to increase the

number of clients. So, in a way, it would serve to diversify the risk of desertion of clients who

apply for amounts above 1.4 million ALL.

Promotion in mass-media (through one or several alternative "spots") would serve to increase

consumer loan lending, a product already launched as a separate product from fondiBESA.


A valid suggestion, in the framework of minimization of fondiBESA’s customer desertion, would

be the application of a "flat" repayment schedule for business loans. We believe that in a situation

where all the other operators such as ProCredit; Raiffeisen; BKT; PSHM etc. are operating with

this type of repayment schedule, when the technical possibilities of fondiBESA allow the

application of such a schedule, it would be the right decision to allow clients to repay in such a

manner (namely "flat"), which could however affect modestly the minimization of customer

desertion.

It is observed from the information obtained from the survey that 30 respondents (or about

14%) repaid their loans after 5-12 months from its receipt.

Although this cannot be called a phenomenon, a valid recommendation would be to find ways to

create "barriers to exit."

Although the management staff of fondiBESA considers the "declining" method of repayment

and the non-application of fees in case of advance repayments as competitive advantages, we

would recommend the applications of “fees” in the case where clients repay before 70% of the

loan maturity.

Although the application "fee" is a coercive instrument for loans up to three years, regarding the

four or five-year loans the application “fee" remains 3%, which does not slow down or limit the

advance repayment of loans, i.e. customer desertion.

Another valid recommendation would be regaining the customers who are now clients of

other institutions.

Although these clients have left and are currently clients of other institutions, keeping contacts

with them through SMS, phone, etc. would be a simple and effective instrument.

Another simple instrument with a psychological effect on customers would be the pre-approval

for repeated loans 2-3 months before the full repayment of the loan: analyze the client's business

and require a formal pre-approval by the credit committee to make an offer to these clients.


DEMAND SIDE ANALYSIS OF MICRO-LENDING MARKETS

IN GERMANY3

Prof. Dr. Alexander Kritikos

Head, Department of Innovation, Manufacturing, Service

German Institute for Economic Research

Mohrenstraße 58, 10117 Berlin, Germany

Tel: +49-30-89789-157, Fax: +49-30-89789-104

Email: [email protected], http://www.diw.de

Christoph Kneiding

Market Intelligence Officer, CGAP / The World Bank

900 19th St, Washington, DC 20006, USA and GfA, Berlin, Germany

Claas Christian Germelmann

Assistant Professor, Institute for Consumer and Behavioural Research, Saarland University

Postfach 15 11 50, 66041 Saarbruecken, Germany

3 Kneiding gratefully acknowledges the financial support of the EQUAL-framework ‘EXZEPT’ which is financed by the European Social Funds (ESF) and the German Ministry of Labour and Social Affairs. Kritikos acknowledges the financial support by the IAB - Institute for Labor Market Research (project no. 1-910), Nuremberg.


ABSTRACT

In industrialized countries with highly developed banking systems, the existence and size of an

uncovered demand for micro-lending services are controversially discussed. However, to date,

only little is known about customer preferences for micro-lending products. By using a unique

German data set consisting of more than 300 persons being surveyed, our paper aims to close

this research gap. We analyze the funding needs of micro businesses; we describe the intended

use of funds acquired by the business owners, and identify the financial sources typically used by

entrepreneurs to cover their financial needs.

By focusing on business owners who financed their first three years’ operations through loans,

we reveal which businesses prefer microloans, and identify the product features that serve best

their needs. We do this by a direct approach where borrowers are asked about their preferences

with respect to a microloan, and an indirect preference analysis where preferences of borrowers

who are satisfied with the traditional bank approach are compared with the preferences of

borrowers who are interested into microloans. Based on this survey, we apply different kinds of

quantitative analysis.

The key results can be put together as follows: Among the entrepreneurs interviewed, 15%

reported revolving funding needs and an interest in microloans. We find that potential recipients

of microloan products are retail business owners, foreign small business owners, and persons

who had previously received private loans. Furthermore, financial products should feature rapid

access to short-term loans combined with personal contacts to loan officers who are able to

thoroughly understand the client’s business concept. 65% of those surveyed financed their first

three years of operations without applying for any loan at all. It is thoroughly possible that within

this group a latent demand exists which could be unleashed by designing novel micro-lending

products. This means for incumbent financial institutions as well as for lenders entering the

market that they are well advised to use a focused marketing strategy in targeting these specific

groups.

As the study is unique in its design we provide an assessment of the micro-lending market in

Germany. On the one side, our research results allow to derive the main aspects of a successful

MFI marketing strategy. On the other side, our research approach may serve as a role model for

similar research approaches in other markets in Western European Countries.

Key Words: Microlending, Small Business Finance, Market Research, Demand Side Analysis

JEL-classification: G21, D12, M31


1. Introduction

Self-employment has become a buzzword in European economic policy. In Germany, for

instance, the number of entrepreneurs has risen from 3.0 to 4.2 million in the last 15 years (see

Piorkowsky and Fleißig, 2008). It is further estimated that every year up to 500,000 people start

their own business, most of them as micro entrepreneurs with no further employees and small

amounts of capital, usually below €25,000. Access to sufficient capital to start operations or

further develop their activities is a difficulty faced by many of these businesses not only in

Germany but also in other European countries (Eurobarometer, 2005).

To explain why businesses face such problems when accessing finance, the asymmetric

information approach (see e.g. Hillier and Ibrahimo, 1993) identifies two main reasons on the

supply side: (1) micro businesses usually cannot provide collateral. As a result, they are unable to

signal their creditworthiness, and banks are unable to assess the credit risk. (2) Owners of these

businesses tend to take out relatively small loan amounts. The fixed costs of granting such loans

tend to eat up more than the profits from interest payments. Therefore, institutional lenders

using standard credit technologies consider loans to this group as unprofitable.

Evidence from developing, emerging and transition economies, however, has shown that lending

in this market segment can be a profitable business if appropriate technologies - known as

microlending - are used (Armendáriz de Aghion and Morduch, 2005). Microloans have a

technical and a methodological component. From a technical point of view, they are sized at the

lowest possible level. In western European countries, any loan below 25,000 Euros is considered

as microloan4. From a methodological point of view, as Armendariz de Aghion and Morduch

[2000] put it, “documentary evidence tends to be de-emphasized relative to standard banking

practices and local character assessment gains prominence.”

Recently, attempts have been made to use these technologies in industrialized countries. First

successes of Microlending approaches in Western Europe were reported by a French and a

British microfinance institution (MFI), namely ADIE founded in 1988, and Street UK founded in

1999 (see EMN, 2006; CDFA, 2006). However, there are many other comparable initiatives,

4 The size of a microloan depends on country-specific conditions. For instance in developing

countries a typical microloan is below $500, while in transition economies, it may take a size of up to

$10,000.


mostly financed with public funds, which never got off the ground. Their failure, though, cannot

be explained by low repayment rates only. Instead, these initiatives created products that took in

particular care of the supply side problems in this loan segment. As a consequence, entrepreneurs

simply failed to apply for funding. A second short-coming of these approaches was that the

restrictions imposed for the use of public funds made it nearly impossible for the MFIs to

develop products focused on their target markets.

Such experiences give reason to reconsider if MFIs should concentrate only on the supply side by

designing microloans which mitigate problems of information asymmetries, or also on the

demand side through products responding to customers’ preferences. Woller (2002) advocates a

radical shift in MFIs’ policies, moving away from a ‘product-driven’ microfinance culture and

giving priority to customer needs. However, to date, only little is known about customer

preferences. By using a unique German data set, our paper aims to close this research gap. We

analyze the funding needs of micro businesses; we describe the intended use of funds acquired by

the business owners, and identify the financial sources typically used by entrepreneurs to cover

their financial needs. By focusing on business owners who financed their first three years’

operations through loans, we reveal which businesses prefer microloans, and identify the product

features that serve best their needs. Thus, we provide a first assessment of the microlending

market in Germany which can also serve as a role model for similar markets in Western

European Countries.

The paper is organized as follows. Section 2 reviews previous theoretical and empirical research

results and outlines our research agenda. Sections 3 and 4 describe the data and present the

empirical analysis. In Section 5 we provide a conclusion showing that microfinance in Germany

(and other western European countries) will only be (more) successful if the peculiarities of both,

the supply and the demand side of a Microlending market will be adequately addressed.

2. Previous Research

2.1 Microlending Theory

In his review paper, Morduch (1999) demonstrate why micro businesses are excluded from access

to credit markets and why microlending is apt to solve this problem. While finance theory

generally posits that all firms have equal access to financial markets and that all share similar


competitive positions (van Auken and Neeley, 1996), micro businesses - when compared to larger

businesses - face more difficulties or are even excluded from access to credit markets.

A considerable body of theoretical literature deals with the idea that asymmetric information is

the main reason of these specific difficulties (Jaffee and Russel, 1976; Besanko and Thakor,

1987a, 1987b). This idea rests on two assumptions about the lack of financial capital observed

among micro-businesses: (1) Lenders cannot distinguish between high and low-risk borrowers,

and potential borrowers are short of standard collateral which is why they cannot easily signal

their own risk-taking behavior leading from the lender’s point of view to the typical problems of

adverse selection and moral hazard (cf. e.g. Morduch, 1999). (2) Given that persons running

micro-businesses mostly ask for very small loan sizes, it is not feasible in the traditional banking

system to substitute the missing signal by additional screening and monitoring efforts. As a

consequence, credit is rationed where the amount lenders are willing to offer is limited, or where

no lender is willing to make any loans to this kind of borrowers (Stiglitz and Weiss, 1981).

These problems can be addressed by implementing microlending technologies into the lending

process: Financial statement analysis combined with collateral in the form of inventory and

accounts receivable (being the typical banking practice in small business finance, for more details

see Berger and Udell, 2003) is substituted by an assessment of various factors: the applicant’s i)

personality traits, ii) entrepreneurial abilities and iii) entrepreneurial knowledge. The information

gathered is then evaluated based on a credit scoring methodology.5

The asymmetric information approach also has implications for the demand side of loan markets.

According to the pecking order theory (Myers, 1984), businesses adhere to a hierarchy of

financing sources where cheapest funds are used first. If these are exhausted, business owners

will draw on more expensive funds. As these costs are also determined by the information

problems of each capital source, Myers and Majluf (1984) expect that internal funds - own capital

and cash flow - are the cheapest financial source for business owners, followed by funds and

loans provided from family members and friends. If further funds from external sources are

needed, loans from banks are preferred to external private equity (such as venture capital) for

several reasons. For example, the loss of control over the own firm is lower under a loan; adverse

5 The most prominent method of microfinance in developing countries is the so called joint-liability contract which, however, finds almost no application in Western Europe. For more information about the theoretical construct of joint liability contracts, cf. e.g. Ghatak and Guinnane (1999), and about its empirical analysis, cf. e.g. Kritikos and Vigenina (2005).


selection and moral hazard deliver further arguments for a preference of loans over equity, at

least when firm owners have positive prospects of their business and do not intend to shift to

riskier strategies once external funds are invested (see Myers, 1984, or Scherr et al., 1993).

Concluding, the asymmetric information approach is apt to explain behavior of both sides of

microfinance markets, according to which banks face adverse selection and moral hazard

problems, while business owners are expected to prefer internal financing when available and

debt over equity when external financing is required.

2.2 Empirical Evidence on Financial Sources of Micro Businesses

Having shown that microlending is more than just lending very small amounts of money to

business owners, this subsection presents an empirical overview on self-employment, the

financial means which are typically used by self-employed and on financing constraints in

Germany. Technically speaking, microloans are loans with a short term maturity (a maximum of

2-3 years) and loan sizes below 25,000 Euros. Businesses considered eligible for such a loan type

are micro-businesses where the business owner is a solo-entrepreneur or employs not more than

5 persons in the business and has a turnover below €1 million per year.6 One may expect,

however, that persons who are interested into these kinds of loans are typically business owners

with a yearly turnover of less than €100,000.

Against this background, the German MSME sector comprises of 4.2 million businesses in 2007.

Around 90% of them have a yearly turnover of less than €1m, 70% of them of less than

€100,000, and 56% are run by solo-entrepreneurs (see Piorkowsky and Fleißig, 2008 and Wallau,

2006). In recent years, the average year-to-year survival rate of all businesses has been 92.5%

(Constant and Zimmermann, 2005). The number of start-ups was around 500,000 over the last

years, with a relatively strong drop to 425,000 in 2007 (see IfM Bonn, 2008). It is estimated that

every second firm was created out of unemployment (Caliendo and Kritikos, 2007).

According to the MSME-panel of the German state-owned bank KfW, 75% of all MSME did

not use any external financing (KfW 2007). Very similar numbers were reported by Kohn and

Spengler (2008) and in a much larger and representative study by Caliendo and Kritikos (2007)

where 3,000 persons who started a business in 2003 in Germany were surveyed in 2006. This

6 It is important to note that there is no common definition. The above definition resembles to the German Institute for Small Business Research (IfM Bonn). In the EU a micro-business is defined as a business with not more than 10 persons and a turnover of less than 2 Million Euros. For an overview of definitions and data, see also the European Microfinance Network (EMN), 2006.


survey asked in addition for the sums of capital employed during the first three years. 53%

reported to have used less than €5,000, 14% between €5,000 and €10,000, 28% between €10,000

and €50,000, and 5% more than €50,000.

Further information on the business owners who made use of external financing, is reported in

the KfW–panel (KfW 2007). They found that in almost all cases those 25% who needed external

funds preferred loans and overdrafts. Venture capital plays a negligible role. In every second case,

loan volumes were below €25,000 meaning that around 13% of all existing MSMEs in Germany

operate with loan sizes below €25,000.7 However, these data give no clue whether business

owners faced any financing constraints.

Little is known about the alternatives of borrowing capital below €25,000. Inside and outside the

formal banking system micro business owners have some funding alternatives that are well

documented. KfW offers several loan products aimed at small and micro-businesses in their start-

up phase. Maximum maturities vary between five and ten years, and maximum loan amounts

range between €10,000 and €50,000. According to Evers and Lahn (2007), about 1,500 loans up

to €25,000 have been extended by KfW in 2006. These are microloans only in terms of their size,

though; the methods used resemble those used for small business loans and not those presented

in section 2.1.

Outside the formal banking system there are about 30 different regional or local MFIs, of which

about 10 jointed the network of the German Microfinance Institute (DMI) which was found in

2004 and started operations in 2005 (see Kreuz, 2006). All of them apply to a certain extent

microlending methods as described above. Another 2,000 loans were actually approved by these

30 institutions in 2006 (Evers and Lahn, 2007).8 This indicates that there is a substantial gap

between businesses operating with loans below €25,000 (namely 13% of all entrepreneurs or

around 500,000 businesses if the methods of extrapolation employed in the KfW panel are

correct) and those businesses which were financed with microloans.

Thus, there must be other sources of loans which are used by micro business owners in this

sector. Berger and Udell (1998) emphasize the importance of private loans for this segment.

7 Using the US data, Bitler, Robb and Wolken (2001) revealed similar evidence that commercial banks are the dominant source of financial services of these kinds of businesses while Harhoff and Körting (1998) found out that lending is typically heavily concentrated on one or two financing institutions in the MSME segment. 8 To compare these numbers with the two most prominent MFIs in western Europe, ADIE in France financed in 2006 about 7,500 borrowers, while Street UK made about 2,000 loans.


However, the above mentioned data give no information on this source. Rather to the contrary,

the data of the KfW panel count private loans as internal funds, which is why they disappear

among those 75% of business owners who declared not to have borrowed money from banks.

There are two more options: either banks are willing to offer also business loans below 25,000

Euros, or business loans are replaced by consumer loans (for first evidence on the latter

suggestion, cf. Kneiding and Kritikos, 2007). Thus, relatively little is known about the financing

sources microbusinesses use.

Last but not least we have to focus on the question whether micro businesses are facing financial

constraints. Such constraints may have two aspects, namely higher efforts for capital acquisition

(compared to larger companies) and complete exclusion from access to loans. There are a several

studies analyzing whether credit rationing is an economically significant phenomenon. For

instance, in a Eurobarometer (2005) survey investigating MSME finance within the European

Union, it was found that German owners of micro businesses seem to face greater hurdles in

accessing loans compared to their European counterparts. When evaluating the quality of bank

services in terms of consultancy, sector-specific know-how, general knowledge and expertise, and

the suitability of the loan offers to customer needs, German banks fared below average. Three

earlier studies (Egeln et al., 1997; Winker, 1999; and Audretsch and Elstons, 2002) found that

smaller firms face more problems while acquiring capital than larger firms.9

2.3 Research Agenda

The following major questions will be addressed in this article: To what extent are there

institutions financing businesses with loans below €25,000? Is there further empirical evidence on

financing constraints in Germany and is there demand for microloans beyond the observed

financing volume? What are the product preferences of micro businesses and which variables are

able to describe target groups for microloans?

To analyze these questions, we collected demand side data containing information (a) on the

financing patterns of micro-business owners (also in comparison to small businesses), (b) on their

actual financing sources and (c) on their attitudes towards typical microlending products.

As we examine the sources of capital available to these businesses, we are able to give further

evidence to what extent micro-businesses

9 As was highlighted by Block et al. (2008) some of these studies may suffer from a survivor bias as only successful firms were in the data sets while failed firms were underrepresented.


- have investments below €25,000,

- face problems when trying to access loan volumes below €25,000,

- are excluded from access to finance.

Based on these results, we compare in a second step the respondents with preferences for

microloans with those respondents who were not interested in microloans, taking into account

various characteristics such as previous experiences with banks, product preferences, and funding

patterns (i.e., the amounts of capital needed each year). This enables us to identify the typical

characteristics of potential microfinance clients and to describe the product features appropriate

to increase the demand for microloans.

Our approach has several advantages. First, our data set contains also information on failed

businesses so that we are able to mitigate survivor bias. Second, we do not only observe the static

results of financial decisions but are also able to make a comparative static analysis revealing the

efforts applicants faced until a loan contract was realized, thus giving further information on

financing problems. Third, among all observed business owners we identify those who would be

interested in microloans enabling us to distinguish them from other business owners.

3. Sample description

3.1 Overview of descriptive statistics

Our data is derived from a survey that provides information on the sources of finance of

different business owners during their first three years of operations. The survey was conducted

between mid-October and December 2005 in the form of 213 telephone interviews with people

who had become entrepreneurs during the past five years. Survey participants were randomly

selected from various client lists provided by German start-up centers in the provinces of Hesse

and Bavaria. The lists were comprised of clients who had taken part in coaching and seminars

held between 2000 and 2003 and who were then preparing to launch their own business. Thus,

comparing to most previous studies this data set has one advantage and one disadvantage. On the

one side, it does not face a survivor bias as it contains successful as well as failed business

owners. On the other side, we cannot exclude that there are problems of inverse causality and of

selectivity as the persons we surveyed participated in coaching and seminars.

The interviews were held using a standardized questionnaire which we had developed on the

basis of 34 non-standardized personal interviews with micro-business owners, as well as through

a focus group comprising seven participants. The majority of the questions were closed-ended,


which enabled respondents to answer unambiguously. When necessary, the interviewer gave

additional explanations.

The questionnaire was designed to collect a wide range of information and was divided into two

main parts. The first contained questions pertaining to funding patterns and sources of capital

during the first three years of business operations. The second part dealt with possible funding

problems encountered and interest of respondents in microlending schemes. We interviewed one

person per firm (the owner-entrepreneur), and in the case of team-run companies, only the main

person in charge. An important advantage of our data set is that we were able to avoid

hypothetical answers. At the time of the interview, all respondents were able to provide a

retrospective view of funding issues since all of them had been either active in the market for

three to five years or failed during this time span.

- insert Table 1 about here- (see appendix)

Within the whole sample, 70% of respondents started without any external funds10, 19% received

a loan from a bank, and 11% from friends or family. Another 11% faced rejection from banks,

5% of the complete sample expressed their need for outside finance but neither banks nor

friends and family provided them with a loan (see Table 1). As shown in section 2.2, other studies

reported similar shares of micro entrepreneurs who received loans or launched their business

without any need to get outside finance.11 Thus, we conclude that with respect to the basic

financial variables (in terms of the shares of outside finance) the average outcomes of our sample

are similar to the average outcomes of larger representative samples which were observed in the

same time period.

Beyond these basic results our data allow a deeper understanding of financing behavior of

MSME businesses by making use of a comparative static analysis. We reveal the paths of capital

acquisition which the borrowers had to pass once they decided to acquire external finance. Our

data show that 64% of the persons stated that they started their business without any external

finance (not even from friends and family) and that they neither needed any outside finance nor

intended at any time to seek for outside finance.

10 The two most apparent reasons are i) low funding needs for the majority of start-ups, and ii) government support that strengthened the equity base. 11 In a similar study, Fraser (2005) found that also in the UK, almost two out of three businesses had used personal savings as the principal source of finance to start the business, and one-third had received funds through a bank loan or a private loan. In this study similar to our approach, private loans from friends were counted as loans.


- insert Figure 1 about here - (see appendix)

In their first three years of operations, the other 36% of respondents were in need of outside

finance. 84% of this group applied for a bank loan,12 and almost two-thirds were successful, i.e.,

they were able to cover their funding needs through an installment loan or an overdraft facility.13

We also investigated whether those borrowers who finally succeeded in getting a loan from a

bank faced temporal financing constraints in the sense that they had to apply more than once for

a loan. Indeed we find that almost two thirds of respondents went to more than one bank to

receive a loan, which resulted in elevated application efforts.

Loan sizes ranged between €500 and €300,000. 75% of the loans were larger than €10,000; on the

hand, 75% of the loans were also smaller than €25,000. Among those who received bank loans,

less than 5% of the subsample still required additional funds showing that when banks provide

financial assistance to young businesses, the loans they provide are of sufficient size.14

The right sub-sample on the intermediate level of Figure 1 provides further information on those

16% of borrowers who needed outside finance but did not apply for a bank loan. They had

access to other sources (loans from friends and family or from an existing overdraft). These

persons had, thus, need for external finance but decided not to base the financing of their

business on a new bank loan.

The subsample on the bottom right is comprised of business owners who did apply for a loan

maybe more than once but were rejected. The reasons for rejection were unknown since banks

usually do not disclose this information to applicants.15 36% of all applicants were rejected by

banks. About half of the rejected loan applicants reported a funding gap or adjusted their

investment volumes, while the other half got access to private loans.

12 Over 90% of business owners who had applied for a loan had a formal meeting with a bank employee where they explained their business concept. Of those who visited a bank, 72% inquired about a loan, 12% about an overdraft facility, and 16% about both.

13 We cannot exclude that this rate of loan approval might be slightly influenced by a positive sample selection bias as the interviewed business owners had received training and coaching during the start-up phase of their business. However, it should be emphasized that Kohn and Spengler (2008) also report of a very similar acceptance rate of loan applications.

14 This coincides with the findings of Lamberson and Johnson (1992) who interviewed 140 firms on their financing experiences, of whom only 6% reported dissatisfaction with the amount of credit available.

15 Evidence from interviews with loan officers reveals that the main reasons for rejection are (i) low loan volumes, (ii) poor business concepts, (iii) redlining of certain industries (e.g. retail), and (iv) a low degree of borrower creditworthiness (IAB et al., 2005).


Interestingly, survival rates differed between those who needed no outside finance or received a

loan from a bank (being put together in one group and those who needed outside finance but

started with a private loan or no loan. Without being able to analyze any causality, in the first

group (businesses which were started without outside finance or with a bank loan) the survival

rate was significantly lower (on the 1% level when using the Fisher test) when compared to those

who needed outside finance but started without a bank loan.

Observation 1: Our comparative static analysis revealed that 36% of all business owners had a

demand for outside finance. Of them 21% received a loan from a bank after the first application,

another 33% also received bank loans but only after having applied more than once for a bank

loan. 16% of those who needed outside finance did not apply for a bank loan and 30% applied

for a bank loan but were not able to sign a loan contract.

As earlier studies found that raising capital poses a problem to business owners (Egeln et al.,

1997, Winker, 1999, and Audretsch and Elstons, 2002), we can confirm that such financing

problems exist and we were able to give new insights by making use of a comparative static

analysis in what way financing problems arise and how they are handled by the business owners.

3.2 Comparison of borrowers vs. non-borrowers

For the subsequent analysis, we split the sample into two groups: those 36% of the persons in the

sample who required (not received) outside finance will be called ‘borrowers’. Those persons who

never asked for a loan (not even from friends and family) because they had sufficient equity

capital to finance their business (64% of the sample) will be called ‘non-borrowers’.

This distinction is made for the following reasons: it seems appropriate to observe those persons

more intensely who were in need of outside finance in the past, as they represent the potential

customer group for microloans. (Among this group are also persons who applied for loans and

were actively excluded.) As it would have made less sense to ask persons with no need for outside

finance about their inclination towards a microfinance product - their statements would be

hypothetical in this respect – we explicitly decided to ask non-borrowers for the main reason why

they refrained from borrowing.16

16 We were encouraged do so as those persons from the pre-tests and from the focus group who had no need for outside finance clarified in a strict way that they would not be interested in a micro-loan which is why they were not able to give meaningful answers to specific questions about features of such loans.


Among the non-borrowers roughly two-thirds had no need for larger amounts of capital during

the first three years of operations, or had enough funds (either from their own savings or from

public support instruments such as the bridging allowance, for more details on the latter, cf.

Caliendo and Kritikos, 2007). About one-third of all non-borrowers said that they were afraid of

indebtedness which stopped them from applying for a loan. They adjusted the size of their

business to their own existing funds. A certain (but unknown) share of non-borrowers might be

excluded from access to bank loans, even though it is not possible to verify this assumption.

Table 2 compares characteristics of borrowers and non-borrowers. The variables are classified

according to the attributes describing the business owner (personal characteristics), those

describing the business (business characteristics), and the funding needs of the firm for each of

the first three years (financial characteristics).

- insert Table 2 about here - (see appendix)

Thirty-seven percent of the borrowers had started retail or crafts businesses, compared to a mere

11% of non-borrowers. A Fisher test reveals that retail (p=.049) and crafts enterprises (p=.048)

exhibit significantly greater financial needs during the first three years than do other lines of

business. This is plausible given that most of the businesses require higher investments for

purchasing physical stock or machines.

Funding needs of borrowers and non-borrowers during their start-up period average out at about

€15,000.17 Table 3 gives additional information beyond the overall average, namely the funding

needs separated for borrowers and non-borrowers for each of the three years in consideration. A

clear distinction can be observed (a) between year one and the two following years, as well as (b)

between borrowers and non-borrowers. While more than 80% of the non-borrowers needed less

than €10,000 in the first year, this was the case for only 47% of the borrowers: more than a

quarter of these businesses required more than €25,000. The levels of funding needs in the two

subsequent years differ significantly from the first, while years two and three both exhibit similar

patterns. Obviously, in both groups, there is a high percentage of businesses that exhibit no

funding needs at all after year one. (c) Moreover, we are able to reveal two kinds of investment

patterns: one group of businesses requiring one-time funding, and a second group with recurring

funding needs.


17 The study by Caliendo and Kritikos (2007) produced an average amount similar to the present data.


Respondents were asked to specify the main intended use of funds in each of the three years. A

large percentage of businesses used the funds to cover start-up expenses such as IT

infrastructure, office equipment, and materials for their first fiscal year. What is crucial to know

for the design of microfinance products is that liquidity finance played an important role for the

borrower group in the two following years: more than 50% reported liquidity gaps that had to be

closed, for instance, the entrepreneur’s own costs of living and pre-financing customer orders.

Cases of ‘emergency finance’, such as back duties falling due, were also mentioned.

4. Empirical analysis

In this section, we will concentrate on persons with need for ‘outside finance’. This is an umbrella

term for all financial resources that do not constitute equity capital, for instance, bank loans and

private loans obtained through friends or relatives. In this respect, we employ a broad definition

of outside finance, as our sample contains also persons who were in need of loans but were

rejected from banks or who used loans from their personal environment.

4.1 Direct demand analysis

A straightforward way of understanding the demand for a certain product is asking potential

customers directly about their preferences. Two methods were employed throughout the course

of the interview. In the first version, respondents were asked to name the three most important

product criteria a microloan should have; the second approach required them to rank given

criteria on a scale from 1 to 5. However, the information provided was inconsistent: while the

unguided questions prompted answers mostly related to interest rates,18 then to maturity, and

flexibility of the loan product, the ranking exercise showed a strong preference for ‘soft’ criteria

like customer liaison and support. This reveals an important weakness of direct demand analysis:

answers are strongly influenced by the survey format, and thereby lead to inconclusive results.

This problem can be mitigated by presenting respondents a generic microloan and thereby

indirectly eliciting their preferences.

18 It is certainly not surprising that many persons being asked about product features will demand low prices, in this case interest rates, in the first place. However, such information does not allow discriminating between persons who are interested in a microloan and those who are not.


4.2 Indirect demand analysis: Tests and Results

We presented the following typical properties of a microloan to all persons who needed external

finance. The features are based on actual microloans offered in countries such as the UK or

France.19

• the loan value varies between €1,000 and €10,000;

• the term of each loan ranges between one and two years;

• there is no amortization-free period;

• the repayment scheme is fully flexible (comparable to an overdraft facility);

• applicants are informed of the credit decision within five days;

• interest rates amount to approximately 20% per annum;

• the loan officer acts as a partner to the client and problems are solved cooperatively;

• different kinds of collateral can be used.

It was mentioned explicitly in the interview that loans with these characteristics are only offered

by MFIs in these countries. Respondents were then asked whether they would ‘buy’ such a loan.

If respondents rejected it, they were asked why. If they said that interest rates were the main

reason, we presented a showcase calculation giving interest payments in absolute terms (a strategy

commonly used by MFIs). Respondents were then asked if this display would change their minds.

A dichotomous variable ‘target group’ was defined to take the value 1 if respondents were

interested in the product and 0 if they were either not interested or not sure. 31 respondents

(41% of the borrower group) revealed their interest in a microloan.

In order to explore what kind of experiences all persons of the borrower group had during their

bank meetings and which product features are important to these persons, all respondents (i.e.

those who were interested in microfinance products and those who were not) were asked to rate

various product features and the service quality they experienced during their most recent bank

meeting on a Likert-type scale varying from 1 (strongly disagree) to 5 (strongly agree). More

specifically, we then compared the answers on these questions between the two groups. To do

so, we employ a Mann-Whitney U test to analyze group-specific differences.

19 Specific product features are discussed, e.g., in Copisarow (2000), Vigenina and Kritikos (2004), or EMN (2006) among others.


4.2.1 The Impact of Previous Experiences with Traditional Banks

We start with the experiences persons reported from their bank meeting, and we compare

persons who showed interest in micro-loans (abbreviated as target group members ‘T’) with

those who did not (‘NT’). Lower mean ranks for those who were interested in microloans

indicate that the sum of the ranks must be smaller than the sum of the ranks for those who were

not. Table 4 illustrates the results. The mean ranks indicate that micro-business owners who were

interested in microloans rate the bank’s customer service lower than the NT-group. Moreover,

for three items we observe that all differences in the mean ranks are weakly significant.


In this context, however, it is important to note that among those persons interested in

microloans there is a higher share that was rejected from a bank (namely around 50%), while

rejection rates among persons who were not interested in microloans were only little more than

20%. Therefore, the data may contain a success bias as those who received a bank loan may

evaluate their meetings with the bank more positively. This rationale is psychological: a favorable

meeting outcome leads to a positive evaluation. On the other hand, the bad experience of not

receiving a loan may result in a negative evaluation due to the unsatisfactory outcome.

Therefore, we repeated the comparison of persons who were interested in a microloan with the

NT-group, but concentrated in both groups on those applicants who received a loan. Thereby, we

are able to control for the above mentioned success bias. Again, we apply a Mann-Whitney U

test. Table 5 presents the results.


Interestingly, the findings from our previous results are unambiguously confirmed. Business

owners who showed an interest in microloan products had significantly worse experiences during

their bank meetings than the NT-group, even if both groups received a bank loan. The target

group’s evaluation of the meetings was significantly less positive, and they indicated that they had

been taken less seriously as fully fledged clients. Furthermore, their responses differed greatly

regarding whether bank employees understood their business concepts and provided them with

sufficient information on the terms and conditions of the possible loan products.

Observation 2: Prior negative experiences with banks are positively correlated with target group

membership, even if the business owner received a loan from a bank.


4.2.2 Crucial product features

With respect to the second set of questions, we aimed to find out which product features are

important to potential microloan clients.


The rank-sum test reveals two significant differences between the two sub-samples (see Table 6).

First, business owners who showed an interest in microloans stated that they operate in segments

that demand fast access to loans. Second, they were willing to pay higher interest rates for faster

access to loans. Interestingly, product features (which were named as important when directly

asked) like flexible repayment schemes, amortization-free periods, and individual support from a

loan officer are clearly not important enough to allow distinctions to be drawn between the two

groups.

Finally, we analyzed the correlations between bank assessments and product features. Our results

show that applicants who gave an overall bad rating of bank meetings were actually willing to pay

higher interest rates for loans. The same holds for those who stated that they had not been

treated as fully fledged clients.

Observation 3: Borrowers who are interested in microloans are prepared to pay higher interest

rates if, in return the access to the loan is fast and easy.

4.3 Do target group members exhibit a typical financing pattern?

We also aimed to find out whether persons interested in microloans exhibit a typical financing

pattern. To analyze this question we used again target group membership as the defining variable

and compared the financing patterns among the two groups (see Figure 2). There is a clear

discrepancy between the funding needs revealing that borrowers interested in microloan products

exhibit a specific financing pattern. Over the three-year period, the target group exhibits fairly

constant funding needs, while the other group of persons (who do not need any microloan

access) reports higher funding needs in the first year and rather low needs in years two and three.

An ANOVA test was conducted to compare the groups’ funding needs in each year, yielding a

significant F value only for the first period. We presume that a lower level of start-up finance is a

distinguishing feature of the target group.

- insert Figure 2 about here - (see appendix)


Unlike non-target group members, the target group reported an average of €6,000 to €12,000 per

year over the three-year period.20 This is a possible benchmark loan size for microloans. Funding

needs of non-target group clients, in contrast, average at €19,00021 in year one and drop to far

below €5,000 in the subsequent two years. The higher funding volume in the first year might

indicate that these borrowers have received bank loans that are generally approved only beyond a

certain amount. In this case, banks are usually more willing to finance subsequent loans. Our

analysis also showed that these borrowers were granted overdraft facilities significantly more

often than target group members in the years after founding the business.

Equity ratios of the two groups display a palpable discrepancy as well: target group members

continuously exhibit lower equity ratios than non-target group members. An ANOVA test

confirms statistically significant differences for the first year (p=.02). As a certain amount of

equity capital is the necessary precondition for receiving a bank loan, it is quite probable that

target group members are more often excluded from the formal banking system. Therefore,

microloans present a viable funding alternative and higher interest rates do not deter them.

Observation 4: Compared to non-target group members, microloan applicants have i) lower

funding needs during the start-up phase, ii) more evenly distributed funding needs, and iii) less

equity.

As most existing MFIs – not only in Germany but also in most Western European countries -

offer loan products only to start-ups in year one, this observation probably explains why there is

such an exceptionally low demand for these products.

4.4 A model for determining target group membership

In order to determine relevant factors affecting target group membership, a model for the

complete borrower group was employed. A binary logit regression was used with ‘target group’ as

the dependent variable. In Model A, personal explanatory variables were applied. The business

variables were added to perform a second Model B. Finally, an extended Model C was estimated,

in which financial characteristics of the firm were included. Nagelkerke R² and Cox & Snell R²

provide estimates of good overall model fit for each of the specifications.

20 Figure 2 is adjusted for seven outliers within the borrower group as they distorted the means quite heavily (including the outliers, means oscillate between €15,000 and €20,000). The 75th percentile including outliers is € 25,000.

21 The average is € 32,000 if we do not adjust for outliers.


Table 7 reports the estimation results of the three models employed. The business owner’s age

does not have a significant impact on target group membership. The same holds for gender,

which is only weakly significant in Model C. Foreigners have a higher propensity to be interested

in microloan products, which could be due to the fact that they are more often excluded from the

banking system and therefore depend more heavily on alternative funding.22 Concerning the

education variables, master craftsmen have a significantly lower propensity to belong to the target

group, which is indicated by the negative sign of the dummy. They usually have higher funding

needs during the start-up period due to more expensive equipment than, for example, businesses

in the service sector.


With respect to the business variables, we observe that firms operating in the retail business have

a strong propensity towards microloans. This coincides with our findings that potential microloan

clients need fast access to funds. Retail business is traditionally characterized by near-term

funding needs, often triggered by the requirement to pre-finance inventory (van Auken and

Carter, 1989). The other industry dummies have no significant bearing on target group

membership. We therefore conclude that being a retail business is the only relevant firm

characteristic that determines target group membership - a result that coincides with the evidence

from many countries when microfinance products were introduced (see e.g. Kritikos and

Vigenina 2005) and with the anecdotal evidence that owners of firms in the retail business sector

are “redlined” by commercial banks.

Model C contains a set of dummies providing information on the firm’s funding characteristics.

Businesses that received a private loan during their first three years of operations tend to show a

significantly higher interest in micro-loans. Anecdotal evidence from the interviews confirms that

people who have received funding through private loans are reluctant to borrow from friends and

relatives in the future, as this implies a certain kind of social dependency. Applicants who had

previously received a bank loan are less likely to belong to the target group due to their

preference for the lower interest rates offered by banks. This confirms the conjecture we made

when analyzing funding patterns. Finally, the dummy ‘funding needs in year two or three’ does

affect target group membership positively. This validates our financing pattern analysis, which

22 Blanchflower et al. (2003) show similar empirical evidence for this observation when analyzing small businesses’ access to the US credit market.


showed rather constant funding needs for the target group and therefore an elevated need for

finance after foundation of the business.

Observation 5: Business owners who are interested in microloans can be found among foreign

and among retail business owners as well as among those who had previously received private

loans. Those, who showed investment patterns with constant investment volumes over the years,

and those who needed finance in the years after business foundation, were also more likely to

belong to the target group.

5. Conclusion

It almost goes without saying that micro-businesses have more difficulties in getting outside

finance than larger firms have. In response to a potential demand for microfinance, several MFIs

have been set up during the last decade in Germany (rather late compared to countries like

England or France) offering microloans particularly to start-ups. However, their outreach

remained far below expectations. Their disappointing experiences revealed that beyond the basic

insights that business owners (also in Germany) face higher financing problems the smaller their

firms are, little is known about financial sources micro entrepreneurs are making use of.

Inspired by the pecking order theory this study investigated the demand side of this market

segment in Germany. We conducted a survey of 213 entrepreneurs, and identified their funding

needs, their financing problems and their product preferences with regard to microloans.

Moreover, we were able to reveal which groups express specific interests in microloans. Two out

of three business owners in our sample reported that they were able to operate without outside

finance and that they were not interested in taking any loan from banks, friends or family

members, an observation in line with the pecking order theory. Among the other business

owners who were in need of outside finance, little more than half of them were able to get a loan

from banks, while the other have was rejected or did not try to get a bank loan; thus the second

half started with loans from friends or family, reduced their investment volume or faced liquidity

constraints.

Concerning the extent of the problem from a market-based point of view, our results can be

interpreted in two ways: When related to the overall number of entrepreneurs it seems as if only a

minority of businesses is actually excluded from access to outside finance which signals that the


share of underfinanced micro business owners is negligible.23 However, as it is not possible to

reveal whether persons who did not apply for a bank loan are also excluded from access to credit,

it is more meaningful to relate persons who had no access to bank loans to those who applied for

a loan. In this context the rate of financing problems is substantial, as we showed applicants had

to apply more than once for a bank loan or were completely rejected.

Based on these findings, we analyzed the potential demand for microloans. We found out that in

our sample little less than half of the business owners being in need of outside finance were

interested in a microloan with all its specific features. We consider these people to be members of

the target group while we termed persons who had no interest in microloans as non-members. As

we found two different financing patterns, we are able to further specify the target group: non-

members needed funds particularly during their start-up phase, while target group members

exhibited fairly constant funding needs over the first three years of operations and significantly

lower funding needs than the non-members in year one. We, thus, revealed a kind of investment

pattern to which traditional banks have not yet adjusted and which fits to the approach of

microfinance products.

We show that MFIs need to focus on certain types of potential clients that are particularly

interested in microlending products; in our survey these were migrants and retail business

owners, persons who received loans from their private network or who were dissatisfied with the

service quality offered by banks where they had felt patronized by loan officers. Moreover, the

decisive features to create a demand for microlending products at higher interest rates are: quick

and easy access to loans, a high probability of loan approval once a business owner decided to

apply for a loan, and an environment which does not remind the clients of their last bank visit.

In order to provide such good service quality to their customers, MFIs will have to employ

professionally trained loan officers who are able to put the crucial product features into action

and to carry out effective screening procedures at the same time in order to maintain a low

percentage of high-risk clients. Only then will an MFI successfully attract customers and be able

to promote its unique advantages over commercial banks.

Our research, although relatively small in terms of sample size, also gives preliminary evidence

that by targeting only start-ups the existing government-owned or government-financed MFIs

23 This kind of policy is followed for instance by the German State owned bank KfW – see their recent report on microfinance, KfW (2008).


unnecessarily confined their target markets. Furthermore, the loan products they offered seemed

to be inappropriate to the demand of their potential clients.

In this context it is also necessary to ask whether improving the access to external finance for

micro entrepreneurs is an effective strategy from a more macroeconomic point of view. One

might argue that, if micro entrepreneurs partly cannot obtain external finance without new

microloan products, larger firms who have access to outside finance might take over the market

shares of the excluded companies so that the overall economy is in the same state without a

microfinance approach. However, there are several reasons why access to microloans is an

important issue. Most prominently, competition increases if micro entrepreneurs do not face

higher barriers to financial means than larger firms which is why micro businesses should at least

have similar options of accessing external finance. It could be further argued that micro

entrepreneurs are better able than larger firms to serve the individual customer needs and by

doing so micro entrepreneurs may contribute to the growth of the economy. Last but not least, it

is important from the labor market’s point of view to provide micro entrepreneurs with access to

finance given that with micro funding available, entrepreneurs are better able to create and

maintain their own job and, with a certain probability, additional jobs as well.

We conclude that, although different and certainly smaller than expected, there are markets for

microlending in industrialized countries such as Germany. They have a potential to further grow

especially if there should be a latent demand among those business owners who were afraid of

asking for a loan. To this end, additional research with larger survey data would be helpful.


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Appendix

Table 1: Overview over differing shares borrowers and non-borrowers.

The share of borrowers that Percent per subgroup of

borrowers (N= 76)

Percent overall

(N=213)

Used bank loans 54% 19%

Were rejected from banks 30% 11%

Used Private loans and/or equity 30% 11%

Had funding gap after rejection 15% 5%

Table 2: Descriptive Statistics for the two subsamples.

*** significant at a 1% level ** significant at a 5% level * significant at a 10% level (‘-‘ indicates that more than 10% of cells have expected count less than 5) ª adjusted for outliers (funding requirements exceeding €100,000 in at least one year)

Variable Borrowers

Non-

borrowers Chi²

Values N Mean N Mean

Owner-Entrepreneur

Characteristics

Female

Foreigner

Education

Academic

Master craftsman

Age

Business Characteristics

Retail

Crafts

Liberal profession

No. of employees

Team foundation

76

76

76

76

76

76

76

76

76

76

0.41

0.09

0.42

0.26

42.68

0.13

0.24

0.13

1.13

0.17

137

137

137

137

137

137

137

137

137

137

0.39

0.02

0.53

0.20

44.80

0.04

0.07

0.20

0.31

0.07

0,38

5.39**

2.14

1.24

-

6.75***

12.94***

1.46

17.46**

5.86**


Table 3: Comparison of funding needs between borrowers (B) and non-borrowers (NB), in %.

Year 1 Year 2 Year 3

B

(N=76)

NB

(N=137)

B

(N=76)

NB

(N=137)

B

(N=76)

NB

(N=137)

None 2.6 13.1 50.0 65.0 52.6 65.7

Less than €5,000 19.7 43.8 25.0 24.1 26.3 26.3

> €5,000 – €10,000 25.0 24.1 11.8 8.0 9.2 6.6

> €10,000 –

€25,000

23.7 14.6 9.2 1.5 6.6 1.5

> €25,000 –

€50,000

19.7 3.6 1.3 1.5 2.6 0

More than €50,000 9.2 0.7 2.6 0 2.6 0

Total Sample (N=213)

yes no

Need for outsidefinance?

Requested bankloan/overdraft?

yes no

Succesful?

yes no

35% had funding gap52% used combination of private loan and

equity13% reduced need or obtained trade credit

35% 65%

84% 16%

64% 36%

58% used combination of private loanand equity

17% used existing overdraft25% other

Total Sample (N=213)

yes no

Need for outsidefinance?

Requested bankloan/overdraft?

yes no

Succesful?

yes no

35% had funding gap52% used combination of private loan and

equity13% reduced need or obtained trade credit

35% 65%

84% 16%

64% 36%

58% used combination of private loanand equity

17% used existing overdraft25% other

Figure 1: Overview of the subsamples.


Table 4: Comparison of target group (T) and non-target group members (NT) (N=74).

Statements Mean ranks z-value

(Prob > |z|) T NT

All in all, I have a positive impression of my

meeting(s) with the bank(s).

26.96 31.94 -1.112

(0.266)

I felt I was taken seriously and treated as a

fully fledged client.

24.91 33.25 -1.86

(0.063)

I had the feeling that the loan officer to

whom I spoke understood my business

plan.

24.27 31.97 -1.754

(0.079)

I received competent advice concerning

relevant products.

23.45 26.87 -0.83

(0.407)

I received comprehensive information on

all terms and conditions.

19.22 26.47 -1.768

(0.077)

Table 5: Comparison of target group (T) and non-target group members (NT) who received a loan (N=40).


(Prob > |z|) T NT

All in all, I have a positive impression of my

meeting(s) with the bank(s).

13.91

22.61

-2.47

(0.014)

I felt I was taken seriously and treated as a

fully fledged client.

14.05

22.35

-2.27

(0.023)

I had the feeling that the loan officer to

whom I spoke understood my business

plan.

15.55

21.65 -2.03

(0.042)

I received competent advice concerning

relevant products.

18.91

20.77

-0.99

(0.323)

I received comprehensive information on

all terms and conditions.

16.14

21.63

-1.71

(0.088)


Table 6: Comparison of target group members (T) and non-target group members (NT) (N=74).


(Prob > |z|) T NT

I am agreeable to accepting higher interest

rates when taking a loan if this allows more

flexibility in repayment schemes.

37.90

37.21 -0.28

(0.8)

In my line of business, it is crucial to

receive a loan rapidly when necessary.

48.34

28.29

-2.4

(0.02)

It matters to me to pay no amortizations,

especially in the first months after

borrowing.

39.10

35.64 -0.92

(0.36)

I am willing to pay higher interest rates for

faster access to loans.

44.17

31.62

-2.02

(0.04)

Individual support given by the contact

person is as important to me as to the terms

of a loan.

36.79

37.90 -0.25

(0.82)

Target Group

Non-Target Group

0

5

10

15

20

25

30

35

40

1 2 30

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

Year

€%

Target Group

Non-Target Group

0

5

10

15

20

25

30

35

40

1 2 30

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

Year

€%

Figure 2: Funding needs (lines, right scale) and equity ratios (bars, left scale) of target group and non-target group members adjusted for outliers with funding needs exceeding €50,000 (N=69).


Table 7: Binary Logit Estimation of determinants of target group membership.

Explanatory Variables Model A Model B Model C

Gender (female=1) -0.63 (0.64) -0.97 (0.77) -2.83 (1.63)*

Age -0.03 (0.04) 0.02 (0.05) -0.03 (0.08)

Nationality (foreigner=1) 2.47 (1.54)* 2.44 (1.44)* 5.04 (2.46)**

Education

(academics=1)

(master craftsmen=1)

-0.24 (0.67)

-3.29 (1.24)***

-0.07 (0.87)

-3.57 (1.46)**

1.91 (1.78)

-6.33 (3.07)**

Preceding period of unem-

ployment (months)

0.01 (0.03) -0.01 (0.03) 0.08 (0.07)

Line of business

(retail=1)

(crafts=1)

(lib. professions=1)

2.67 (1.24)**

0.87 (1.05)

-0.09 (0.99)

6.76 (2.64)***

0.72 (1.85)

0.08 (1.28)

Team foundation 2.03 (1.11)* 3.44 (2.15)

Received private loan 2.46 (1.40)*

Received bank loan -4.85 (1.96)**

Received overdraft -1.03 (1.66)

Liquidity finance -2.71 (1.90)

Funding needs in year 2 or 3 2.64 (1.64)*

Constant 1.38 (1.78) -1.34 (2.26) 0.43 (3.62)

Nagelkerke R² 0.345 0.485 0.754

Cox & Snell R² 0.254 0.357 0.556

Model Chi² 50.28 27.4 18.21

Number of observations 75 75 75

Standard errors in parentheses

*** significant at a 1% level ** significant at a 5% level * significant at a 10% level

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