2012 AsFA ID: 10145

1

Bancassurance Markets in China: Some evidence from European Banks

Hsin-Yu Liang*

Assistant Professor of International Trade Feng Chia University

100 Wenhwa Rd., Seatwen, Taichung, 40724, Taiwan Phone: (886)-4-2451-7250 ext. 4267 Fax: (886) 4-24510409

E-Mail: lianghy@fcu.edu.tw

Yann Peng Ching Master Student of International Trade

Feng Chia University 100 Wenhwa Rd., Seatwen, Taichung, 40724, Taiwan

Phone: (886)-4-2451-7250 ext. 4267 Fax: (886) 4-24510409 E-Mail: yann_ching@hotmail.com

*Corresponding author.

Please do not quote without prior permission from the authors

This version: Dec., 2011

2012 AsFA ID: 10145

2

Abstract

This study considers possible operational benefits of mixing banking and

insurance sub-sectors in order to make suggestions related to bancassurrance markets

in China. Our study sample contains only banks and insurance companies that haven’t

been directly involved in bancassurance during the year 2008 in European Union (EU)

countries. The EU has had bancassurance markets since the 1990s. Our monthly stock

return findings are based on efficient frontier portfolios and pair-wise combinations.

Our results suggest that portfolio diversification is an important benefit of combining

banks with different types of insurance companies. We further show that banks

strategically involved in the service of non-life insurance will benefit by

simultaneously enhancing returns and reducing risks. These findings support

recommendations for cross-strait financial integration after the Economic Cooperation

Framework Agreement (ECFA); we encourage non-life insurance companies in

Taiwan to form bancassurance companies as joint ventures with banks in China.

JEL classification: G21; G34; G28

Keywords: bancassurance, portfolio diversification, ECFA

2012 AsFA ID: 10145

3

Bancassurance Markets in China: Some evidence from European Banks

Abstract

This study considers possible operational benefits of mixing banking and

insurance sub-sectors in order to make suggestions related to bancassurrance markets

in China. Our study sample contains only banks and insurance companies that haven’t

been directly involved in bancassurance during the year 2008 in European Union (EU)

countries. The EU has had bancassurance markets since the 1990s. Our monthly stock

return findings are based on efficient frontier portfolios and pair-wise combinations.

Our results suggest that portfolio diversification is an important benefit of combining

banks with different types of insurance companies. We further show that banks

strategically involved in the service of non-life insurance will benefit by

simultaneously enhancing returns and reducing risks. These findings support

recommendations for cross-strait financial integration after the Economic Cooperation

Framework Agreement (ECFA); we encourage non-life insurance companies in

Taiwan to form bancassurance companies as joint ventures with banks in China.

JEL classification: G21; G34; G28

Keywords: bancassurance, portfolio diversification, ECFA

2012 AsFA ID: 10145

4

Introduction

The existing branch networks of banks in China make local Chinese banks

unique. Foreign banks or insurers seek to control Chinese banks in order to penetrate

the financial service sector in China. Major local banks in China typically have

thousands of branches. Foreign companies that undertake joint ventures with Chinese

banks can enter the Chinese financial services market and can easily build a broad

distribution channel that can increase market share in a short time. Thus, foreign

banks and insurers usually choose either joint ventures or alliances to penetrate the

Chinese bancassurance sector (Davis, 2007). Furthermore, the upgraded living

standards and increasing consumption abilities of 1.3 billion Chinese people

constitute a huge business opportunity for insurance companies around the world.

Before China’s engagement with the global economy, most Chinese people had

cultural inhibitions that suppressed their consumption of protective insurance products.

Thus, most insurance products sold in China are simple and have some saving or

investment function. However, as western culture gradually influences Chinese

consumers and challenges their earlier concepts of financial planning, they might be

willing to know more about more complicated insurance products. This has been

noted by Davis (2007), who wrote: “China is another giant moving into

bancassurance from the dominant agency market”. Because Chinese insurance

markets are not yet well-developed, bancassurance firms might need foreign partners’

professional knowledge in areas such as operating systems, marketing, product

development, staff training, and operation risk management.

The signing of the Economic Cooperation Framework Agreement (ECFA)

between Taiwan and China has brought great business opportunities for cross-strait

financial integration and has boosted the trend of cooperation between financial

2012 AsFA ID: 10145

5

institutions on both sides. Taiwan has allowed foreign insurance companies to enter

the Taiwanese insurance sector for a decade, during which Taiwanese insurance

companies have accumulated operating experience and “know-how” brought by

foreign insurers. Now that the Taiwanese insurance sector has matured, Taiwanese

companies have “know-how” related to financial regulation and operating experience

in risk management, product development, innovation, and professionalism.

Taiwanese companies are seeking some way to broaden their market share worldwide.

Following ECFA guidelines, Taiwanese banks and insurance companies can access

the Chinese financial service market and bring their “know-how” to China. Both sides

can communicate in a common language (Mandarin) and both sides share the Eastern

Asian culture and Chinese values. This cultural similarity reduces the costs of market

entry, such as employee training and translation. Thus Taiwanese firms in China have

low market entry costs and other foreign firms have higher market entry costs.

Furthermore, we also believe that the marketing skills of Taiwanese insurance

companies will help Chinese financial workers to sell insurance products.

After the signing of the Maastricht Agreement (1992) in Europe, liberal

regulations promoted financial integration of European firms; this integration led to

the concept of bancassurance. Even though legalized by the Gramm-Leach-Bliley Act

(1999), bancassurance has not become a major trend in the U.S. Therefore, in this

study, we analyze the possible integration of European banks and insurance

companies which were not directly involved in bancassurance in 2008. Reasoning

empirically from a sample of European firms, we derive policy implications for how

to do cross-strait financial integration in the framework of the ECFA.

Most empirical studies related to bancassurance analyze the benefits of the

2012 AsFA ID: 10145

6

mergers by examination of the post-merged sample banks/bancassurances, including

some inefficient economies of scale and scope that resulted from conflicts of interests.

The present authors, Liang and Ching, (2010) used efficient frontier analysis to

evaluate the potential operating benefits among European banks and three types of

insurance companies by reviewing the means, standard deviations, and coefficients of

variance for stock returns; they provided evidence that bancassurance reduced risks

and enhanced returns for these European firms. Our 2010 study did not adjust for the

exchange rate changes in international portfolio analysis and used 45 banks in order to

have a sample of banks comparable to the sample used by Nurullah and Staikouras

(2008). The present study examines 192 banks (all listed European banks that do not

have insurance subsidiaries in year 2008). By extending our sample size, we can

avoid some bias that might be caused by omitting observations. Furthermore, we also

adjust for the exchange rate changes in the international efficient portfolios by

adopting the methodology of Eun and Resnick (1988). The present work adapts two

approaches in Eun and Resnick (1988) for exchange rate changes related to stock

returns in international portfolios; both approaches (Method 1 and Method 2) reach

similar conclusions. Both approaches relate to efficient frontier analysis and pairwise

combinations.

Our analysis of the evidence makes three contributions to the literature: First,

after one has accounted for the impact of exchange rate changes, one find that firms

that formed bancassurance between 2004 and 2007 benefitted. Second, banks can

obtain operating benefits by strategic involvement in non-life insurance. Third,

non-life insurance companies in Taiwan can use joint ventures with Chinese banks to

penetrate the bancassurance markets in China.

2012 AsFA ID: 10145

7

This paper is organized as follows: The next section presents a review of relevant

literature, followed by a description of the sample data and research methodology.

The empirical results are discussed, and we set forth policy implications for actions

within the framework of the ECFA.

Literature Review

A. Bancassurance in Europe

The concept of bancassurance first started in European countries; it has now

experienced rapid growth in other countries, especially in emerging markets. The

success of bancassurance in Europe has primarily been due to favorable regulations

and fiscal policies. Liberal regulations on the ownership of insurance companies by

banks and the sales of insurance products through banking networks are clearly

necessary if bancassurance is to develop (Swiss Re, 2007). Life insurance was

attractive to banks because most European Community countries promoted it through

advantageous tax provisions in order to encourage individuals to save for their

retirements (Lown et al., 2000). Despite the withdrawal of fiscal benefits from life

insurance in France, Italy, and Spain since the mid-1990s, bancassurance in these

markets still retains a high level of resilience (Swiss Re, 2007).

The European insurance market is characterized by two distinct models: the

bancassurance model and the broker model (Davis, 2007). The bancassurance model

occurs in countries like France and Spain, where banks control at least half of the life

insurance market, while the broker model can be found in countries such as the UK

and Netherlands, where the life insurance market is dominated by brokers. The main

reasons for the different rates of development in bancassurance in Europe are the

2012 AsFA ID: 10145

8

difference in legislative and regulatory standards and the complexity of insurance

products. The success of bancassurance is arguably linked to the maturity of the

market (Ernst & Young, 2010). When a market becomes more mature, it also grows

in complexity, and bancassurance occupies a much less prominent position.

B. Comparison Between Life and Non-life Insurance Products in Bancassurance

Market

Life and non-life insurance are both fundamentally about taking on and managing

risk, but they involve different types of risk. Non-life insurance faces short and

long-term underwriting risk; life insurance tends to face some combination of

underwriting and long-term market risks (Ernst & Young, 2010).

Life insurance and other long-term investment products have attracted most of the

strategic attention of bank distributors, while many banks have assigned low priorities

to purely protective non-life insurance products associated with auto and home loans

(Davis, 2007). However, as the bancassurance market has developed, the trend has

changed. As stated by Davis (2007), “In bancassurance countries like France, banks

have moved from selling the long-term life product to marketing simple term life and

non-life products”. Simple and standardized products that do not require specialized

advice can be sold effectively to a bank’s client base by that bank’s branch systems,

by the internet, or even by direct mail. (Davis, 2007).

The sophistication of insurance products such as whole-life insurance products

makes it difficult to attach the products to banking services. These types of insurance

products require dynamic and massive distribution channels, and might also be easily

subject to mis-selling regulations (Artikis and Staikouras, 2008). Bundling banking

2012 AsFA ID: 10145

9

products with less sophisticated and standardized insurance products such as property

and casualty insurance products reduces the cost of originating business and adverse

selection, since the mortgage advice is conditional on buying insurance(Artikis and

Staikouras, 2008). Non-life insurance products with high degrees of product

standardization and simplicity can be sold at bank counters by personnel such as bank

tellers, who do not have much insurance knowledge (Falautano and Marsiglia, 2003).

As stated by Artikis and Staikouras (2008), non-life insurance services provided by

banks can be seen as brand-assurance, brand-assurers may enjoy more public trust

than traditional insurance providers.

C. Economic Scale and Scope of Bancassurance Formation

Banks and insurers are similar in that they both pool and channel the money of

individuals (Gora, 1997; Fields, Fraser, and Kolari, 2007) and are both

information-intensive financial service providers. Therefore, economies of scale may

be easily achieved through the formation of bancassurance. For example, banks can

collect available funds from households or business units and transfer those funds to

units that need external capital. Furthermore, banks are experts at monitoring

borrowers and providing risk management services for depositors. Insurance

companies also play an intermediary role by pooling funds for risk sharing and

providing risk management services for their customers. Investment banks, mutual

fund companies, and securities brokers, however, only transfer market risk to their

customer by facilitating transactions and providing access to the markets.

Empirical studies have provided evidence that economies of scale in bancassurance

reduce information cost by serving each customer with a larger set of services. Fields,

Fraser, and Kolari (2007b) used the size of the target relative to the bidder in terms of

2012 AsFA ID: 10145

10

the total assets to measure economies of scale, and discovered that when the target is

large, the bidders are more likely to have positive bidder returns. Other studies also

provided evidence that the bidders’ positive abnormal returns are associated with the

size of the target (Chen and Tan, 2011; Dontis-Charitos, Molyneux, and Staokouras,

2011; Staikouras, 2009). Economies of scope in bancassurance are able to distribute

their insurance policies throughout the network of banks while saving on distribution

costs (Dontis-Charitos, Molyneux, and Staokouras, 2011). The banks are then able to

sell insurance products to increase their profits (Fields, Fraser, and Kolari, 2007).

The globalization of financial markets and numerous technological breakthroughs

have brought an unexpected wave of competition among financial institutions.

Normally, banks that issue loans engage in rent seeking; bank customers who make

up a large body of corporate borrowers have found that they can avoid rent seeking

from bank loans and obtain cheaper financing by issuing equity in the capital market

themselves (Gora, 1997). Before bancassurance, traditional banking in most European

Community countries faced slow growth rates and falling profitability; banks were

thus forced to explore new business opportunities. Life insurance was an attractive

alternative because most European Community countries promoted it with

advantageous tax provisions to encourage individuals to save for their retirement

(Lown et al., 2000). Furthermore, changing customer preferences, such as one-stop

shopping, required cooperation amongst all financial service providers (Voutilainen,

2004).

European insurance companies faced high costs when searching for new distribution

channels, and thus their profit margins declined. A broad customer network and

public trust in banks can provide these insurance companies with a way to benefit

2012 AsFA ID: 10145

11

from economic scale and scope.

Diminishing profit margins in banks and insurance companies force them to seek new

sources of income by cross-selling to other industries as bancassurance (Voutilainen,

2004). Banks are able to sell more products to increase their non-interest profits (fee

income) and to utilize fixed capacity resources for new products (Bergendahl, 1995).

Simultaneously, insurance companies are able to distribute their insurance policies at

lower prices than traditional insurers. Banks additionally often have exclusive

information about lenders and borrowers and are able to access payment systems and

central bank funding (Bergendahl, 1995). In brief, both banks and insurance

companies have responded to the competitive environment by entering into

bancassurance arrangements and achieving economies of scale and scope.

Data and Methodology

A. Data

The sample data for this study covers 192 listed European banks (all listed

European banks that do not have insurance subsidiaries), 32 life insurance

underwriting companies (SIC code: 6311), 14 non-life insurance underwriting

companies (SIC code: 6331), and 7 insurance brokers (SIC code: 6411). The OSIRIS

database provided the accounting data for these firms for the period between 2004 and

2007. The selection criteria require that candidates: a) are not partially owned

insurance subsidiaries (meaning that over 50% of their equity must be held by a bank)

and b) are banks that do not have insurance subsidiaries. These criteria ensure the

sample banks and insurers have not been directly involved in bancassurance activities.

2012 AsFA ID: 10145

12

Each bank’s monthly stock return (SR) is used to measure that bank’s performance.

The monthly stock prices listed in the OSIRIS database are expressed in local

currencies. Therefore, stock return calculations for banks and insurers from different

countries, should further consider the potential gains and losses from exchange rate

fluctuations. Exchange rate fluctuations are likely to mitigate the potential gains from

international diversification by making an investment portfolio more risky (Eun and

Resnick, 1988). Eun and Resnick (1988) discussed two approaches for calculating the

stock return: the first one (Method 1) includes the interactive terms between changes

in stock price and changes in exchange rate; the other one (Method 2) does not

include these interactive terms. The descriptions for both approaches are shown in

Table 1.

B. Methodology

In 1952, Markowitz provided a comprehensive theoretical framework for the

analysis of investment portfolios. Several studies have adopted this method to address

the possible integrations among banks, non-bank financial services, non-financial

services, and commerce (Liang and Reichert, 2010; Reichert, Wall, and Liang, 2008;

Wall, Reichert, and Liang, 2008). The Markowitz portfolio selection model provides a

mean variance portfolio analysis for the integration between banks and insurers. Here

is a brief description of Markowitz's model:

Assume that there are N securities denoted by Si (i=1,..., n); the return of the

securities Si is denoted by Ri and the proportion of total investment funds devoted to

these securities is denoted by wi . Thus, the return associated with the portfolio is

given by

2012 AsFA ID: 10145

13

Since the variance is regarded as the risk of investment, the best investment is

one with the minimal variance subject to an average given return.

The samples in this study are divided into four groups:

I. Group I: Banks (SIC code: 602)

II. Group II: Life insurance underwriting companies (SIC code: 6311)

III. Group III: Non-life insurance underwriting companies (SIC code: 6331)

IV. Group IV: Insurance brokers (SIC code: 6411)

The risk and return implications of the integration between these four groups are

examined by the creation of efficient portfolios. The monthly SRs are used to measure

performance of banks and insurers. Since the data collected is at the firm level, the

bank’s market capitalization is used as a weight to calculate the SR at the aggregate

level. Thus, the weighted average industry SRs for the years 2004 to 2007 are used to

measure the performance of the four groups in this study.

Empirical Result

1. Efficient Frontier Analysis

Table 2 presents the summary of statistics for the four groups calculated by

2012 AsFA ID: 10145

14

Method 1, and Table 3 presents the results of Method 2. The top portion of each table

gives the mean and standard deviation for the stock return over the sample period, as

well as the correlation with group I. The ranking of each group is provided; industries

with large mean performances have high ranks; groups with low standard deviations

and low positive or negative correlations also have high ranks. The remainder of the

panel indicates the mean performance measure, standard deviation, and coefficient of

variation (CV) for various mean-variance efficient portfolios (labeled A, B, C, D, and

E). The composition of each of these efficient portfolios is presented at the bottom of

the table.

In both tables, portfolios A, B, and C, show increasing involvement in non-life

insurance activity, and have higher stock return means and lower standard deviations

and coefficients of variation than the bank alone. This implies that European banks

diversifying into the non-life insurance sector over the sample period may have higher

average returns and lower portfolio risk. Using Method 1 as an example (Table 2),

comparing portfolio C (51.41% allocated to non-life insurance sector) with Portfolio

A (6.31% allocated to non-life insurance sector), the average stock return increases

from 1.34% to 1.70% with a 45.10% increase in the non-life insurance sector. At the

same time, the coefficient of variation also declines from 2.25% to 1.94%. The results

are similar in Table 3 by using Method 2 (Table 3). The optimal efficient portfolio

with the lowest CV for these two methods are the portfolios (Portfolio C in Table 2

and Table 3) with over 50% asset allocation in the non-life sector, about 20%

allocation in banks, and almost 24% allocation in the insurance brokerage sector.

In Table 3, by further comparing the standard deviation of the bank group (Group

I) alone (3.35%) with efficient portfolios A, B, and C, it can be observed that the risk

level of banks declines if they diversify into the insurance sector (Groups II, III, and

IV); at the same time, the returns of the bank are enhanced. Next, if the CV of the

2012 AsFA ID: 10145

15

bank alone (2.663%) is compared with all efficient portfolios, it is evident that the CV

of the efficient portfolios is visibly lower. This proves that the so-called universal

banking system that allows European bancassurance markets also enhances the

performance of our sample banks and reduces their risk levels.

2. Pairwise Combination between Banks and Insurance Sectors

We think that it would not be helpful for banks in Europe which have not been

directly involved in insurance activities to affiliate with these insurance sectors at the

same time by creating the efficient frontier portfolios of four assets. Thus after

examining the possible outcome of portfolio combination of these four groups by

efficient frontier analysis, we consider the pairwise combinations between banks

(Group I) and insurance sectors (Group II, III, IV) in Table 4 and Table 5 by using

two-asset portfolio analysis to discover some useful short-term implications. Table 4

summarizes the result of combining European banks in varying portions with

insurance firms by Method 1; Table 5 shows the corresponding results of Method 2.

Similar to the efficient portfolio analysis, stock returns (SRs) are used as the measure

of performance, and the tables show the mean (MEAN), standard deviation (STD),

and coefficient of variation (CV) of each combination.

Tables 4 and 5 show the outcomes of three types of pairwise combinations (Panel

A: bank and life insurance, Panel B: bank and non-life insurance, and Panel C: bank

and insurance broker) for both methods (Method 1 and Method 2). The optimal

outcome for each type is the one with the lowest CV; optimal outcomes are as follows:

1. Panel A: 75% allocation in commercial banks and 25% in life insurance. 2. Panel B:

25% allocation in commercial banks and 75% in non-life insurance. 3. Panel C: 75%

allocation in commercial banks and 25% in the insurance brokerage sector. By

comparing the CVs of the above three optimal pairwise combinations (2.61% in CV

2012 AsFA ID: 10145

16

for Panel A, 2.06% in CV for Panel B, and 2.41% in CV for Panel C in Table 4),

commercial banks in Europe should be better off if they select a 75% affiliation with

non-life insurance as the first step to create a two-asset portfolio. This also lends

support to the efficient frontier analysis finding (Portfolio 3 in Table 2 and Table 3)

that the optimal portfolio in the efficient frontier should be the one with over 50%

asset allocation in the non-life insurance sector and with portfolio performance further

enhanced from 2.06% CV to 1.94% CV.

Conclusion and Implications

1. Potential Benefits in Bancassurance Markets: Evidence from European

Banks

This analysis adjusted the weighted average industry stock return of sample banks

and insurance companies from 2004 to 2007 for exchange rate changes in stock

returns; this analysis examined efficient portfolios and pairwise combinations among

banks and insurance sub-sectors in Europe; this analysis discovered that the potential

profits of our sample banks (all European banks have not directly involved in any

insurance activities) were improved and the potential earning risks were reduced.

These findings strongly support the findings of our previous study (Liang and Ching,

2010) and further clarify the result by adjusting for the impact of exchange rate

changes in the asset returns and including more sample banks. Our results further

indicate that by strategically investing in the non-life insurance sector, banks can

improve their potential profits and reduce their potential earning risks. Thus, if banks

in Europe get involved in the non-life insurance sector, the financial market in Europe

might achieve a higher level of efficiency in bancassurance markets. Our finding here

might provide some useful suggestions for the bancassurance markets in China within

the framework of the ECFA.

2012 AsFA ID: 10145

17

2. Implications for Cross-strait Financial Integration after the ECFA

According to the Swiss Re and BCG report in 2009, China’s insurance industry is

still in developing stage, and it is booming. Even though the Chinese population is

facing an aging problem, the insurance products provided there are still limited and

simple. Most Asian consumers do not want to buy insurance products for protection

only, but seek to build savings by investment. So far, most insurance products sold

through China’s bancassurance platform are intended to accumulate saved wealth

(Swiss Re and BCG, 2009; PricewaterhouseCoopers, 2010). No health or pension

insurance is available from banks; there are only a few types of non-life products

distributed through Chinese bancassurers (Swiss Re and BCG, 2009). Therefore, as

Chinese living standards have risen, and as westernized culture has altered

consumption preferences and financial planning, foreign insurers have noticed the

increasing demand for private health and pension insurance and non-life insurance

products. However, because the Chinese government imposes heavy regulations on

foreign ownership of banks and non-bank financial institutions, foreign insurers

usually cannot enter the market to construct their sales networks and obtain license

coverage (Swiss Re and BCG, 2009). Therefore, joint ventures with Chinese banks

might be the best strategy for foreign insurers to enter the insurance markets in China;

foreign banks engaged in joint ventures might be licensed more quickly.

The present study has analyzed data from Europe, but the findings might

encourage Chinese banks to affiliate with non-life insurance companies to enhance

returns and to reduce risks. Most non-life insurance products are quite simple

compared to popular life insurance products that involve some investment function.

Chinese banks should sell non-life insurance products through their local branch

networks; current bank workers could sell these products without major re-training in

2012 AsFA ID: 10145

18

new marketing skills.

The business cycle of Taiwanese insurance industry is at the mature stage and

these companies are eager to broaden their overseas market shares; the bancassurance

markets in China are particularly desirable now that the ECFA is in force. While

European firms might have trouble adjusting to Chinese culture, Taiwanese insurance

companies can easily set up alliances with local financial firms that share the same

language and cultural values. Furthermore, Taiwanese insurance companies make

excellent partners for firms in the Chinese bacassuance markets; Taiwanese partners

offer sales know-how, experience in insurance product design, marketing, and risk

management. Affiliations between Taiwan insurers and Chinese banks might create a

win-win situation, especially with non-life insurance products. This is because it is

easier to bundle banking products with less sophisticated and standardized insurance

products, such as property and casualty insurance products. Chinese bancassurance

firms still do not widely distribute these types of products.

References

Artikis, P.G., S. Mutenga, and S.K. Staikouras. 2008. “A practical approach to blend

insurance in the banking network” The Journal of Risk Finance 9(2): 106-124

Bergendahl, G. 1995. “The profitability of bancassurance for European banks”

International Journal of Bank Marketing, 13(1): 17-28.

Chen, Z. and J. Tan. 2011. “Does bancassurance add value for banks? – Evidence

from merger and acquisitions between European banks and insurance companies”

Research in International Business and Finance. 25(2011): 104-112.

Davis, I.S. 2007. “Bancassurance: the lessons of global experience in banking and

insurance collaboration” VRL Financial News.

2012 AsFA ID: 10145

19

Dontis-Charitos, P., P. Molymeux, and S.K. Staikouras. 2011. “Does the stock market

compensate banks for diversifying into the insurance business?” Financial Markets,

Institutions & Instruments. 20(1):1-28.

Ernst & Young. 2010. “Bancassurance: A Winning Formula”

Eun, C.S. and B.G. Resnick. 1988. “Exchange rate uncertainty, forward contracts, and

international portfolio selection” Journal of Finance. 43(1): 197-215.

Falautano, I. and E. Marsiglia. 2003. “Integrated distribution of insurance and

financial service and value creation: challenges ahead” The Geneva Papers on Risk

and Insurance. 28(3): 481-494.

Fields, L.P., D.R. Fraser, and J.W. Kolari. 2007a. “Is bancassurance a viable model for

financial firms” The Journal of Risk and Insurance. 74(4): 777-794.

Fields, L.P., D.R. Fraser, and J.W. Kolari. 2007b. “Bidder return in bancassurance

mergers: Is there evidence of synergy?” Journal of Banking and Finance. 31(2007):

3646-3662.

Gora, J.C. 1997. “Bancassurance: position for affiliations - lessons from Europe,

Canada and the United States” Atlanta: Loma.

Liang, H.Y. and Y.P. Ching. 2010. “Possible financial integration in European banks”

The International Journal of Finance. 22(2): 6460-6484.

Liang. H.Y., and Alan Reichert. 2010. “The integration of banking and commerce: a

global perspective” Journal of Banks and Bank Systems. 5 (3): 5-14

Lown, C.S. et al. 2000. “The changing landscape of the financial service: what lies

ahead” Federal Reserve Bank of New York Economic Policy Review, 6(4): 39-55.

PricewaterhouseCoopers. 2010. “Foreign insurance companies in China”

Reichert, A., Wall, L., and Liang, H. 2008. “The final frontier: the integration of

banking and finance – part 2, risk and return using efficient portfolio analysis”

Economic Review (Federal Reserve Bank of Atlanta): 1-14

2012 AsFA ID: 10145

20

Staikouras, S.K. 2009. “An event study analysis of international ventures between

banks and insurance firms” Journal of International Financial Markets, Institutions &

Money. 19(2009): 675-691.

Swiss Re and BCG. 2009. “Bancassurance in China”

Swiss Re. 2007. “Bancassurance : emerging trends, opportunities and challenges”

Voutilainen, R. 2005. “Comparing alternative structure of financial alliances” The

Geneva Papers on Risk and Insurance Issues and Practice, 30(2): 327-342.

2012 AsFA ID: 10145

21

Table 1. Variable Description

Variable Definition Formula

Method 1

SR Stock Return (Ri + e i +Ri e i) *100 (where Ri = Pt / Pt-1 , e i = S t / S t-1 )

Method 2

SR Stock Return (Ri + e i ) *100 (where Ri = Pt / Pt-1 , e i = S t / S t-1 )

2012 AsFA ID: 10145

22

Table 2 Portfolio Analysis by Industry (Method 1)

Stock Return weighted by Market Capitalization

SR(%) SR(%) CV Correlation

Industry Mean Rank STD Rank % Rank with CBs Rank

Bank (Group I) 1.257 4 3.348 1 2.663 2 1 4

Life Insurance (Group II) 1.320 3 4.098 2 3.105 3 0.676 3

Non-life Insurance (Group III) 2.082 1 4.318 3 2.074 1 0.637 2

Insurance Broker (Group IV) 1.337 2 4.735 4 3.542 4 0.266 1

Efficient risk and return portfolios A B C D E

Mean SR (%) 1.337 1.582 1.701 1.925 2.082

STD SR (%) 3.007 3.137 3.301 3.766 4.318

CV (%) 2.249 1.983 1.941 1.956 2.074

Industry Portfolios allocation (%)

Bank (Group A) 56.473 37.907 24.252 0 0

Life Insurance (Group B) 10.962 0 0 0 0

Non-life Insurance (Group C) 6.309 36.932 51.405 78.864 100

Insurance Broker (Group D) 26.257 25.160 24.344 21.136 0

2012 AsFA ID: 10145

23

Table 3 Portfolio Analysis by Industry (Method 2)

Stock Return weighted by Market Capitalization

SR(%) SR(%) CV Correlation

Industry Mean Rank STD Rank % Rank with CBs Rank

Bank (Group I) 1.257 4 3.348 1 2.663 2 1 4

Life Insurance (Group II) 1.325 3 4.102 2 3.096 3 0.676 3

Non-life Insurance (Group III) 2.082 1 4.318 3 2.074 1 0.637 2

Insurance Broker (Group IV) 1.337 2 4.735 4 3.542 4 0.266 1

Efficient risk and return portfolios A B C D E

Mean SR (%) 1.338 1.529 1.727 1.916 2.082

STD SR (%) 3.007 3.086 3.347 3.743 4.318

CV (%) 2.247 2.018 1.938 1.954 2.074

Industry Portfolios allocation (%)

Bank (Group A) 56.556 43.935 21.195 0 0

Life Insurance (Group B) 10.795 0 0 0 0

Non-life Insurance (Group C) 6.392 30.545 54.644 77.656 100

Insurance Broker (Group D) 26.256 25.520 24.161 22.344 0

2012 AsFA ID: 10145

24

Table 4. Pairwise Combination of Commercial Banks with Insurance Companies

(Method 1)

Percent in insurance sub-sector

0 10 25 50 75 90 100

Panel A:

Life Insurance

MEAN SR (%) 1.2567 1.2631 1.2727 1.2886 1.3045 1.3141 1.3205

STD SR (%) 3.3839 3.3395 3.3265 3.4477 3.7302 3.9635 4.1409

CV (%) 2.6926 2.6438 2.6138 2.6756 2.8594 3.0162 3.1360

Panel B:

Non-life Insurance

MEAN SR (%) 1.2567 1.3393 1.4631 1.6695 1.8759 1.9998 2.0823

STD SR (%) 3.3839 3.3406 3.3407 3.5113 3.8673 4.1513 4.3638

CV (%) 2.6926 2.4943 2.2833 2.1031 2.0616 2.0759 2.0956

Panel C:

Insurance Broker

MEAN SR (%) 1.2567 1.2647 1.2768 1.2968 1.3168 1.3288 1.3368

STD SR (%) 3.3839 3.2063 3.0805 3.2778 3.9004 4.4089 4.7852

CV (%) 2.6926 2.5352 2.4128 2.5276 2.9621 3.3179 3.5796

2012 AsFA ID: 10145

25

Table 5. Pairwise Combination of Commercial Banks with Insurance Companies

(Method 2)

Percent in insurance sub-sector

0 10 25 50 75 90 100

Panel A:

Life Insurance

MEAN SR (%) 1.2633 1.2699 1.2796 1.2959 1.3122 1.3220 1.3285

STD SR (%) 3.3649 3.3193 3.3049 3.4244 3.7061 3.9393 4.1168

CV (%) 2.6635 2.6139 2.5827 2.6424 2.8242 2.9798 3.0987

Panel B:

Non-life Insurance

MEAN SR (%) 1.2633 1.3463 1.4708 1.6783 1.8858 2.0103 2.0933

STD SR (%) 3.3649 3.3216 3.3224 3.4956 3.8554 4.1417 4.3558

CV (%) 2.6635 2.4672 2.2589 2.0828 2.0444 2.0602 2.0808

Pane C:

Insurance Broker

MEAN SR (%) 1.2633 1.2725 1.2861 1.3089 1.3317 1.3454 1.3545

STD SR (%) 3.3649 3.1910 3.0695 3.2691 3.8882 4.3927 4.7660

CV (%) 2.6635 2.5078 2.3866 2.4976 2.9197 3.2650 3.5186

2012 AsFA ID: 10145

26

Appendix 1. Financial Institutions for the Bancassurance Analysis

I. European Banks

Company name Country

1. 3I GROUP PLC UNITED KINGDOM

2. AAREAL BANK AG GERMANY

3. AARHUS LOKALBANK DENMARK

4. ABC ARBITRAGE FRANCE

5. AFFINE FRANCE

6. AGEAS NV NETHERLANDS

7. AGEAS SA/NV BELGIUM

8. ALANDSBANKEN ABP - BANK OF ALAND PLC FINLAND

9. ALLIANCE TRUST PLC UNITED KINGDOM

10. ALLIED IRISH BANKS PLC IRELAND

11. ALTAREA FRANCE

12. AMAGERBANKEN, AKTIESELSKAB DENMARK

13. AMANDA CAPITAL PLC FINLAND

14. APULIA PRONTOPRESTITO SPA ITALY

15. ATTICA BANK SA - BANK OF ATTICA SA GREECE

16. AVANZA BANK HOLDING AB SWEDEN

17. BAADER BANK AG GERMANY

18. BAILLIE GIFFORD SHIN NIPPON PLC UNITED KINGDOM

19. BANCA FINNAT EURAMERICA SPA ITALY

20. BANCA GENERALI SPA - GENERBANCA ITALY

21. BANCA IFIS SPA ITALY

22. BANCA POPOLARE DELL'EMILIA ROMAGNA ITALY

23. BANCA POPOLARE DI SONDRIO SOCIETA COOPERATIVA PER

AZIONI

ITALY

24. BANCA POPOLARE DI SPOLETO SPA ITALY

25. BANCA PROFILO SPA ITALY

26. BANCO DE VALENCIA SA SPAIN

27. BANCO DI SARDEGNA SPA ITALY

28. BANCO ESPANOL DE CREDITO SA, BANESTO SPAIN

29. BANCO ESPIRITO SANTO SA PORTUGAL

30. BANCO POPOLARE ITALY

31. BANCO POPULAR ESPANOL SA SPAIN

2012 AsFA ID: 10145

27

32. BANIF SGPS SA PORTUGAL

33. BANK FUER TIROL UND VORARLBERG AG - BTV (3 BANKEN

GRUPPE)

AUSTRIA

34. BANK OF GREECE GREECE

35. BANK OF IRELAND IRELAND

36. BANKERS INVESTMENT TRUST PLC UNITED KINGDOM

37. BANKNORDIK P/F DENMARK

38. BANKVEREIN WERTHER AG GERMANY

39. BANQUE DE LA REUNION FRANCE

40. BANQUE NATIONALE DE BELGIQUE - NATIONALE BANK VAN

BELGIE

BELGIUM

41. BANQUE TARNEAUD FRANCE

42. BARCLAYS PLC UNITED KINGDOM

43. BAUSPARKASSE MAINZ AG BKM GERMANY

44. BERLIN-HANNOVERSCHEN HYPOTHEKENBANK AG - BERLIN

HYP

GERMANY

45. BINCKBANK NV NETHERLANDS

46. BKS BANK AG AUSTRIA

47. BOURSORAMA FRANCE

48. BRAIT SA LUXEMBOURG

49. BREWIN DOLPHIN HOLDINGS PLC UNITED KINGDOM

50. BRITISH ASSETS TRUST PLC UNITED KINGDOM

51. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL

ATLANTIQUE VENDEE - CREDIT AGRICOLE ATLANTIQUE

VENDEE

FRANCE

52. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL BRIE

PICARDIE - CREDIT AGRICOLE BRIE PICARDIE

FRANCE

53. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL

D'ALPES-PROVENCE - CREDIT AGRICOLE ALPES PROVENCE

FRANCE

54. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL DE LA

TOURAINE ET DU POITOU - CREDIT AGRICOLE DE LA

TOURAINE ET DU POITOU

FRANCE

55. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL DE

L'ILLE-ET-VILAINE - CREDIT AGRICOLE DE

L'ILLE-ET-VILAINE

FRANCE

56. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL DE

NORMANDIE-SEINE

FRANCE

57. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL DE PARIS FRANCE

2012 AsFA ID: 10145

28

ET D'ILE-DE-FRANCE - CREDIT AGRICOLE D'ILE-DE-FRANCE

58. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL DU

MORBIHAN - CREDIT AGRICOLE DU MORBIHAN

FRANCE

59. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL LOIRE

HAUTE-LOIRE - CREDIT AGRICOLE LOIRE HAUTE-LOIRE

FRANCE

60. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL NORD DE

FRANCE - CREDIT AGRICOLE NORD DE FRANCE

FRANCE

61. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL SUD

RHONE -ALPES - CREDIT AGRICOLE SUD RHONE ALPES

FRANCE

62. CAISSE REGIONALE DE CREDIT AGRICOLE MUTUEL

TOULOUSE 31 - CREDIT AGRICOLE MUTUEL TOULOUSE 31

CCI

FRANCE

63. CAJA DE AHORROS DEL MEDITERRANEO CAM SPAIN

64. CATTLES PLC UNITED KINGDOM

65. CLOSE BROTHERS GROUP PLC UNITED KINGDOM

66. COFITEM – COFIMUR FRANCE

67. COMDIRECT BANK AG GERMANY

68. COMMERZBANK AG GERMANY

69. COMPAGNIE FINANCIERE MARTIN-MAUREL FRANCE

70. CONAFI PRESTITO SPA ITALY

71. CONCORD INVESTMENTBANK AG GERMANY

72. CREDIT FONCIER ET COMMUNAL D'ALSACE ET DE LORRAINE

(BANQUE) - CFCAL BANQUE

FRANCE

73. CREDIT INDUSTRIEL ET COMMERCIAL - CIC FRANCE

74. CREDITO ARTIGIANO ITALY

75. CREDITO BERGAMASCO ITALY

76. CREDITO VALTELLINESE SOC COOP ITALY

77. DAB BANK AG GERMANY

78. DEUTSCHE BANK AG GERMANY

79. DEUTSCHE POSTBANK AG GERMANY

80. DJURSLANDS BANK A/S DENMARK

81. DUNEDIN ENTERPRISE INVESTMENT TRUST PLC UNITED KINGDOM

82. DVB BANK SE GERMANY

83. EDINBURGH INVESTMENT TRUST PLC (THE) UNITED KINGDOM

84. EIK BANKI P/F DENMARK

85. ELECTRA PRIVATE EQUITY PLC UNITED KINGDOM

86. ERSTE GROUP BANK AG AUSTRIA

2012 AsFA ID: 10145

29

87. ESPIRITO SANTO FINANCIAL GROUP S.A. LUXEMBOURG

88. EUROSIC FRANCE

89. EVOLUTION GROUP PLC (THE) UNITED KINGDOM

90. EXOR SPA ITALY

91. FALA FRANCE

92. FINIBANCO HOLDING SGPS SA PORTUGAL

93. FOREIGN & COLONIAL INVESTMENT TRUST PLC (THE) UNITED KINGDOM

94. GRENKELEASING AG GERMANY

95. GROUPE BRUXELLES LAMBERT BELGIUM

96. HOLDINGSELSKABET AF 1958 A/S DENMARK

97. HORNBLOWER FISCHER AG GERMANY

98. HQ AB SWEDEN

99. HSBC TRINKAUS & BURKHARDT AG GERMANY

100. HVIDBJERG BANK AKTIESELSKAB DENMARK

101. ICAP PLC UNITED KINGDOM

102. IDB HOLDINGS SA LUXEMBOURG

103. IKB DEUTSCHE INDUSTRIEBANK AG GERMANY

104. IMMOFINANZ AG AUSTRIA

105. INITIATIVE & FINANCE INVESTISSEMENT SA FRANCE

106. INSTITUT REGIONAL DE DEVELOPPEMENT DE LA REGION

NORD PAS-DE-CALAIS - I.R.D. NORD PAS-DE-CALAIS

FRANCE

107. INTERMEDIATE CAPITAL GROUP PLC UNITED KINGDOM

108. INTERNATIONAL PERSONAL FINANCE PLC UNITED KINGDOM

109. INVESTEC PLC UNITED KINGDOM

110. IPG INVESTMENT PARTNERS GROUP

WERTPAPIERHANDELSBANK AG

GERMANY

111. IW BANK SPA ITALY

112. JUPITER PRIMADONA GROWTH TRUST PLC UNITED KINGDOM

113. JYSKE BANK A/S (GROUP) DENMARK

114. KAS BANK NV NETHERLANDS

115. KREDITBANKEN A/S DENMARK

116. LAAN & SPAR BANK A/S DENMARK

117. LANDESBANK BERLIN HOLDING AG - LBB HOLDING AG GERMANY

118. LANG & SCHWARZ WERTPAPIERHANDELSBANK AG GERMANY

119. LOCINDUS FRANCE

120. LONDON CAPITAL GROUP HOLDINGS PLC UNITED KINGDOM

121. MAN GROUP PLC UNITED KINGDOM

2012 AsFA ID: 10145

30

122. MARFIN INVESTMENT GROUP GREECE

123. MAX BANK A/S DENMARK

124. MEDIOBANCA SPA ITALY

125. MERCANTILE INVESTMENT TRUST PLC (THE) UNITED KINGDOM

126. MERKUR-BANK KGAA GERMANY

127. MITTEL SPA ITALY

128. MOENS BANK A/S DENMARK

129. MONKS INVESTMENT TRUST PLC UNITED KINGDOM

130. MURRAY INTERNATIONAL TRUST PLC UNITED KINGDOM

131. MWB FAIRTRADE WERTPAPIERHANDELSBANK AG GERMANY

132. NOERRESUNDBY BANK A/S DENMARK

133. NORDAKTIENBANK AG GERMANY

134. NORDEA BANK AB (PUBL) SWEDEN

135. NORDFYNS BANK DENMARK

136. NORDJYSKE BANK A/S DENMARK

137. NORDNET AB SWEDEN

138. NORTHERN 2 VCT PLC UNITED KINGDOM

139. NORTHERN 3 VCT PLC UNITED KINGDOM

140. NORTHERN AIM VCT PLC UNITED KINGDOM

141. NORTHERN INVESTORS COMPANY PLC UNITED KINGDOM

142. NORTHERN VENTURE TRUST PLC UNITED KINGDOM

143. NORVESTIA OYJ FINLAND

144. OBERBANK AG AUSTRIA

145. OESTERREICHISCHE VOLKSBANKEN AG AUSTRIA

146. OESTJYDSK BANK A/S DENMARK

147. PACIFIC HORIZON INVESTMENT TRUST PLC UNITED KINGDOM

148. PARAGON GROUP OF COMPANIES PLC UNITED KINGDOM

149. PARIS ORLEANS SA FRANCE

150. POLAR CAPITAL TECHNOLOGY TRUST PLC UNITED KINGDOM

151. PROTON BANK S.A. GREECE

152. QUIRIN BANK AG GERMANY

153. RAIFFEISEN INTERNATIONAL BANK-HOLDING AG AUSTRIA

154. RATHBONE BROTHERS PLC UNITED KINGDOM

155. RINGKJOEBING LANDBOBANK DENMARK

156. RIT CAPITAL PARTNERS PLC UNITED KINGDOM

157. ROBECO NV NETHERLANDS

158. SALLING BANK A/S DENMARK

2012 AsFA ID: 10145

31

159. SCHRODERS PLC UNITED KINGDOM

160. SCOTTISH INVESTMENT TRUST PLC UNITED KINGDOM

161. SIIC DE PARIS FRANCE

162. SIIC DE PARIS 8EME FRANCE

163. SINO AG GERMANY

164. SKJERN BANK DENMARK

165. SPAR NORD BANK DENMARK

166. SPARBANK A/S DENMARK

167. SPAREKASSEN FAABORG A/S DENMARK

168. SPAREKASSEN HIMMERLAND DENMARK

169. SPAREKASSEN HVETBO DENMARK

170. SPAREKASSEN LOLLAND DENMARK

171. STANDARD CHARTERED PLC UNITED KINGDOM

172. SVENDBORG SPAREKASSEN A/S DENMARK

173. SYDBANK A/S DENMARK

174. THROGMORTON TRUST PLC UNITED KINGDOM

175. TOENDER BANK A/S DENMARK

176. TOSCANA FINANZA SPA ITALY

177. TOTALBANKEN A/S DENMARK

178. TRADEGATE AG WERTPAPIERHANDELSBANK GERMANY

179. TULLETT PREBON PLC UNITED KINGDOM

180. UMWELTBANK AG GERMANY

181. UNION FINANCIERE DE FRANCE BANQUE FRANCE

182. VAN DER MOOLEN HOLDING NV NETHERLANDS

183. VAN LANSCHOT NV NETHERLANDS

184. VARENGOLD WERTPAPIERHANDELSBANK AG GERMANY

185. VESTFYNS BANK A/S DENMARK

186. VESTJYSK BANK A/S DENMARK

187. VIEL & COMPAGNIE FRANCE

188. VINDERUP BANK A/S DENMARK

189. VOLKSBANK VORARLBERG E.GEN. AUSTRIA

190. VORDINGBORG BANK A/S DENMARK

191. WIENER PRIVATBANK SE AUSTRIA

192. WITAN INVESTMENT TRUST PLC UNITED KINGDOM

2012 AsFA ID: 10145

32

II. Life insurance Company

Company name Country

1. AXA FRANCE

2. GENERALI ASSICURAZIONI SPA ITALY

3. ALLIANZ SE GERMANY

4. MüNCHENER RüCKVERSICHERUNGS-GESELLSCHAFT

AKTIENGESELLSCHAFT GERMANY

5. AVIVA PLC UNITED KINGDOM

6. CNP ASSURANCES FRANCE

7. PRUDENTIAL PLC UNITED KINGDOM

8. AEGON NV NETHERLANDS

9. MAPFRE SA SPAIN

10. GENERALI DEUTSCHLAND HOLDING AG GERMANY

11. FONDIARIA - SAI SPA ITALY

12. PREMAFIN FINANZIARIA SPA ITALY

13. HANNOVER RüCKVERSICHERUNGS-AKTIENGESELLSCHAFT GERMANY

14. MEDIOLANUM SPA ITALY

15. UNIPOL GRUPPO FINANZIARIO SPA ITALY

16. VIENNA INSURANCE GROUP - WIENER STäDTISCHE

VERSICHERUNG AG AUSTRIA

17. SCOR SE FRANCE

18. LEGAL & GENERAL GROUP PLC UNITED KINGDOM

19. UNIQA VERSICHERUNGEN AG AUSTRIA

20. SOCIETà CATTOLICA DI ASSICURAZIONE COOP. ARL ITALY

21. STANDARD LIFE PLC UNITED KINGDOM

22. OLD MUTUAL PLC UNITED KINGDOM

23. MILANO ASSICURAZIONI SPA ITALY

24. NüRNBERGER BETEILIGUNGS-AKTIENGESELLSCHAFT GERMANY

25. GRUPO CATALANA OCCIDENTE SA SPAIN

26. TOPDANMARK A/S DENMARK

27. RHEINLAND HOLDING AG GERMANY

28. VITTORIA ASSICURAZIONI SPA ITALY

29. FOYER SA LUXEMBOURG

30. ASPIS PRONIA GENERAL INSURANCE COMPANY SA GREECE

31. RESOLUTION LIMITED UNITED KINGDOM

32. ST. JAMES'S PLACE PLC UNITED KINGDOM

2012 AsFA ID: 10145

33

III. Nonlife Insurance Company

Company name Country

1. RSA INSURANCE GROUP PLC UNITED KINGDOM

2. TRYG AS DENMARK

3. BRIT INSURANCE HOLDINGS N.V. NETHERLANDS

4. AMLIN PLC UNITED KINGDOM

5. EULER HERMES FRANCE

6. BEAZLEY PLC IRELAND

7. CHAUCER HOLDINGS PLC UNITED KINGDOM

8. FLAGSTONE REINSURANCE HOLDINGS SA LUXEMBOURG

9. ADMIRAL GROUP PLC UNITED KINGDOM

10. NOVAE GROUP PLC UNITED KINGDOM

11. MANNHEIMER AG HOLDING GERMANY

12. FBD HOLDINGS PLC IRELAND

13. PERSONAL GROUP HOLDINGS PLC UNITED KINGDOM

14. RANDALL & QUILTER INVESTMENT HOLDINGS PLC UNITED KINGDOM

IV. Insurance Broker

Company name Country

1. APRIL GROUP SA FRANCE

2. JARDINE LLOYD THOMPSON GROUP PLC UNITED KINGDOM

3. CHARLES TAYLOR CONSULTING PLC UNITED KINGDOM

4. AI CLAIMS SOLUTIONS PLC UNITED KINGDOM

5. COBRA HOLDINGS PLC UNITED KINGDOM

6. CBG GROUP PLC UNITED KINGDOM

7. VERSIKO AG GERMANY