The Credit Frontier · 2020-05-19 · Network Infographic: Ana Subtil Cover Design: Ana Subtil Our...

The Credit Frontier - research paper

1

The Credit Frontier research paper

Powered by:


Powered by:

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Consequat mauris nunc congue nisi. Morbi tempus iaculis urna id volutpat. Suspendisse





Colophon

This report has been made by a multi-local team in Milan and Lisbon, in a cooperation project of FinTechStage, Fintech District and illimity Bank.

Editor-in-chief: Francesca AlivertiProject Lead: Francesca Aliverti and Mico Curatolo Editors: Francesca Aliverti, Flavio Proietti PantostiResearch and Content: Flavio Proietti Pantosti, Alessandro Raschi and Renata AlvesNetwork Infographic: Ana SubtilCover Design: Ana SubtilOur team: Francesca Aliverti, Flavio Proietti Pantosti, Ana Subtil, Matteo Rizzi, Renata Alves, Mico Curatolo, Alessandro Longoni, Alessandro RaschiCompanies, individual profiles, and interviews: FinTechStage Network

Many thanks to all the partners and interviewees that allowed us to complete this overview.

Reactions:[email protected]

FinTechStage & FinTech DistrictVia Filippo Sassetti, 32, 20124 Milano MI, Italy

Foreword

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Consequat mauris nunc congue nisi. Morbi tempus iaculis urna id volutpat. Suspendisse ultrices gravida dictum fusce. Senectus et netus et malesuada fames ac turpis. Gravida dictum fusce ut placerat. Massa sed elementum tempus egestas sed sed risus. Aliquam sem et tortor consequat id porta nibh venenatis cras. Porta lorem mollis aliquam ut porttitor leo. Nisi porta lorem mollis aliquam ut porttitor leo a. Porttitor eget dolor morbi non. Sit amet luctus venenatis lectus magna fringilla urna porttitor. Adipiscing tristique risus nec feugiat in fermentum posuere urna nec. Amet tellus cras adipiscing enim eu. Eros donec ac odio tempor orci dapibus. Id aliquet lectus proin nibh nisl. Est pellentesque elit ullamcorper dignissim cras tincidunt lobortis feugiat vivamus. Vitae elementum curabitur vitae nunc sed. Nec ultrices dui sapien eget mi.

Sit amet est placerat in egestas erat imperdiet. Sem viverra aliquet eget sit amet. Ornare arcu odio ut sem nulla pharetra. Et netus et malesuada fames. Sed turpis tincidunt id aliquet risus. Eget mi proin sed libero enim sed faucibus turpis. Faucibus pulvinar elementum integer enim neque volutpat. Mattis nunc sed blandit libero. Et magnis dis parturient montes nascetur ridiculus mus mauris vitae. Justo donec enim diam vulputate ut pharetra sit. Nunc eget lorem dolor sed viverra. Sit amet facilisis magna etiam tempor orci. Ipsum dolor sit amet consectetur adipiscing


8



Table of contents

Introduction1. Scenario

1.1 Macro1.2 SMEs in Europe and Italy1.3 Access to Finance for SMEs

2. Pain points and trends2.1 SMEs pain points2.2 Banks pain points2.3 Emerging technology trends

2.3.1 Lending-as-a-Service2.3.2 The Role of Neo Banks2.3.3 Digital Process: Loan Origination Automation2.3.4 Data Sharing2.3.5 Tech-Companies and alternative data to improve credit scoring

3. Tagging InnovationThe credit frontier and clusters

3.1 Credit frontier InfographicClosing remarksAppendix

1012131416192022242425 262627

2930444648

Introduction

10

FinTech has come a long way. From being one of many business support functions to a driving force in both the financial services and technology fields, sporting 48 unicorns, startups worth more than $1B, worldwide by mid-2019, whose collective value hovers around $190B. FinTech is not simply the geek version of financial services, it has in fact worked as testing ground for advanced technologies that are today widespread, especially in the field of data. After the Great Financial Crisis a new breed of FinTechs emerged, growing alongside the “elders” such as PayPal. At the very start of the FinTech revolution initiatives such as Swift Innotribe, contributed to a new direction of development.

We could say SMEs have seen a similar trajectory, with alternate fortunes as well. The segment has for long been treated, at least credit-wise, as a low margin byproduct of corporate credit that doesn’t ensure nor the stability nor the opportunities that banks have traditionally preferred.

The development, commercialization, and affordability of new technologies paired with hampered trust in traditional financial institution has substantially changed how both FinTechs and SMEs view themselves and their context. At first to parallel developments as FinTechs focused on the wider and seemingly easier consumer market while SMEs worked out new tools for sustaining their financial needs. Nevertheless, after some time both communities realized the opportunity that had been emerging and the focus on SME credit has since been taking up more and more pace.

The objective of this short research is to put the two worlds in relation and better understand where the segment is going. This has been done through written and oral sources, reports and ad hoc interviews, drawing from the experiences and networks of the actors involved.

The US Federal ReserveBanks developed the FedaireFunds Service.

Frederick Lincoln Fuller created the IBM 801 Bank Proof cash machine.

Frank McNamara created the Diners Club credit card.

A Bardays bank branch in Enfield, London opened the world’s first ATM.

NASDAQ invented electronic trading and the IPO.

Carl Reuterskold founded SWIFT (Society for Worldwide Interbank Financial Telecommunication).

Michael Bloomberg created Innovative Market Solutions (IMS).

William Porter created TradePLus, today E*Trade Group.

Financial Services Technology Consortium (Fintech) was a project initiated by Citicorp.

1918

1934

1950

1967

1971

1973

1981

1982

1993

Evolution of Fintech



11

Apple launched Apple Pay.

Google introduced Google Wallet.

Paypal was founded under the name Confinity.

The first mobile payment was realized, via text message, buying a Coca-Cola from a vending machine.

The first virtual bank called Security First Network Bank was opened.

Wells fargo became the first bank to offer an online checking account.

2016

2014

2011

2009

1998

1997

1995

1995

Bitcoin v 0.1 was released, Innotribe created.

The first university fintech bachelor program was created.

Global Fintech Funding tops $111B2018

2019

Marketplace lending and alternative

underwriting platforms

Lending

Blockchain/Crypto

Regtech Personal FinancePayments/

Billing

Insurance

Capital Markets

Wealth ManagementMoney Transfer/Remittances

Mortgage/Real Estate

A note on our approach

The objective of this short research has been to highlight the most interesting trends of the Credit segment, by putting in relation the SMEs and the Financial Institution ecosystems.

The focus on the current scenario, on the main challenges and pain points and on the most interesting technology trends is aimed to give to the reader a better understanding of the next future trends of the segment.

The research team analyzed reports, research papers, articles and sources while also realizing ad hoc interviews with representatives of various players of the financial world, drawing from their experiences and networks. In the Appendix you’ll find a short bio of all involved experts and a full version of the interviews.

The several illustrations, figures, and boxes with numbers and excerpts from the above mentioned sources are meant to give a more insightful read, thanks to the contribution of institutions and individuals. The “Tagging Innovation” section is the second part of this short research, an insightful mapping of the most interesting fintech companies representing advanced and innovative solutions for SMEs and lenders in the space.

The research team selected together with illimity the criteria for the census and mapping of these companies with a focus on European countries and Israel.

1.Scenario


12


13

The traditional banking industry is facing a revolution: this is not only due to a change in service offering and product portfolio, but it is also affected by the increase in competition, industry 4.0 and regulatory change.

Starting from an already difficult funding scenario for SMEs, the advent of the 2008 financial crisis made access to their traditional sources of funding extremely difficult, especially in the countries that suffered recession the most. The number of rejected loans increased, loan rates and conditions became less favourable. To limit this problem, the European Central Bank

adopted a series of unconventional measures such as Long-term refinancing operations, quantitative easing and so on with the aim of providing liquidity to the market and facilitating loan standards.

Despite these measures, after the financial crisis banks have been ever-

more cautious, especially when it comes to funding for smaller and riskier business. In particular, outdated legacy systems and processes are the major obstacles for traditional banks, which are slow to adjust and respond to changing market conditions. As a result, SMEs struggle to access finance and it’s hard for banks to meet the evolving demands of today’s SMEs.

So what about this revolution?The most evident trend is the rise of digitally native banks which, thanks to technology advancements, are radically increasing competition by lowering costs and entry barriers. Wider industry 4.0 innovations, at the same time, impact distribution channels of banking services, with banks that can, or could, leverage on digital channels, big data, and cloud computing technologies. Finally, compliance is playing a key role, especially at European level, with regulators having imposed several regulatory changes.

1.1Macroscenario

“For banks, the only way out of their business model conundrum is to learn how to rebuild

the banking and insurance charter holistically, tearing down operational and regulatory pillars across business units transforming the industry

into an advisory mechanism.” Paolo Sironi - Author, IBM Fintech Advisor

VS


14

SMEs serve as the backbone for the economy and are active at nearly every point in the value chain as producers, suppliers, distributors, retailers, and service providers, often in partnership with larger businesses. SMEs drive innovation, economic growth and job growth in Europe, but need higher investment in skills, innovation and tech to boost productivity.

After the financial crisis the employment and value added showed a positive trend due to the increasing number of SMEs over time (Fig. 1).

1.2SMEs in Europe and Italy

In this context, FinTechs and digital native banks have a great opportunity: they can know more about their customers by leveraging digital distribution channels and can take advantage of new regulation and technology because, by starting ex novo, can create an ad hoc structure. On the contrary, for traditional banks, adapting to new rules and technologies requires time and resources that could disadvantage them compared to new fintech actors.

“SME has been the neglected segment in the initial years of the fintech revolution, although the nature of SME clients makes them more receptive to PULL-oriented digital propositions, therefore demand driven, than the PUSH-oriented general

public, offer-driven.” Paolo Sironi - Author, IBM Fintech Advisor


15

Italy is the first country in EU-28 by number of SMEs, followed, in order in the TOP 5, by France, Spain, Germany and UK (Fig. 2).

These data point out the significant role played by SMEs, representing the backbone of the European economy by creating employment and growth, especially in Mediterranean countries such as Italy - where their contribution to employment and added value it is higher than EU-28 average (European Parliament, 2019)1.

1European Parliament (2019) - Key figures on SMEs in the european union. Data are based on Eurostat definition of SMEs.

Evolution of SMEs in the EU-28 (2008=100)

Number of SMEs (in 1 000, 2017)

(Fig. 2)

(Fig. 1)

120 114.3

Value added

Number of SMES

Employment

113.8

102.5

110

100

90

802008 2009 2010 2011 2012 2013 2014 2015 2016 2017

IT

FR

ES

DE

UK

3 746

2 9612 662

2 4532 137

Source: 1European Parliament (2019)

Source: 1European Parliament (2019)


16

1.3Access to Finance

The share of bank debt in European companies, and in particular SMEs, as a percentage of financial liabilities is greater than in American companies2. In the US equity capital is on average higher relative to the amount of bank loans (Fig. 3).

2018 debt and equity issuance as a % of total finance provision for NFCs in European countries, the EU average and the US

Quad 4 High equityand low debtQuad 3 Low equity

and low debt

Quad 2 Low equityand low debt

Quad 1 High equityand high debt

% Debt Issuance

% Equity Issuance

Source: Dealogic, US FED, ECB, BoE and other European central banks

2 EUROPEAN CENTRAL BANK (ECB) 2016 - “Trends in the external financing structure of euro area non-financial corporations”. ECB Economic Bulletin.

(Fig. 3)

“SMEs can rarely present comprehensive financial information about their work, so the problem for

conventional banking is that SMEs have much less in the way of fixed assets, they have lots of movable

assets and intangible assets.”Matthew Gamser - CEO, SME Finance Forum

4.5 %

DE

UK

EU 2018

EU 2013

4.0 %

3.5 %

3.0 %

2.0 %

2.5 %

1.0 %

0.5 %

0.0 %

1.5 %0 % 5 % 10 % 15 % 20 % 25 %

US

BE

ITES

CY

MTNL

FR


17

The reduction of traditional bank loans to businesses is confirmed by the decreasing dependence of SMEs on traditional banks. In fact, as of 2017.The prevalence of bank debt amplified the impact of the reduction of loans by banks to businesses after the 2008 financial crisis which had a huge impact on Italian companies, especially on SMEs. Banks loans to SMEs continued to decrease quickly until 2016, while bank loans to large companies almost resumed their pre-crisis levels.

However, over the last couple of years, a new trend emerged in the market where niche segments were partly filled by new digital banks and fintechs that developed new ecosystems, focused on SMEs, particularly on Medium business, based on a new way of financing.

“Many SMEs don’t know about all the financing options available to them or are even hesitant to

apply because of a perceived high cost or assumption that they will be rejected.”

Jessica Alfaro – Consultant, IFC World Bank Group

The use of bank debt is particularly relevant in Italian companies (Fig. 4).

(Fig. 4)

100%

80%

60%

40%

20%

0%

Equity Capital

Italy Germany France Spain EU Area USUK

US

Bank Debt Bonds Other Financial Liabilities

11%

27% 20%

57% 60% 65% 62% 60%

5%11%

5%

15%

14%

8%

18%

19%

1%16%

19%

5%

62%

15%

11%

12%

70%

8%

10%

13%

Breakdown of financial liabilities for non-financial firms3

3Banca D’Italia (2016) – “Annual Report”. Banca d’Italia; Gobbi (2017, 2013) - “Il finanziamento delle imprese in Italia e nell’area Euro”, “Audizione nell’ambito dell’indagine conoscitiva sugli strumenti fiscali e finanziari a sostegno della crescita, anche alla luce delle più recenti esperienze internazionali”. Banca d’Italia


18

(Fig. 5)

Trend of lending stock to Italian SMEs (% change YoY)

4PWC 2019 - “Specialty Finance Challenger Banks in Italy: reshaping the lending landscape?”. PwC Top Trends Financial Services.

This is confirmed by the decreasing dependence between SMEs and traditional banks as of 2017 out of 140.000 SMEs, 40.8% completely self-financed their business without using bank debt (PWC, 2019)4.

In addition, Medium businesses dominate the traditional credit supply to SMEs market in Italy (Fig. 5), which account an overall funding over € 180bn, which includes both bank loans and bonds. On the contrary, small and micro businesses were characterized by a stagnant growth in financing in past years (Fig. 5).

3.0

2.0

1.0

(0.3)

(2.3) (2.1) (2.1)

(1.4) (1.3) (1.6)

(0.9) (0.9)

(0.3)(0.1)

0.5 0.70.5

0.3(0.3)

0.6

1.6

2.6

1.5

0.0

-1.0

-2.0

-3.0Dec 2015

Sep 2016

Dec2016

Mar2017

Jun2017

Sep2017

Dec2017

Mar2018

Apr2018

May2018

Source: PWC 2019 & Banca d’italia

Medium-large companies

Total companies

Small businesses

“There is a presumption that banks used to serve small businesses and they stopped during the financial crisis. In fact, 80% of the customers in

Kabbage’s portfolio have fewer than 10 employees and these are customers that banks have never served

because of size.”Kathryn Petralia - President & Co-Founder

at Kabbage

2. Pain points and trends


19


20

Small and Medium businesses are heterogeneous in type and size. Their needs are very connected to the stage they are in their lifecycle and their financing needs vary greatly, accordingly. During their growth phase SMEs face constraints due to the reduced access to markets, skills and capital. Banks perceive them as risky and costly and this causes a lack of financing options for SMEs with a potential adverse selection dynamic. As a consequence, SMEs usually have to rely on expensive informal sources of capital, finding it difficult to make substantial growth-oriented investments, be it for productivity, hiring newemployees or market expansion.

Small and medium-sized companies have different structures by definition. The reasons behind financing needs for working capital finance change according to their size (Fig 6).

2.1SMEs pain points


21

(Fig. 6)

The amount of financial challenges decreases with the increase of company size. Access to bank lending is more challenging for SMEs than for a Corporate and is less challenging for Medium businesses compared to small and micro ones.

Focusing on medium enterprises, the drivers behind the need for working capital finance are: short term investments, reduction of reported net financial debt improvement and higher liquidity for growth. Medium enterprises have less needs to boost the day-to-day liquidity but are more interested in controlling financial KPI and allocating liquidity to invest in short term projects.

5 EY (2018) - “The Future of SMEs Banking and EY (2018) - “The annual survey to SMEs owners”

5Source: Own elaboration on EY (2018)

Small enterprise(10-49 employees)

Possible drivers behind need for working

capital

Financialchallenges

Level of financialengagement

Medium enterprise(50-249 employees)

Corporate(250+ employees)

• Day-to-day liquidity

• Smoothing out irregular cash flows that may

be unpredictable

• Accessing liquidity for growth

• Seeking less rigid, time-consuming forms

of finance

• Highest credit risk because of low credit rating and lack

of collaterals

• Lack of proper books of accounts and financial

records

• Limited ability to handle administrative burden

• Limited ability to handle multiple relationships with

finance providers

• Represent a small ticket size & high transaction cost

in banks perspective

• Taking months to get credit

• Relatively unsophisticated finance function

• Relatively low awareness of variety of financing

options

• Accessing liquidity for growth

• Reduction of reported net financial debt

• Investment for short-term projects

• Higher credit risk than larger firms because of low credit rating or lack

of collaterals

• Lack of proper books of accounts and

financial records

• Lacking in experience to adopt the best financial practices

• Limited ability to handle administrative burden and complexity

of some traditional products

• Taking months to get credit

• Sophisticated finance function

• Awareness of variety of financing options

• Reduction of reported net financial debt

• Investment for short-term projects

• Higher access to finance due to low

credit risk

• Sophisticated finance function

• High level of awareness of variety of financing options

• Ability to automate processing of payables

and receivables


22

Banks have a lower propensity to lend to small and medium businesses for several reasons, including greater information asymmetry and higher fixed management costs on small loans. In Europe, still ⅓ of SMEs funding requests are rejected or receive less than requested (Fondazione CS MARE, 2019)8. The lenders generally point out to the lack of information on SMEs that makes their risk profile evaluation very hard.

Often small and medium businesses don’t have a solid financial structure and operate in sectors that are still reeling from the financial crisis.These factors don’t let them easily access

2.2Banks pain points

Accordingly, the main pain points for SMEs in asking for a loan: long and complex application process -/+ 24h on loan origination paperwork plus some weeks to get a loan approval, wait for a credit decision, high interest rates and a low transparency as the reasons behind their dissatisfaction.

Among these, speed appears to be a big barrier for SMEs, with only 3% of those seeking funds obtaining finance within a week (The Paypers, 2019)6. In addition, the larger the SME, the longer it took to secure loans, for medium business, it could take from five to six months. According to a McKinsey study (McKinsey, 2018)7, today the time needed for an SME to get a decision

on the provision of a bank loan is between 3 and 5 weeks. The digitalisation processes can reduce this time to 2 days, with obvious advantages from a cost optimization point of view.

ACCEPTED

DENIED

More than 1/3 of SMEs funding requests rejected or reduced by banks for lack of risk profile information

Are w

e sure those are the best o

nes to

finan

ce?

6The Paypers (2019) - “Merchant lending reimagining business loans”7Mckinsey (2019) - “The lending revolution: How digital credit is changing banks from the inside”8Fondazione CS MARE (2019) - “SMEs access to finance”

VS

48 h

Time to loan, from traditional to FinTech

5

“SMEs can rarely present comprehensive financial information about their work, so the problem for

conventional banking is that SMEs have much less in the way of fixed assets, they have lots of movable

assets and intangible assets.”Matthew Gamser - CEO, SME Finance Forum


239Capgemini (2018) - “World Fintech Report 2018”.10European Central Bank (2019) – “The euro area bank lending survey”

financing. In the event of an economic recession, credit is first reduced to those borrowers who suffer most from problems of agency costs and information asymmetries and is limited to the companies that appear best in class, again engaging in an adverse selection dynamic.

To sum up, the main challenges preventing bank lending to SMEs are: the limited abilities to handle administrative burden, the difficulty in providing security and guarantees, the higher credit risk compared to the larger firms, the difficulty for banks to monitor the risk, the absence of a sophisticated finance function in small-medium business and the limited availability of financial data (information asymmetry).

The overall rigidity in the payment process increases SMEs difficulty in applying to a traditional bank for finance. As a matter of fact, 70% of Fintechs claims that the main weakness of large financial institutions is the lack of agility (Capgemini, 2018)9.

The ECB bank lending survey - a survey in which banks expressed their perspectives on the SME lending market - shows that the credit standards eased for loans to small and medium-sized enterprises while remained broadly unchanged for loans to larger firms in the second quarter of 2019 (ECB, 2019)10.

Competition is the factor contributing in easing credit standards, confirming the key competitive role of new Fintech actors in such market.

“We are able to interrogate the data differently and more efficiently, […] we use it to understand in real time how a business is performing and to predict their performance

in the future, and […] we are able to offer unique products to our customers.”

Kathryn Petralia - President & Co-Founder, Kabbage

“While ‘traditional’ players attract savings and need to be prudent, the new kind of

providers obtain funding ‘case by case’. The latter makes them in a way less vulnerable

for large economic/financial shocks, because they simply stop providing new loans.”

Geert Gladdines - Policy Advisor Business Services & SME Specialist, NVB - Dutch

Banking Association


24

Developments in financial technology and online lending offer medium businesses a new alternative: Lending-as-a-service, or LaaS. LaaS is a sub-category of Banking-as-a-Service (BaaS), which refers cloud-based infrastructures and Application Programming Interfaces (APIs) being used to allow businesses to build, configure and manage their own financial services11.

In practice, the new digital players, leveraging on data collected through digital distribution channel, can apply AI and ML algorithms for credit scoring, for improving credit scoring models and use innovative underwriting methodologies.

The LaaS paradigm expands the range of financial solutions available for SMEs.

In today’s digital world lack of information is no longer an issue, rather it is the lack of capability to source and process correctly the relevant information about SMEs. Traditional lenders will need to reinvent their business models, widening and improving their scoring systems to meet SMEs needs.

11Own elaboration on Tradeleger (2019) - “Lending-as-a-Service (LaaS) – Next generation Marketplace Loans”

2.3Emerging technology trends2.3.1Lending-as-a-Service


25

The measured increase in regulatory requirements was 500% between 2008 and 2018.

Traditional banks worldwide claim an annual cost of about $ 207 billion to meet the increasing regulatory requirements of the sector (Links Foundation, 2019)12. The increase in competition and the consequent fragmentation of

the sector has generated a strong pressure on margins. Traditional banks struggle to adapt their organization in response to new paradigms, following the digitalization of processes and the outsourcing of parts of the chain of value to improve the cost / income ratio. The clash between market operators has therefore shifted to the digital channel, where new players have appeared, native digital banks. These have high digital service standard, matching the user experience offered by large technology companies.

The traditional banking way to SMEs lending based its process via non-digital channels. The credit processes are often slow and not suitable for small-medium businesses. Moreover, it’s difficult and inefficient to exploit credit enhancement opportunities. The real challenge is to apply new models for risk management. Neobanks are now offering advanced matching engines to leverage new models of risk scoring based on social and big data, employ a fully efficient-digital process and a fast and almost automatic underwriting process, which is crucial for SMEs. SMEs lending requires a low cost to income ratio and short response time (2 days) and in terms of the marginality SME lending can

2.3.2The Role of Neo Banks

12Links Foundation (2019) - “Banche Native Digitali”

2008

2018

X5

Regulatory changes in the financial sector

“The reason I would argue that there is so much volatility in small businesses performance and

success is that they don’t have access to the tools that large businesses have.”

Kathryn Petralia - President & Co-Founder, Kabbage

“For the most part if you are an alternative lender you are not regulated yet […] but I believe that’s going to become an issue.”

Matthew Gamser - CEO, SME Finance Forum


26

A way to renew traditional banking business models is leveraging online applications in order to automate processes. New SME lending tools guarantees smooth solutions for all types of SME loans (underwriting, automated KYC, and so on). To point out two distinguished examples, in 2015, JP Morgan Chase partnered with OnDeck Capital, a marketplace lender, to provide

loans to small businesses based on algorithms. On the European side of the Atlantic, Kabbage, a Fintech pioneering automated lending, did the same by partnering with ING to deliver instant capital to small businesses throughout Spain. From an SME’s perspective, the use of cloud accounting and invoicing and settlement process automation makes assessing eligibility for financing straightforward and rapid. Another

potential game-changer in the field of trade finance is blockchain, which presents applicability to improve processes and gain efficiency but still needs to prove its potential.

2.3.3Digital Process: Loan Origination Automation

The possibility to share data among financial institutions (and Fintechs) truly unlocks the power of credit risk model predictions. The larger the set of data, the greater the accuracy of scoring models. This is what the Japanese Risk

2.3.4Data Sharing

produce a yield of 6-7% (PWC, 2019)4.Digital banks have alternative and unconventional distribution channels, are highly skilled in restructuring process, are digital-based and have flexible operating models with low fixed costs. These features allow them to focus on niche segments characterized by higher risk profile and/or higher yields.

“Artificial Intelligence is commercially untapped in the western world since challenger banks have not learned yet how to build advisory open banking platforms that deliver real value to clients. AI could help them to

unlock this value.”Paolo Sironi - Author, IBM Fintech

Advisor

4PWC 2019 - “Specialty Finance Challenger Banks in Italy: reshaping the lending landscape?”. PwC Top Trends Financial Services.


27

13T20 Japan (2019) - “Digital Innovation Can Improve Financial Access for SMEs” 14Statista (2019) - “Alternative Lending report 2019”

A way to reduce management costs and enlarge the customer base for banks and other players is to adopt alternative credit scoring solutions. In fact, the high relative cost of managing small-sized loans is due to the credit analysis effort to rate the quality of SMEs’ risk profile. In 2017, the global alternative lending market

was estimated to have a transaction value of $ 380.6 billion (Statista, 2019)14.

In addition, scoring models can be made more efficient by leveraging alternative data such as social information, invoice data, e-commerce. This type of contextual data enhances credit

risk scoring accuracy and consequently reduces cost of financing for SMEs. In China the Ant Financial Services Group, (associated with Alibaba) has succeeded in leveraging alternative data

coming from e-commerce transaction through AI in order to provide credit to SMEs.

2.3.5Tech-Companies and alternative data to improve credit scoring

$380+ Billion

Global alternative lending mark

et in

2017

Ant Financial is a trailblazing example of providing financing to SMEs by leveraging data

from e-commerce transaction on partner site Alibaba.

“Artificial Intelligence is commercially untapped in the western world since

challenger banks have not learned yet how to build advisory open banking platforms that deliver real value to clients. AI could

help them to unlock this value.”Paolo Sironi - Author, IBM Fintech Advisor

“New credit scoring models, and alternative lending models using access

to increased amounts of data are important, but have yet to significantly scale up or replace more conventional

cash flow-based scoring models.”Jessica Alfaro – Consultant, IFC World

Bank Group

Data Bank (RDB), Credit Risk Database (CRD) 2, and the Fichier Bancaire des Entreprises (FIBEN) are respectively doing, the RDB in Japan and the CRD

and FIBEN in France (T20 Japan, 2019)13. The collected data is used for portfolio management and loan review, having reportedly contributed to improve the credit risk analysis of banks.


28

Tech companies have the potential to renew and disrupt the traditional SMEs lending industry using machine learning and AI to analyse the trove of data that they collect from businesses in their ecosystem.

Banks have understood that in order to meet SMEs’ needs, they need to go beyond traditional services and must start providing other tools and solutions that allow them to collect customer data. For example, HSBC launched a Knowledge Center, an online magazine and information center for small businesses which features interviews with thought leaders & inspirational entrepreneurs. Similarly, another solution could be to create or plug-in a social media platform for SMEs to offer immediate answers and support to their queries.

Data sharing and open banking are deeply interrelated with this matter and will play a key role in enabling alternative data. This can make the difference in the increasingly competitive SME lending market. For example, in 2018, Iwoca provided to an UK beauty salon the first loan using open

banking data: 40 data points indicated how the beauty salon was performing and the salon was able to receive the loan in less than 2 hours.

First open banking loan in 2018: Iwoca provided a loan in less than 2 hours thanks to

more than 40 open data points.

HSBC launched a knowledge center and magazine specifically aimed at small businesses with interviews

and insights from thought leaders and entrepreneurs.

Technology came to small business lending very late, 10 - 15 years after

consumer lending, and the reason for that is that it’s hard to get the data.Kathryn Petralia - President & Co-

Founder at Kabbage


29

3. Tagging Innovation


29


30

The Credit Frontier

Infographic clusters

The segment of alternative lending is by far the largest in the field, it encompasses very different players, business models and lending structures. What unifies them is the value proposition of being an alternative to traditional loans, beating them either on speed, terms, user-friendliness or all of the three.

The decision to split up the cluster in invoicing and loans & working capital is due to the structural difference given by what the two types of financing are based on.

The first on direct evaluation of how likely the payment of invoices is, while the second is linked to the business of the lendee, therefore more similar to traditional bank financing.

The data intelligence cluster is probably the most interesting tech-wise and has also been a focus of the research given the potential of the developments that are taking place. The segment encompasses various types of business, mostly focused on how to put great amounts of data to use in the lenders’ interest. Where they radically differ is the type of data the models are based on and how they are processed.

Data Intelligence

Neobanks

Alternative Lending

This cluster is populated by many of the most well-known players in the “European wave”, some of which have a strong consumer focus and are only more recently directing their attention to the SME segment. Neobanks are very different among themselves and cover a wide spectrum of services and approaches to banking, at the same time the reason why they need a cluster for themselves is in their very definition – these are the ones directly taking on traditional banks.

What do we see when looking at the SMEs credit ecosystem? A diverse reality where a fundamental role is played, of course, by traditional lenders. Our objective in this second part of the research has been indeed to go at the opposite end of the spectrum, looking for the up and comers which are challenging and pushing the “credit frontier” further, track them and find a medium that could communicate their energy and position in the wider sector – this is why we build the infographic.

The criteria by which we’ve selected the players are mainly linked to their relevance for the ecosystem, their position in the SME credit value chain, and their innovative pulse which we look at by evaluating the business model and supporting technologies.

In practice though, an Infographic like this must be a continuous work in progress due to the dynamic landscape we are faced with, it is also an open exercise both in conciseness and precision. Please contribute if you see something missing that you feel should have a place here.

FinTechStage and the Fintech District are ecosystem players by design. Our very core stands at building ecosystems and making them thrive so our work for the infographic and research also draws on our networks and overview of the developments in the field. If there’s something that needs further discussion in your opinion, we’re interested!


31


So where are the FinTechs pushing the Frontier? The relationship between the Infographic and the report is clear: after mapping the scenario and the ongoing trends we are bringing those into the actual business by identifying who and where is driving them.

There are several observations that, although not conclusive, are of interest and are underlying the infographic. Some are obvious: the majority of these startups come from countries which already have strong FinTech ecosystems, with the UK by far the strongest, followed by other familiar ones such as the Netherlands and Switzerland, or Israel for advanced tech and security-related solutions. Another confirmation is it takes time to build credibility in the segment and trust is fundamental: most interesting actors have more than 3 years of activity under the belt. Often times they develop partnerships with established players, a trend that picked up significantly in Fintech as a whole. Technology-wise, this part of the market seems to have remained partially immune to buzzwords and most players are calling things with their names, with most of our attention being directed to the opportunities given by data on and from SMEs that was virtually non-existent until just years ago. Finally, the segment needs to move fast and take into account the inherent relevance of the moves of behemoth players such as Ant Financial, Amazon or Alphabet which by themselves can make, break or even create a market.

The security cluster, putting together both cybersecurity, fraud detection, ID and other solutions represents an area that is extremely developed in the consumer space but less so in the direction of SMEs. We are seeing the application of various use cases also to the segment but given the lag of development of SME credit in general it is still to be seen which solutions take the lead in defending it as well.

Putting together infrastructure solutions and platforms of different types might seem a stretch at first but what these businesses have in common and is key is their enabling role. From streamlining processes to assisting in creating new ones, these startups are trying to change how lenders and lendees work.

The reporting and accounting functions are often times the same in SMEs and their importance is often neglected, not out of choice but of lack of time and resources. At the same time the relevance of this function to make financing work is paramount and this is where the solutions in this cluster have found their niche. On one hand they smooth things out for SMEs while on the other they create an opportunity for lenders, in some cases themselves, to tap into an underserved market.

Security

Infrastructure / Platforms

Reporting / Accounting

This cluster is populated by many of the most well-known players in the “European wave”, some of which have a strong consumer focus and are only more recently directing their attention to the SME segment. Neobanks are very different among themselves and cover a wide spectrum of services and approaches to banking, at the same time the reason why they need a cluster for themselves is in their very definition – these are the ones directly taking on traditional banks.


32

Alternative Finance

Alternative finance represents a different method from the traditional financing provided by banks. These methods leverage digital channels to make the process more efficient and open also to private investors.The reasons why Alternative finance is becoming even more important for Startups and SMEs to finance their projects are several. First of all, the products offered by banks do not respond to the requests of companies and the waiting times of credit institutions are longer compared to the speed of alternative finance. Innovative startups and SMEs constantly needs liquidity to boost their growth, but redit institutions are not equipped to provide financing at competitive costs and with the speed necessary to meet the their needs. Alternative financing can take place on an equity or debt basis.

Equity based vs debt financing

EquityEquity based financing refers to pure crowdfunding: it includes all FinTechs which offer, to a group of people, the opportunity to invest in private company through online platforms in return for equity. However, within the alternative finance this method is the most distant from traditional lending for which the recourse to bank debt occurs without an exchange of equity but by resorting precisely to debt instruments. In addition, equity crowdfunding is more suitable for startup and micro enterprises rather than small and medium sized companies. For this reason equity based crowdfunding is not taken into consideration in this research.

Debt & otherDebt financing is the financing through debt instruments or loan. On one hand, debt financing is provided by platforms which offer a digital channel through which a multitude of (or selected) investors has the possibility to finance a project in return for interest. On the other hand, Digital Banks are trying to develop almost-istant loans solution for both B2B and B2C clients. In all cases, the borrower does not transfer equity in exchange for capital, but will pay interest on the loan received.


33

The segment of alternative lending is by far the largest in the field, it encompasses very different players, business models and lending structures. What unifies them is the value proposition of being an alternative to traditional loans, beating them either on speed, terms, user-friendliness or all of the three. The decision to split up the cluster in invoicing and loans & working capital is due to the structural difference given by what the two types of financing are based on. The first on direct evaluation of how likely the payment of invoices is, while the second is linked to the business of the lendee, therefore more similar to traditional bank financing.

Alternative lending / InvoicingInvoicing platforms allow businesses to sell individual invoices to an online community of investors in order to free up cash and offset liquidity problem. Invoicing includes both invoice factoring and invoice discounting, both services providing finance against unpaid approved submitted invoices.

In Fintech, there are two main types source of debt financing:

1. Alternative Lending2. Digital Banks

Marketplace modelIn debt financing most Fintechs operate as pure marketplaces, such that the risk of the funded projects falls entirely on the investors (lenders). On the contrary, in the case of banks or credit intermediaries carries out a “credit” activity and takes on the credit or counterparty risk. It is the main operational difference between the activities carried out by FinTech companies and those of banks, or supervised credit intermediaries.(consob)

Debt FinancingAlternative lending


34

Business model 1. Invoice discountingInvoice Discounting concerns the transfer of commercial invoices of its customers (assigned debtors), through a specialized online platform, by an SME (assignor) to a third party investor (assignee), who advances the balance to the SME net of its remuneration.

The invoice, which is created as a result of a commercial transaction between supplier and company, is purchased through the marketplace by the investor, in advance of the deadline, with a variable discount rate. Investors buy them by immediately paying a deposit generally equal to 80-90% of the nominal value of the credit; when the invoice is settled, the investor collects the countervalue and simultaneously pays the balance to the transferor company.

SME

Invoices

Debtor

Advance invoice

Platform Online

Balance at expiration

Investor


35

2. FactoringFactoring is very similar to invoice discounting business model. The difference consist of a company generally transferring the entire packages of trade receivables, present and future, to a specialized operator, the factor, who purchases them directly and who also takes on the task of administrative management.

While therefore with invoice trading companies can decide based on daily needs which of their invoices to sell and which not, with the factoring contract there is a predetermined commitment. In the factoring contract, the buyer is also unique, while with invoice trading, multiple subjects are competed for the purchase of credits.

In terms of costs, the factor generally applies fixed and variable commissions related to the administrative management carried out, in addition to the financial interest rate. With invoice trading, however, there are only two cost items: the brokerage fee requested by the platform, and the discount applied by the investor.

Alternative Lending / loans & working capitalA working capital loan is a loan that is taken to finance a company’s everyday operations. These loans are not used to buy long-term assets or investments and are, instead, used to provide the working capital that covers a company’s short-term operational needs. Unlike invoicing, the financing takes place without guarantee of an invoice but following different business model.

Business model1. Crowd-lending (or social lending) & P2P lending (or marketplace lending):Crowd-lending consists of financing companies not by purchasing shares but by lending money. Thus, the earnings for investors are predetermined as interest on a loan. Crowdlending is useful for companies that need a lot of funds in a short time.

FinTech companies operating in this area of activity do not provide the loan themselves. Under these conditions, FinTechs are distinguished from banks and credit intermediaries who, typically, act as a contractual counterparty to the borrower. In this way a sort of “collective loan” is created through a digital platform, for the benefit of borrowers. The innovation consists in the possibility of directly concluding a loan agreement through debt or debt securities between third parties, which are clients of the same platform (Consob, 2018).


36

How crowdlending worksInvestment/credit

Supply (investment + yield)

Repayment (depreciation + interests)

Investors

Commissions Commissions

Borrower

Credit

Platform Online

When a crowdlending platform offers the financing in the form of loans to private individuals or adopt a “direct model”, often it is referred to as “P2P lending”. The adoption of the “direct model” means that lenders can individually choose the loans to be granted; in this case, the platform can decide ex-ante which projects to propose on platform, delimiting the scope of investment choices.

In all cases, these forms of crowd-lending - private, business and direct model – share actually the same business model scheme. The Fintech platforms act as marketplace, offering the possibility of obtaining loans in the form of loans directly to potential lenders. These are in turn private investors, companies or institutional investors.

Benefits

For borrower: • Process more transparent, less complex and faster than banking;• Crowdlending campaign give visibility to listed companies and act as a

marketing activity for them;• Management of the entire credit relationship consultancy by the market

platform operator


37

For investors• Interesting ROI;• Low minimum investment threshold;• Management of the entire credit relationship consultancy by the market

platform operator

2. Club dealClubdeal solutions can also be identified as part of the activities carried out by FinTech that focus exclusively (or mainly) on institutional or specifically identified investors, interested in the subscription of debt securities issued by companies proposed by the platform. In this way, electronic markets are created on which it is possible to find funds on maturities which, at the moment, are concentrated on the short term.

Data IntelligenceThe data intelligence cluster is probably the most interesting tech-wise. The segment encompasses various types of business, mostly focused on how to put great amounts of data to use in the lenders’interest. Where they radically differ is the type of data the models are based on and how they are processed.The term Data Intelligence refers to the analysis of various forms of data, structured or not, from heterogeneous sources. The aim of the analysis is to extract information from simple data in a form that can be used by companies. The most interesting attempts and major applications of using Data Intelligence in the lending business are: to determine creditworthiness and to streamline the process.

Business model1. Alternative dataDetermining how likely an individual o business is to default is critical for the whole sector. It can be a complex task even with perfect information, and often the information is incomplete or wrong. New business models have started looking at “alternative data” about potential borrowers. Scoring models can be made more efficient by leveraging alternative data such as social information, invoice data, e-commerce transactions, this type of contextual data enhances credit risk scoring accuracy and consequently reduces cost of financing. In addition, alternative data can be particularly useful for determining the creditworthiness of borrowers without a traditional credit history.

In order to collect customer alternative data, banks and Fintech need to go beyond traditional services and must start providing other tools and solutions


38

that allow them. For example, HSBC launched a Knowledge Center, an online magazine and information center for small businesses which features interviews with thought leaders & inspirational entrepreneurs. Similarly, another solution could be to create or plug-in a social media platform for SMEs to offer immediate answers and support to their queries.In general different types of data are used in relation to the served clients (fig below)

2. Data sharingData sharing is the extreme application of the previous model. The possibility to share data among financial institutions (and Fintechs) truly unlocks the power of credit risk model predictions. As it is clear, the larger the set of data, the greater the accuracy of scoring models. This is what the Japanese Risk Data Bank (RDB), Credit Risk Database (CRD) 2, and the Fichier Bancaire des Entreprises (FIBEN) are respectively doing, the RDB in Japan and the CRD and FIBEN in France (T20 Japan, 2019)13. The collected data is used for portfolio management and loan review, having reportedly contributed to improve the credit risk analysis of banks. In this models the collected data is used for portfolio management and loan review, having reportedly contributed to improve the credit risk analysis of banks. Data sharing and open banking are deeply interrelated with this matter and will play a key role in enabling alternative data.

Alternative Data

Individuals

Social Media

News and Reviews

Web Searches,Personal Data

Corporate Data

GovernmentAgencies Data

Business Processes

Transaction Data

Dualistic view of the world


39

NeobanksThis cluster is populated by many of the most and are only more well-known players in the “European wave”, some of which have a strong consumer focus and recently directing their attention to the SME segment. Neobanks are very different among themselves and cover a wide spectrum of services and approaches to banking, at the same time the reason why they need a cluster for themselves is in their definition – these are the ones directly taking on traditional banks.Born as “digital native” companies, designed for mobile banking, these banks offer their customers a renewed customer experience, with completely digital process. Unlike traditional banks they only exist online. Their lean structure allows to easily manage all the services that a bank offers, from payments to credit cards, from transfers to notices of abnormal transactions on the account, and now also for lending.Types of Digital Banks (source: link foundation)

1. Neo banksIndependent fintech startups positioned as new entrants in the market. Its core business is banking. They do not have their own license, but use the licenses of partner banks to offer financial services fully digital.

2. Challenger BanksIndependent fintech startups positioned as new entrants in the market. Its core business is banking. They are in the process of obtaining banking licenses to openly challenge traditional banks.

3. Corporate Neo BanksNew organizations born as a spin-off of credit institutions belonging to a bank group. The group already have consolidated experience in the sector, and represent a defensive reaction by the incumbents to the challenger Fintechs.

4. Tech BanksOrganizations consisting of large tech-companies, belonging to groups that do not have the banking sector as their core business. They challenge current incumbents by leveraging their technological resources and tons of big data.

5. Retailer BanksOrganizations made up of large organized distribution companies, belonging to groups that do not have the banking sector as their core business. They represent new entrants in the market and challenge incumbents by exploiting their brand and the trust of their customer network as an asset.


40

Business ModelIn all these cases, Digital banks share the same business model of a traditional banks with the difference that they manage online the entire lending process. D. B. employ a fully efficient digital process and a fast and almost automatic underwriting process, which is crucial for small business. Among them, Tech Banks can developed advanced matching engines to leverage new models of risk scoring based on customers big data which are gathered though they core business, different from banking.

Reporting / AccountingCorporate reporting consists of management control techniques and tools that drive companies in day by day operations to pursue long term goals. Reporting include tools for: analysis of critical success factors; determination of the key indicators, the Key Performance Indicators, whose purpose is to report to management how the company is behaving.

The accounting process includes summarizing, analyzing, and reporting financial transactions of a business to oversight agencies, regulators, and tax collection entities. The financial statements used in accounting summarize over an accounting period the company’s operations, financial position, and cash flows.

The reporting and accounting functions are often times the same in SMEs and their importance is often neglected, not out of choice but of lack of time and resources. At the same time the relevance of this function to make financing work is paramount and this is where the solutions in this cluster have found their niche. On one hand they smooth things out for SMEs while on the other they create an opportunity for lenders, in some cases themselves, to tap into an underserved market.

Accounting and reporting can play a relevant role in supporting SMEs development by decreasing the information asymmetry problem. If lenders have transparent information they can better assess the credit risk of the borrower. In addition, accounting and reporting is a powerful tool for owners and/or managers of SMEs, provided they have the necessary skills to understand the information, to make adequate business decisions in terms of allocation of resources, determining the amount of financing required.

Business ModelCompanies in this category develop apps and software to carry out accounting and reporting activities, they usually offer to their business clients through a Software-as-a-service model.


41

Infrastructure / Platforms The introduction of the PSD2 has introduced a new set of rules to allow third party operators to access certain information relating to customers and their operations. The regulatory changes, PSD2 first, and the growing diffusion of technologies, such API, imply the opening of the banking sector which allow new operators to enter the market with digital services and limited IT investments.

This category groups toghether infrastructure solutions and platforms of different types. What they have in common is their enabling role: from streamlining processes to assist in creating new ones, these companies can offer a range of services across the entire banking sector and inevitably are trying to change how lenders and lendees work.

In particular, companies are experiencing the marketplace model in which customers and business can use a single interface to access products and services offered by a multitude of operators. This platform model offers customers a complete series of services, designed with a holistic approach to their needs supported by the increasingly widespread and effective use of big data analytics and AI.

Business model

Banking-as-a-service(Baas)Baas refers to the provision of financial services in cloud. An API (application programming interface) is the key element in the implementation of a solid Banking as a service strategy. APIs are scalable, reusable and secure interfaces, useful for data exchange and allowing different software components to communicate with each other. In the past, banks tended to purchase software for digital financial services and install it on internal legacy systems.Banking as a Service aims to offer open APIs, and therefore to create an environment that facilitates the introduction of plug-and-play applications. Companies can easily combine different product offerings in order to meet the specific needs of each of their customers.

The banking sector will therefore have to get used to the presence of different platform and marketplace business models, therefore based on collaboration and co-opetition mechanisms, where it is possible to offer personalized services also through external providers. Figure below illustrates how:


42

In turn, the Banking-as-a-Service (BaaS) can be divided in four sub-categories (fig below):

Core Banking Platform

Banking as a Service (BaaS)

Lending as a Service (LaaS)

Banking as a Service (BaaS)End-to-end process ensuring the overall execution of a financial service provided digitally. Service is available on demand and is carried out within a set time-frame.

Open Banking Eco-SystemNew entrants from outside the traditional banking system who don’t build a complete

value chain, they instead leverage component parts, through a platform

based approach. They see and imagine new and rapid value creation opportunities, not

products and distribution channel.

Core BankingSystem of record processing all daily

transactions. Includes deposit, loanand credit-processing capabilities, withinterfaces to general ledger systems

and reporting tools.

Lending as a Service (LaaS)Specialised multi-tenant software platforms designed to support corporate loan originations and managment. Dedicated cross-function components including API connectors, Credit analytics, management, User & account management, Data transformation & mapping, Reports and Dashboards.

Partner TPPs


43

Security Fintech digital companies and the shift of traditional lenders to digital channel exhibits companies to cyber risk. Second, massive data breaches are throwing enormous amounts of personal financial data out on the dark web.

The security cluster, putting together both cybersecurity, fraud detection, ID Management, KYC and Communication security. represents an area that is extremely developed in the consumer space but less so in the direction of SMEs. We are seeing the application of various use cases also to the segment but given the lag of development of SME credit in general it is still to be seen which solutions take the lead in defending it as well.

Business Area

Fraud DetectionFraud can never be fully prevented; therefore, a highly effective fraud detection system must be in place to detect frauds as they occur. In the same way that the fraud prevention system requires preventive controls, the fraud detection system requires detective controls. Detective controls are generally matched with identified risks, and they tend to be clandestine. In some cases, it may be more cost effective to implement controls to detect rather than prevent fraud.

ID ManagementIdentity Management (IM) refers to integrated systems of technologies, policies and procedures that allow organizations to facilitate and control user access to critical applications and data, while simultaneously protecting personal data from unauthorized access.

KYCThe expression know your customer means a recognition process used by companies to verify the identity of their customers and evaluate potential risks or illegal intentions in the relationship with the customer.The term often refers to banking regulations and anti-money laundering regulations governing these activities. The customer recognition processes also concern companies of other types and sizes, with the aim of ensuring anti-corruption/fraud compliance for their agents, consultants, distributors.

Communication SecurityCommunications security is the discipline of preventing unauthorized interceptors from accessing telecommunications in an intelligible form, while still delivering content to the intended recipients.Privacy companies offer global and multi-platform encrypted communications service in the form of voice calls, video calls, instant messaging, email services etc.

Partner TPPs


4444

3.13.2 Credit Frontier geographic distribution

UK

NO

IE

US

ES

FR

BE

CHIT

DE

EE

IL

FI

SE

NL

DK


4545

3.13.2 Credit Frontier geographic distribution

UK

NO

IE

US

ES

FR

BE

CHIT

DE

EE

IL

FI

SE

NL

DK


46

Closing remarks


46


47

The work underlying this research has encompassed a few months of work and we are already noticing emerging aspects that we would like to stress and keep working on. We are aware though, that a research paper on FinTech is by nature incomplete: it suffices to look at VC investments data for 2019 to grasp how fast it is moving with more than 5B€ in the first half of 2019.15

It is in this very sense that we want to focus our attention on one key takeaway from the research: the SME segment has been touched only recently by the wave of changes in the financial sector as a whole but given the importance of SMEs for any economy, and for the European especially, the consequences will be pivotal. The acceleration is evident and the market opportunity is vast, as is the chance for the sector to become more efficient and competitive. For this reason, we deem fundamental the role of entrepreneurs and policymakers alike in a genuine ecosystem effort that can create strong foundations for future developments.

The role of up and comers, illimity included, is that of reframing existing problems and showing a new approach - one that can push the credit frontier further.


47

15 Dealroom.co, 2019.

APPENDIX


48


49

Expert interviews

BioJessica AlfaroConsultant with the IFC’s SME Finance ForumWorld Bank Group

Jessica has over 10 years’ experience working with MSMEs and is an expert in lending, entrepreneurship and finance. Based in Madrid, she is currently a consultant with the World Bank Group and a Visiting Lecturer in the School of Economics and Business

Administration at the University of Navarra in Pamplona, Spain. Previously, she has led and backstopped onsite technical needs assessments at banks in Africa and Asia, sourced and managed financial institution relationships for an international network of small business banks, and organized in-person and elearning training opportunities for bankers across a number of emerging markets as a Manager at CapitalPlus Exchange. She has been an Associate Director of the Illinois Small Business Development Center at the University of Illinois at Chicago, a Senior Loan Officer at ACCION Chicago and on the MSME lending team at Ithala Development Finance Corporation in Durban, South Africa. Committed to economic and financial inclusion, she has served on community Boards and committees, and volunteered with organizations that focus on improving access to finance for consumers and business owners.

Below you will find the integral texts of the various interviews we have conducted during our research, their inputs have been precious in directing it

and we want to thank again all interviewees for their contribution.

All the views and opinions expressed here and redacted in the boxes in the research are their own and don’t represent necessarily those of the parties

involved in the production of this paper.

Interviewing: Jessica Alfaro (J)Interviewer: Flávio Proieti (F)

1)F: From your institutional perspective, what has been the most evident change brought about in the post-crisis years for SME financing?


50

J: The financial crisis caused SME lending to dry up even more and, in some markets, small business loans were practically non-existent after the crisis. It’s been a slow road to recovery in small business lending, and the SME funding gap still exists, especially in the traditional lending market. One of the biggest areas of recovery to help SME has been in the alternative lending market, utilizing technology and data to get around historical SME lending obstacles of creditworthiness and profitability from more traditional lenders.2)F: How have you seen the wider SME landscape change through and thanks to technology in the last years?

J: Many more lending options for SMEs, which could potentially be faster and cheaper, especially growth in peer-to-peer lending.

3)F: If you could list them, which would be the 3 most pressing issues for SMEs looking for financing.

J: Issues both on supply and demand side: Supply: some SME segments still struggle to get funding, especially the smallest businesses, and startups or new firms.Demand: many SMEs don’t know about all the financing options available to then or are even hesitant to apply because of a perceived high cost, or assumption that they will be rejected.

4)F: Given your experience in various developing economies and the incredible leapfrogging we’ve seen in some instances, which levers would you use in developed contexts such as the European one to foster innovation in SME finance?

J: Moving to mobile/digital banking and moving away, more quickly, from expensive, branch banking with incumbent banks and traditional lenders still with the majority of the market share in SME finance

5)F: Unlikely-To-Pay loans are an issue of great interest from a European perspective, deeply intertwined with creditworthiness in lending. How much shake-up do you see brought about by technology in this segment for the SMEs on your radar

J: New credit scoring models, and alternative lending models using access to increased amounts of data are important, but have yet to significantly scale up or replace more conventional cash flow-based scoring models.


51

Matthew GamserCEO, IFC’s SME Finance Forum

Matthew Gamser is the CEO of the SME Finance Forum, a center for knowledge exchange, good practice promotion and networking, managed by the International Finance Corporation (IFC) for the G-20

countries’ Global Partnership for Financial Inclusion. He has over 35 years’ experience in private enterprise and financial sector development, with an emphasis on emerging markets. He has worked with commercial banks and non-bank financial institutions in broadening and deepening services to households and enterprises previously lacking formal finance. He also collaborated with governments and policy-makers on improving the enabling environment and infrastructure for financial sector development, with a focus on financial inclusion and on the role of the financial sector in mitigating the effects of climate change. He helped to develop a benchmarking system for SME banking services, and other tools and techniques for building capacity in financial institutions and financial sector regulators. He also helped introduce mobile banking/electronic payments systems as a new business area. He is working for IFC for over 11 years, ledding IFC’s advisory work in increasing access to financial services in the East Asia and Pacific region.

Interviewing: Matthew Gamser (M)Interviewer: Flávio Proietti (F)

1)F: What was brought about in the post crisis years for SME financing?

M: SMEs were always a difficult field for bankers and other conventional financiers and the crisis, on the one hand made things even harder for the conventional financial approaches, because banks suddenly had less capital. On the other hand, because of technology we are finding new ways to finance SMEs, that, with small exceptions, really couldn’t do before and it’s both bad news and good news. I mean most of these institutions that are advancing these alternative ways are the most aggressive ones: the newcomers, the non banks, the neobanks, the peer to peer lenders, whatever you want to call them, and they are very different. Basically what bankers would do beforehand. The whole motto was “The SME has to come to me, they have to give me the information and the security, in the form of collateral I require, to satisfy my risk, and appetite, and if they can do that I can finance them, and if they can’t – I’ll send them away”. That is not the way things are done now at the cutting

Bio


52

edge. At the cutting edge, you also have the data, you are not starting from credit, you are starting from payments, transactions and other types of B2B transactions, in particular. You’re acquiring that data, and you’re proactively assessing what your clients can be and what you can do for them. You’re not telling the entrepreneur - “This is what you need to do or I can’t help you,’’ you’re saying “Hi I’ve identified you in my mix as an entrepreneur that I can help and here’s what I can offer you” and then not only you monitor through the lifecycle in a way that conventional bankers didn’t do (unless you were late with a payment). So there is a fundamental change going on, in the way that we can finance SMEs, and still most SMEs are stuck in the old system which is why they’re such a huge financing problem for SMEs by all the surveys of the community around, and why several countries in Europe despite the fact that we’ve been in a growth mode for a number of years now, still haven’t got their SMEs credit back to pre-crisis levels. There are some people that would disagree with me, and they would say that the reason that those SMEs aren’t getting financing is just that there just isn’t enough demand and there was too much financing for SMEs before. I don’t believe that. I don’t think the statistics can back that up, and I’m certain the SMEs Association don’t believe that argument. From the European bankers and regulators.

2)F: This is also reflected in how we set up the research trying to distinguish traditional players and new players in this very point and in the very approach to financing. And this is the reason why we will also be interviewing some banks and new players.

M: Funding Circle have a Risk Manager that spent a lot of years in Barclays and other banks, and they will tell you what is different about working in Funding Circle from where he did before. Some of institutions, they’re really quants, they were never really bankers. Some others, have risk managers or bankers that are questioning the way they used to do things. You wanna be careful talking to the quants, in many cases because they are really young, never been through a cycle, and they think they are very cleaver, and they may or may not be, when things change. But people like Funding Circle, where their Chief Risk Officer, happens to been many years on the other side of the fence, when he’s making these changes, he knows what he is doing and why, and he understands what the credential requirements are. If you’re still a conventional banker, It’s not just gonna flowed all of them. For example, not related with SME finance, but the previous incident with Revolut for example where they were just way too fast at KYC, because they were all very clever but they didn’t have enough background in banking and didn’t know how important it was to stick to some of these rules. And they got in big trouble.


53

The whole field is changing. First of all, the problem was and still remains information, but information is changing. SMEs are becoming more and more digital. Digital in their payments, commercial activities - it’s not purely cash converted to digital money, there is also transactions that used to be on paper and are hard to track or with things that were solid and hard to track. Now these transactions are themselves digital thought IoT, so everything is becoming digitalized and it’s forcing a completely mindset change in how you go about this. And I can’t state that any more strongly than, it really is a complete reversal, since we used to try to beg and square, and if we could send people out to the markets, to meet the clients directly, kick the tie and then leave with credit once we got to know them a bit, try to make some money and then build from there . Because in most countries, even if there was a credit bureau, we didn’t have that much info on these SMEs. The best thing we could know is to learn about their entrepreneurs. If they paid their bills on time, which isn’t enough. Now we can know so much more. We still use, (if there are) Credit Bureau. There is good infrastructure, it doesn’t replace it, but there are so much more, that if we’re clever, we can utilize. That’s how the Kabbages, and the Funding Circles have been developing. If you talk, for example, with the American Alternative Lenders, they’ll also give you a very specific example of why people are also finally realizing why consumer and SME lending are different. Consumer lending is sort of like a straight FICO score, based on your personal finance leverage: how much you owe, and how regularly you paid. That doesn’t work for new enterprises, and new enterprises are really important, because they are what we need to create, to create jobs. When enterprises are new and they succeed, they tend to grow faster than enterprises that are around for a long time, but the problem is all alternative financiers like Kabbage, Ondeck and Funding Circle say well: “What does the average entrepreneur do?”. They are running a growth oriented company. Initially, nobody is gonna give in money – just friends, family and fools, so they get all these money from their friends and family and then they max out their personal credit cards, to get as much liquidity they can. Which from a conventional scoring point of view, would drive their credit score way down. But it doesn’t necessary tell you which one are good bets and which aren’t. What you need to look is how they’re order book look like. That used to be impossible, because by the time you could learn their order book, which would require physical interaction, you spent more than what you’re going make on this client. Today you can assessthat order book electronically and it will tell you much more than the FICO score. Even FICO is doing this. For the work they’re doing to advise people on SME lending, they’re not just sticking to what they used to use, they’re using other things. It is recognizing this and then understanding the credit, managing through the lifecycle with a very close monitoring without having to have a lot of physical presence.This is where we are going. The ultimate practitioner of this are people like Ant Financial, MYbank - which


54

is the entreprise part of ANT Financial, Alibaba and AliPay and they’re modo is 3-1-0: 3 minutes to a decision, 1 minute to deliver to funds and 0 physical interaction necessary. They will know how many models they are running, and how they are continuously re-scoring their customer base, which is in the tens of millions of enterprises in China right now. That’s where we’re headed. Not everybody can capture as much, and as complete information as they can, but as ecosystems to use as - FinTechStage - “to build ecosystems”, where not only ecosystems, but fintechs can grow and thrive and its ecosystems; where digital can replace analog in business, which is the most important ecosystem of all, then you have an open set of doors.


55

Geert GladdinesPolicy Advisor Business Services & SME SpecialistNVB - Dutch Banking Association Geert Gladdines is Policy Advisor at the Dutch Banking Association, with a specific focus on Business Finance. Geert is working on topics related to Access to Finance of Small and Medium Sized Enterprises, Responsible

Business Lending and the development of the Dutch financial ecosystem for business clients.

Interviewing: Geert Gladdines (G)Interviewer: Flávio Proietti (F)

1)F: The acceleration of innovation in SME finance of the last few years has been impressive, where would you draw your mark for the “game-changer event”, your “aha” moment?

G: The tipping point for alternative finance in the Netherlands has been end 2017/start 2018. From this moment, previously new kinds of finance, started growing rapidly. This applies to finance types such as leasing, factoring and crowdfunding, but also to platforms that are organizing the origination of loans, while being backed by a larger more traditional player. In this category you will find New10 (ABN AMRO), Funding Options (ING), Rabo and Crowd (Rabobank) and Neos (KKR), and initiatives like the Subordinated Loan Fund, making a link between SMEs and institutional investors (pension funds).

Around this period, the mindset of SMEs also changed. Previously they were oriented - virtually solely - on bank financing. Starting 2018, it is becoming ‘normal’ for a business to not only ask a bank for a quote, but also orient with new kinds of financing. Before, this could be seen as a sign of weakness (if bank loan is not available, you are not credit worthy), while starting 2018, the use (and mixing of) different kinds of financing becomes a smart, diversified approach to financing a business. The mixing of different kinds of financing also enables businesses to optimize the kind of financing. For instance: Using cheaper debt for real estate, using leasing for machines, crowdfunding for marketing and (expensive) factoring for delayed invoices.

The uptake of combined/staple finance has been slow, but since the entry to the alternative lending market of traditional players (like New 10 from ABN) and the growth of ‘newly old’ players, such as Funding Circle and Spotcap, it has become normal for different kind of finance providers to jointly finance SMEs on

Bio


56

the same deal. A few years ago, a structured deal was only available for large tickets, however, with new providers and technology, SMEs are increasingly sitting in the driver seat for structuring their deals also for smaller tickets.

(non exhaustive) List of important events around 2018:

• April 2015: Introduction of Subordinated Loan Fund (ALF, managed by Aegon Asset Management) and Company Lending Fund (BLF, managed by Robeco)

• September 2017: ABN AMRO launches New10 • January 2018: Launch of Foundation Alternative SME Finance. • June 2018: ING partners with Funding Options • July 2018: Dutch banks publish Code of Conduct, including principes on

cooperation with non-bank finance providers. • August 2018: NEOS introduces direct lending option for medium sized SMEs. • December 2018: Rabobank launches Rabo and Crowd, together with

investment platform Nxchange. • April 2018: NPEX receives Multilateral Trading Facility licence under MIFID II. • March 2019: Dutch State gives financial guarantee to Qredits until 2040:

Pre 2018: Of course the market was already evolving and non-banking players started on the Dutch market. Examples are Spotcap in 2015, NPEX in 2008, Qredits in 2009. They were however not truly ‘adopted’ by the market.

2)F: Do you see a rapprochement between corporate and SME segments thanks to the development in technology, or vice-versa?

G: On the one hand: No. The value chains are becoming increasingly disentangled, with different financing solutions for different segments. Providers are specializing, tailoring their products to specific segments and financing needs. This also means that certain providers are only providing balance sheet services (as part of a traditional core banking service), while other providers are basically only an intermediary sales channel, leaning on funding from pension funds or banks.

On the other hand:Yes. Previous products that are too complex, or based on manual checks, are becoming available to smaller businesses, because technology enables banks or alt-fi (alternative finance) players to better judge the specificities of an individual business.

Technology enables businesses to provide better insights in their credit


57

worthiness and day-to-day operations. This means that handling costs go down. Potentially opening up new parts of the market for different finance providers.

The same is happening between businesses themselves: Between companies, complex structures of financing options emerge, where large corporations are financing their suppliers, based on the detailed insights they get of the production process of these suppliers.

3)F: We often hear about how startups have incredible advantages over traditionalplayers but we rarely talk about the opposite, what do you think in terms of strengths and weaknesses of their model?

G: Weakness: There is a risk that Startup Fintech providers are so specialized, they can only serve the market on a specific moment in time, under specific conditions. Their business model does not always allow to provide finance under lower rates or in an economic downturn. For instance: if an SME obtains a loan for 8% with an online platform, based partly on crowdfunding and (institutional) investors who expect a 6% ROI, there is not much room for NPLs. While ‘traditional’ players attract savings and need to be prudent, the new kind of providers obtain funding ‘case by case’. The latter makes them in a way less vulnerable for large economic/financial shocks, because they simply stop providing new loans. However, for the market as a whole and the financial ecosystem for SMEs, it is not healthy if large parts of the supply side of the market are suddenly retracting.

Strengths: The ‘usual’: No legacy, new software, investors exactly suited to the kind of services of a fintech, lower licencing requirements. However: when fintechs grow, they notice that a larger, more complex license (and responsibility), also gives them a marketing advantage (thrust with SME clients grows) and creates certain barriers to competitors.

4)F: If you could list them, which would be the 3 most pressing issues for SMEs looking for financing?

G: 1) Financing intangibles, like software and R&D or Financing human capital. 2) Providing adequate real time data about their financial situation and operations. 3) Knowledge of structuring a finance application, especially when looking for non-bank or a combined financing option.


58

5)F: On the other side, which would be the 3 for traditional players such as banks with regards to a new era for the segment?

G: 1) enabling real time credit checks and loan origination2) enabling unsecured loans (as compared to traditional bank loans that are backed by a mortgage or other kind of securities) to SMEs by checking their creditworthiness based on real time data and predictions3) making sure SMEs enjoy a seamless cooperation between banks and non-banks.

6)F: One of the radical developments going on in the banking sector is about data and Creditworthiness, where do you see this going for SMEs specifically? Which areas do you think will give the winning hand to the players?

G: Trust is essential. Sharing of data, especially sensitive data about the financial health of a business, only works if the receiver of data can guarantee security. This applies to ownership of data as well. If a business gives data, it wants to have the certainty that it is not stored forever. In a way, company data is given away as a lease. The company should be able to take back the information when a service of a finance provider is no longer necessary. This sounds counter intuitive, because finance providers want to build up both (semi-anonymous) data lakes and long term individual company profiles. However, in the long run, banks or altfi finance providers need to become digital vaults and earn and retain the right to provide services for the time they have the data in their vault.

7)F: Last but not least, if we had to ask you what is the most interesting aspect of being in the midst of the fintech r-evolution for SMEs, what would you point to?

G: The financial ecosystem for SMEs becomes bigger, enabling business to undertake plans they would not be able to do without new financial options, driven by technology. The market gets bigger and it is not a zero sum game.


59

Paolo SironiAuthor and IBM FinTech Thought Leader Paolo is an author and FinTech thought leader and an elected member of the IBM Industry Academy, Watson Financial Services. He represents IBM worldwide and in this capacity, he advises C-level financial institutions

and mentors entrepreneurs on a host of issues related to business model transformation in the age of digital banking. Previously to IBM (2012), he held senior roles in quantitative risk management and investment banking, and founded a startup that offered innovative investment analytics solutions to wealth management firms. He is a recognized bestselling author on books about portfolio management and FinTech innovation, maintains a comprehensive personal website and social media, and speaks regularly to the media and industry leaders internationally about innovation - as an industry influencer himself. He is also a visiting professor on Fintech.

Interviewing: Paolo Sironi (P)Interviewer: Flávio Proietti (F)

1)F. From your perspective, what has been the most evident change brought about in the post-crisis years for SME financing?

P: The GFC has generated a perfect storm on SMEs with long lasting consequences, following the re-allocation of banks' credit portfolios in the western world, particularly in Europe. Credit de-risking and restructuring of NPL portfolios have adversely reinforced the pro-cyclical nature of Basel 2 capital accords, hitting particularly hard on SMEs at a time when the economic outlook deteriorated fast. This has persisted notwithstanding interest rates have never been so favourable for businesses, thanks to the intervention of the Central Banks.

2)F: How have you seen the wider SME landscape change through and thanks to technology in the last years?

P: SME has been the neglected segment in the starting years of the fintech revolution, although the nature of SME clients makes them more receptive to PULL-oriented digital propositions (demand driven) than the PUSH-oriented general public (offer-driven). The reason is due to the imperfect vision of Silicon Valley and their cohort of Venture Capitalists looking for volume instead of

Bio


60

value, misunderstanding the nature of banking businesses thus looking for easy wins on homogeneous markets. The SME world is clearly more fragmented and more inclined to value-based propositions than the client-base of personal finance. However, we have finally observed a new breath of fintech coming's to market with solutions for small businesses in the last couple of years.

3)F: If you could list them, which would be the 3 most pressing issues for SMEs looking for financing?

P: First of all, SMEs need faster time-to-market of their solutions due to the acceleration of market trends: they need banking to speed up digitally while financing analog processes are often lengthy and bureaucratic. Second, SMEs need to simplify their financing along their supply-chain: they need banking to become more digitally contextualised inside their ecosystems. Third, SMEs need to be put back in control of their credit ratings to grant them positive interaction with lending propositions: they need digital transparency of every step of the decision-making processes in order to address pain-points and support their business model propositions with more clarity.

4)F: On the other side, which would be the 3 for traditional industry players, such as banks, with regards to a new era for the segment?

P: First of all, banks don't have a lot of capital notwithstanding the long period of industry restructuring, especially in Europe. Second, banks cannot sufficiently remunerate share-holder value after the price for risk due to extremely low interest rates (negative in core EU countries). Third, banks need to provide more intermediation-based propositions based on added-value advisory services to resolve the compression of interest rate margins. However, they have a hard time in succeeding by plugging in digital solutions because the effort requires a change of their revenue generation mechanism corresponding to a transformation of their business model. Legacy leadership is harder to break than mending legacy systems.

5)F: As an influential author you also have the opportunity to explore untapped contexts, if you were to bring back to Europe and Italy 2 key insights from SME-focused FinTechs that you’ve seen which would they be?

P: I think SMEs grant fintech the right playground to learn how to mix banking and non-banking services by contextualising the first inside the second. This is to me the way forward to build consistent digital engagements. Those fintech building ecosystem plays are also well positioned, because SMEs are in the


61

middle of a battlefield: fighting to service clients on one side, fighting to optimise their supply-side relationships on the other side.

6)F: What are the most radical innovations from your privileged perspective in IBM that you’ve seen land on the market but are still commercially untapped?

P: 5G is the most significant innovation because it will provide SME's with a quantum leap of the cloud-based digital infrastructure needed to open up new business models which are not yet conceived. Artificial Intelligence is also commercially untapped in the western world, since challenger banks have not learned yet how to build advisory open banking platforms that deliver real value to client. AI could help them to unlock this value.

7)F: Which do you envisage as a banks' biggest challenge for the future? How do they have to change their model and approach?

P: The traditional revenue-generating mechanisms of financial institutions lay on two economic pillars: interest rate margins and intermediation margins. Unfortunately, existing business models based on the separation of these pillars do not reconcile with prevailing economic and regulatory conditions. With regard to interest rate margins, there is no share-holder value after the price for credit risk due to low interest rates, lack of banking capital, insufficient market capitalisation. With regard to intermediation margins, payments are becoming digital and instantaneous reducing transactional revenues. Investment management is becoming more transparent (particularly in Europe) and very competitive thanks to hybrid digital solutions (especially in US), which has ignited a race to zero prices. As such, banks are not anymore a mechanism for the transmission of monetary policies (especially with the emergence of stable coins), thus adding investment management and insurance services on top of their operations. The only way out of their business model conundrum is to learn how to rebuild the banking and insurance charter holistically, tearing down operational and regulatory pillars across business units transforming the industry into an advisory mechanism for SMEs and family. This way banks can generate fee-based value, helping clients to optimise their interaction inside their ecosystem made of needs and real-world problems. They will plug lending inside financial planning frameworks because real personalisation comes from understanding liabilities of SMEs and families, not their assets.This outcome will be the role of what I branded "open banking advisory platforms" and I describe relentlessly in my literature and fintech though leadership. There will be no other unicorn.


62

Kathryn PetraliaCo-Founder & Kabbagehead, Kabbage Kathryn Petralia the Co-Founder, COO and Kabbagehead at Kabbage, a data and technology company offering automated cash flow solutions, whose goal is to simplify the way small business access the capital and services

they need to build lasting businesses. Kabbage was founded by herself, Marc Gorlin and Rob Frohwein in 2011, and by 2015 was extended to large banks as Santander. She is an American entrepreneur addressed by Forbes as the 98th most powerful woman in the world. She was also elected by TechCrunch as “women succeeding in tech”. Kathryn is a leader with more than 20 years experience across credit, payments and lending.

Interviewing: Kathryn Petralia (K)Interviewer: Flávio Proietti (F)

1)F: As an introductory question, you are a technology intensive company, and what we are interested in is how your approach differs from traditional players (such as banks). What would you point out as the major difference of approach in the analysis of a potential customer - a lendee - from Kabbage?

K: I have to actually take a step back before I enter that question because there is this presumption that banks want to serve the small businesses and that they used to serve small businesses and they stopped during the financial crisis. There’s a lot of different assumptions that are made about banks and small businesses overall, but I think it’s important to talk about the small business landscape first. So in the US there are 32 million small businesses, 90% of them have fewer than 20 employees. In Kabbage’s portfolio 80% of our customers have fewer than 10 employees and these are customers that banks have actually never served and have a hard time serving because they’re so small. It costs a lot to a bank, because it is the same process for a bank to underwrite, a business looking for 50k dollars as a business looking for 5k dollars, and it’s not economically viable or scalable for them to serve very small businesses. Even credit unions and community banks have the same challenge. So the reason why we are able to serve the segment - and if you think about it (it’s called SMB in the US and SME abroad), most technology providers are trying to serve the M’s, they’re not trying to serve the S’s and the S’s represent the preponderant of small businesses. I think it’s important to lay that groundwork to explain who

Bio


63

we are serving, and why it is difficult to serve them and how we are able to do it. We are actually answering the same questions that banks are answering about the customers base firm, the difference is - we are able to interrogate the data differently and more efficiently because our customers give us real time access to data from providers they use to run their business. It could their bank account, accounting platforms, payment processing data, social data, shipping data, web and analytics data - all these different categories that our customers share with us, we use to understand in real time how their businesses are performing and help us predict their business’ performance in the future. What’s also really important is that we stay connected to that data so that we are able to offer unique products to our customers - we can give them a line of credit and that’s unusual in small business lending because it’s difficult to manage the ongoing liability of what is it compared to larger businesses - it is indeed, a very volatile community of businesses.

2)F: How do you manage applications - since you have a totally different approach to data, including from banks nowadays? Does this different approach to data show you a very relevant bottleneck where your system rejects most applications or you see this as a normally distributed application phase?

K: Businesses who apply at Kabbage for a loan or for a line of credit - businesses that are generating 5k dollars/ month in revenue (which is not a lot) - we will approve 80% of them, which is an incredibly high approval rate, specially for a business generated potentially as little as a 5k/month in revenue.

3)F: Is Kabbage approving all those businesses that the traditional narrative of a bank would not fall through.

K: That is correct.

4)F: Am I correct to assume that your job is countering this argument from banks (which it’s not economically viable for them), the so-called traditional narrative: “the smaller the business, the riskier” - meaning if you couldn’t or wouldn’t secure a bank loan than automatically you’re a risky business, and what Kabbage is doing (as well as other startup lenders) is countering this argument through technology. And if so, how would you explain this counter- argument to a non-finance professional.

K: That is a correct assumption. I believe the challenge is twofold, because it’s hard to find small business owners, because these customers are not simply congregating in common places. Tracking them is hard, and what happens


64

with banks, is that the customers are walking in the door. From a credit risk perspective you run into the issue of adverse selection which means that the people who most need the credit are the highest risk and small businesses are incredibly volatile. That is the way they operate, but what’s really important to mention, is if they had the ability to manage cash flow that will actually solve that problem for businesses, so they become less volatile. The reason, I would argue, that there is so much volatility in small businesses performance success is that they don’t have access to the tools that large businesses have. And they’re never going to or I don’t even think it should be the goal. Not every small business should be a multi billion dollar global enterprise. Some businesses maybe just simply care about taking care of animals, or baking cakes, or finishing hardwood floors and I believe that’s an important distinction. These are the small businesses that drive our economy and they are vital to our economic performance as a global community.

5)F: There’s a lot of discussion about AI, Machine Learning, data, and in the news is often shared that most european tech firms, currently working with AI, aren’t really doing so. This makes us reflect on how a different approach doesn’t necessarily require huge tools, implementation of big automation systems, and implementation of true AI, and at the same time the advances that have been made since 2009 (when Kabbage was founded), are impressive, and I would like to understand how these processes influenced your structure.

K: I want to start responding that mention to the european tech firms is not only limited to Europe since almost no tech companies use AI. People don’t know what it is, they’re conflating machine learning, and other advanced analytics techniques into AI, and they’re very different things. I believe the only place in financial services - especially when it comes to highly regulated products - where AI would make sense is on user experience. I think it would be very hard to let the machines learn underwriting without a human being part of that process - and simply because there is so much potential for a disparate impact, which is a really important and critical issue when it comes to access to financial services. Kabbage has used advanced techniques since the very beginning - machine learning has been part of our work since 2013 or so. It is really early but to be honest machine learning has been around for a long time, it’s just been used in other industries.

6)F: We want to make sure to clarify - on the SME side - there is no misunderstanding in the application of AI, as it appears somehow from several articles and reports, that AI is a magic wand to solve any problem and there are simply


65

some spaces where it wouldn’t really make sense to have it, and regulatory speaking it wouldn’t even be possible.

K: It AI was as pervasive as it is suggested by the tech community, I am pretty sure we would have a cure to cancer or something that innovative already.

7)F: Regarding some advanced techniques, there is also some hype on RPA - Robotic Process Automation, basically all automation that are not AI driven (programmed through a specific path) which could be of great use for some SMEs for managing the type of data they’re sharing, and how they’re collected upon themselves. What is your perspective on this, do you think you would/ do already evangelize your customers on creating some processes, systems and automations that would allow them to be better, data-savvy and therefore advancing their understanding of their businesses.

K: So, what do we tell our customers? There is a new ruling being proposed in the US that requires that companies that deliver data content to their customers, need to tell them and let them opt out of being delivered content that was generated by an algorithm. The question is interesting, because all of our customers are already opting in, to share data with us that they know is going to be used in a model that is going to determine the line credit for which they qualify or approve them entirely. At Kabbage we do more than lending, we allow our customers to process payments (like PayPal and how they started), and we will be adding a new product in the course of the next 6 months. We round out cash management tools for small businesses and we’re advocating more about it. With our customers to a smaller degree, but from a policy perspective is more on access to data. The challenge is a lot of businesses and consumers, which creates a lot of data, are not able to claim ownership, and so they are unable to share that information with a third party, and banking is the biggest example. In Europe, PSD2 solves for this - you haven’t yet seen the velocity and drew put that you might expect of the innovation because it takes time, because it’s banking - but there is an idea that you can work with. It is really hard to change bank accounts because you have to manually move all these processes and transactions into a new institution. That puts a stranglehold on the customer and the customer doesn’t really have the right to move from one position to another, which is very difficult to do. In sum, open data and access to data, it’s a big forwage we strongly advocate.Everything we do is a model, everything our customers see it’s the result of a model and they know that because they’re willingly giving in the data. The difference is that with YouTube for example, people don’t realize that the next video that is suggested to them, is suggested for reasons that may not be because it’s something that the customer would like to watch, but because it’s


66

going to generate more revenue for YouTube itself.

8)F: There are steps forward and certainly more assess and more manageability of customer data would be a great step forward, but what else do you see, also regarding other fields and industries - that in terms of data and technology - are trickling down the financial sector. Besides machine learning that has been around for a while just took some time to crush the doors of financial services, do you see something else?

K: I would argue that, outside of national security agencies globally, financial services companies started using machine learning tools before lots of other companies did, only because everything about financial services is data. It’s all 1s and 0s, so it’s actually the easiest place to apply technology when it comes to decision making because it’s all very objective - assuming there is not a human involved - it’s very easy to do that. I worked in a company in the 90s that was using machine learning models to build/make credit decisions, so I’m not sure we are necessarily the last to adopt new technologies or to adopt model development capabilities - I think there are probably parts of it: a great example is that technology came to small business lending very late, 10- 15 years after it came to consumer lending, and the reason for that, it’s because it’s hard to get the data, since is not necessarily a manual process because its possible to interrogate that data in an automated way.

I personally was not at an SME before we started Kabbage, I was more on the consumer side from the fintech perspective. There are two big reasons for that late adoption, one of is hard to find those customers, and the second reason is the data is very dispersed, across lots of different places, so Kabbage was really the first one to automate lending for SMEs, and most of it, by the way, was out of ignorance. What I mean by that, is that my background was in consumer lending, that’s what automated is in the 90s. It not even occurred to me when we started Kabbage, we weren’t solving a problem like “Oh we know that nobody is automating small business lending” I didn’t know a lot about small business lending, I just knew that businesses need capital, consumers need to borrow for various things. We started out making the most of Ebay businesses, and the reason we did that is because Ebay had an API, they gave real time access to real interesting and unique data about businesses selling on Ebay - seller and transactional amount of data - and so that is what started the idea for Kabbage in the first place. It was this idea to use data. We only learned later that nobody else did that for any other part of the SME market, we could not believe that was possible, so we were really surprised.

9)


67

F: Do you think there is a data point, or a group of data points, that could be game-changing for your analysis, but it’s still not available and even though you don’t see coming available soon, you would really like to have for your model at Kabbage?

K: There are two problems that I need to solve, that are hard to solve. One of them is to understand if a business is who they say they are - and I am able to do that better than most, because I am triangulating data across from multiple providers, in order to arrive at the end answer, but there are two ways that we love to do that and there are regulatory requirements that constrain our application process and that creates friction for consumers that really frustrate us. One of them is UBO - Ultimate Beneficial Owner, which requires that any institution or business providing financial products to a small business has to verify ownership, of that business if there is any entity or individual who owns 25% or more of that business - the max being 4 of course. More so, a lot of businesses have partners, more than 1 sometimes, might be an investor working on the UK, and there’s something called company’s house, which aggregates all that information that you can access in real time. It is easy to do and you can verify the business. We have nothing like that in the US. In the US, we have very different 50 states each with their own Secretary of State, each of which houses, uses and shares that data differently, but there’s no federal database, or any access. To answer your question, what I would love is to have access to that data repository so that my customers could have an easier time getting through the application, since it makes it really challenging. The other federal piece, that I think would be useful is to have real time access to tax data, to allow us to verify revenue. I would love for that to be mandated for small businesses lenders to ensure that lenders don’t provide businesses with more capital than they need, because that’s a real verified way of confirming revenue, and that’s one of the number one things that you look at, when you are underwriting a small business- those would be my requests on the federal side. I also think the other plates for data would be really useful, but hard to get, in some cases because they are not available - the actual underlying transaction data. Whether that means you are a retailer and you sold 17 pairs of shoes and 14 handbags; or whether you are a plumber with 299 customers, that you served in the last 30 days, you sold 14 air conditioning units and 217 service contracts - that is the type of information that would be useful to me, getting in that underlying transaction detail is very hard for small businesses, because they need to come up and framework for collecting that data. I am not sure if it is a problem that can be solved, with any tools that exist today, but it’s something I would love to have.

10)F: There has been big talk and backlash on the democratic aspect of data


68

and its bias. When we are talking about consumer lending there is a lot of sensitive data but with SMBs is slightly less problematic although it can still be problematic. What I would ask you is if you find some biases in data, besides the obvious democratization of lending, that comes from you potentially be able to serve all the 32 million businesses in the US, do you see other aspects where you need to be more democratic and how you would approach it?

K: Let me start with a stat that is important to us: we have twice as many women in minority business owners in our customer portfolio, as they exist in the general business owning population. There are two reasons for this I believe: the first is around selection bias,for example: You are a weed shop owner in downtown Cincinnati, a black woman and you walk into your local bank branch. It is a national bank but it’s still a local branch. You sit across the counter from a 62 year old white male loan officer. That is a very awkward conversation. Hence, many people don’t even go to this branch and have this conversation, and many people who do have that conversation, may not get what they want, not because the loan officer isn’t sure, not because they intend to have bias, but we as humans all have biases. Another example I often give: You are a loan officer underwriter, you have never seen the customer, and you are only looking at loan documents. All the sudden, you see Sally applied for a loan, but well - your ex-girlfriend is named Sally, she just broke up with you last night, you hate all Sallys, you can’t help it, you are a human, you are gonna have a bias against this applicant Sally, even if you don’t know this applicant, because we hierarintaly make bad decisions. On the other side, I think at Kabbage we make better decisions because we are using blind data. We don’t see our customers, we don’t see which ethnicity they are, we don’t know a gender, we don’t know any of this, we are literally just making decisions based on business performance. We do not base on our opinions of things, although there is a risk that you run, if you can take that too far. Say, you look into your customers transaction data and you think, “Hey, I want to understand where my customer shop and I want to understand if that presents more risk to me”. Afterwards, you wind up finding that you have several customers that shop at this hispanic neighborhood across the country. You find that these customers are less likely to repay, but maybe it is because they live in disadvantaged areas, and they don’t have the resources they need to run their businesses efficiently. Maybe they could run them better if they had access to capital but they simply don’t. You have to be really careful on how your machines build models and the kind of decisions that your machines are making because you can intentionally bias your model against the population, that really needs its support.


69

11)F: When we think about Kabbage and new businesses in general, the usage of blind data is done in a much more democratic way. Do you think that in this process of democratizing, through data, there is something that Kabbage could do or that could be done, in an even earlier phase than where Kabbage is currently kicking in? Even before the customer enters the bank to step into this awkward conversation? Or even assess the possibility of opening a business?

K: Regarding the first step to choose to open a business, that is quite hard. I don’t know if I can find people who I think maybe want to open a business, and let them know that they can do it. What I do know, because we are launching a couple of products that are startup products for businesses is that I need to have 12 months of data and it’s very hard for me to serve a business that’s only been around since last month, since there is no information to support that business. What we are doing is launching a product later this year called “Insights”which basically entails that any business can come to our site, connect to “Insights”, connect their data and will predict cash flow for them. By doing that we can say “Hey, we really believe you could benefit from an injection of cash; you’re keeping too much money on your account; you’re borrowing too much money; you are keeping it for too long; you pay too much fees; here is how you should be doing it” - our goal is to give people information before they need it. Then there are a couple of other starter products: one is a charged card product that any business could use, since a lot of businesses are using personal credit cards, which has this inherited consequence, that adversely impact on your credit score. It happened to us on Kabbage, when we started it, because they are highly utilised as credit lines, and they are there to spring their businesses and then it makes their personal borrowing more expensive and as such, businesses need products that they can get into sooner, that are tied to their personal credit, or that don’t have personal guarantees. In that way, if you make a bad decision on your business, you likely lose your home. If you ask for a small business loan that has collateral as guarantee or has a home, you could be homeless because you made one bad decision.

12)F: To non finance professionals it might appear that using data relying on models and not on human judgement might be a proxy for less scrutiny - if you are coming from a traditional approach - and we find this as something that is difficult to explain. I think your effort in terms of pushing policies forward is also very much focused on this. How would you address a concern that basically translates into “great technology and great people using the technology”, since this is the best case scenario. What is the real scenario that you explain to a policy maker to make them understand how important it is to factor in the data?


70

K: I have spent a lot of time working with policy makers, regulators and legislators and I think the question that they’re asking is more like “I don’t know if the businesses understand what they are getting. How do we know that there has been really clear transparent disclosure about the weights, the fees and the costs of borrowing?” This is really their biggest concern, because everybody seems to understand that businesses need capital for growth, even, elected officials who have never owned a business. This seems to be something that people respect and appreciate, and they also believe that business owners are maybe more savvy than consumers, that they are more educated about the decisions that they’re going to make. However they still believe that there is a lack of transparency because these financial products are very confusing, and as such they spent much more time talking about that than I do about you the data. Nobody seems to worry about the data, they cared about the data for Facebook there is a lot of conversation about that, but when it comes to ownership of data, even the CFBP has an opportunity under Dodd-Frank to require banks to share data with their parties.I feel this is a really accepted topic right now - the sharing of data - it’s more about transparency in terms of pricing.

13)F: In sum, to frame it in a different way: the main concern is data being used in a fair way in order to allow businesses not to rely on Kabbage cause you’re the only provider for that service, but because - it’s fair and also in terms of what the is cost to this small businesses.

K: That is a correct framework.

Powered by:

The Credit Frontier · 2020-05-19 · Network Infographic: Ana Subtil Cover Design: Ana Subtil Our...

Documents

Transcript of The Credit Frontier · 2020-05-19 · Network Infographic: Ana Subtil Cover Design: Ana Subtil Our...