A Comparison of Bancassurance Sales with an Insurer’s Own Team:
the Taiwan
Experience
Da Han Chung,
Yen Lin Hung,
Yu Hsuang Lee,
Jun Min Wang
Department of Risk mamagement and Insurance, Shih Chien University, Taipei, Taiwan
Abstract
The bancassurance model for financial firms has become more important for Taiwan’s financial services industry since
passage of the Merger Law of Financial Institutions and the Financial Holding Company Law in 2000 and 2001, respectively.
Banking networks represent the major distribution channel for life insurance products in Taiwan. Studies on bank-insurance
consolidation report that bancassurance is a profitable strategy for a bank, but there is no definitive answer on whether insurers
gain benefits or cost advantages in selling insurance products through a bancassurance channel. No research has yet focused on
comparing the efficiency among different channels when selling insurance products. To fill the research gap, this study
concentrates on bancassurance formed through the creation of subsidiaries and compares the efficiency of this model to the
traditional insurance selling channels in Taiwan.
The Data Envelopment Analysis (DEA) approach was employed to compute the efficiencies of bancassurance and traditional
channels separately. The findings are:
 The efficiency score of a life insurance company’s own sales representatives is significantly higher than that of its
bancassurance representatives.
 The efficiency relationship between the bancassurance channel and the traditional selling channel is independent.
 A marketing efficiency evaluation of a life insurance company, when divided into different marketing channels for
evaluation, is capable of providing meaningful results for marketing decision-makers.
Key words: bancassurance; efficiency; Data Envelopment Analysis
Introduction
By definition, bancassurance is simply a method of distributing insurance products. It is a global movement that is gradually
breaking down the traditional barriers between the various businesses of supplying financial products and services (Benoist,
2002).
The last 15 years have witnessed many changes in the organization of the financial services industry in Europe, the US, and
Latin America, particularly the closer integration of banks and insurers. For example, bancassurance is highly developed in France
where banking networks account for a significant proportion of life insurance sales, although they are taking longer to make
inroads into the non-life market (Benoist, 2002). In the UK, the emergence of the phrase "financial services” reflects the
breakdown of old barriers between banking and insurance and their replacement by integrated institutions offering a range of
services (Morgan, 1994; Salomon, 1990). In the US, deregulation under the Gramm-Leach-Bliley Act (GLBA) of 1999 legalized
bancassurance and is likely to lead to its geographic spread. The new law allows the formation of financial holding companies that
can offer a wide range of financial activities, including underwriting and selling insurance and securities, commercial and
merchant banking, investing in and developing real estate, and other financial activities (Field, Froser, and Kolarl, 2007).
Bancassurance is also highly developed in Argentina, while large banks play an important role in distributing insurance products
in Brazil, also. Bancassurance is a growing sector in Mexico due to the role banks played in the creation of pension funds
following the 1997 pension reform. Joint ventures between local and foreign insurance companies were common prior to 2000,
and foreign insurers have established many partnerships with Mexican banks (Benoist, 2002).
1
The bancassurance model for financial firms has become more important for
Taiwan’s financial services industry since
passage of the Merger Law of Financial Institutions and the Financial Holding Company Law in 2000 and 2001. Based on these
two laws, insurance companies, banks, and securities firms can affiliate under common ownership and cross-sell financial
products and services to existing and potential customers.
Another reason for the progress of bancassurance business in Taiwan is the “over-banking” problem. Banks were owned
mostly by the Taiwan government before 1991 (Chen and Yeh, 1998). Due to private local and foreign banks entering the Taiwan
market after the Commercial Bank Establishment Promotion Decree in 1991, the banking environment changed substantially. The
Decree, which acted as a deregulation trigger, set off the over-banking problem. In order to eliminate the over-capacity and
diseconomies from over-banking, other non-traditional businesses, such as bancassurance, became the new trend in Taiwanese
bank operations. But in order to enter the insurance market rapidly and build marketing channels cost-effectively, new insurance
entrants followed the bancassurance strategy.
The banking industry in Taiwan has experienced tremendous change and increased growth in earnings from insurance
products. Banking networks represent the major distribution channel for life insurance products. According to a report by the
Financial Supervisory Commission of the Republic of China, bancassurance accounted for 34.41 percent of total first year life
insurance premium income in Taiwan as of 2007, behind insurance companies’ own sales teams’ revenue of 60.17 percent but
ahead of brokers and general agents at 3.76 percent. The number of insurance sales representatives employed by agencies and
brokerages tripled to about 142,000. The increased number of agencies and brokerages affiliated with banks account for 70
percent of all new entries. The growth rate of insurance premiums from these banking agents now exceeds that from traditional
underwriters of insurers.
Before 2002, the model of an insurance selling channel was “leveraged life distribution,” where the life insurance company
took the lead in the channel (Flur, Huston, and Lowie, 1997). The main protagonist under this scenario was a large life insurance
company with a range of effective distribution channels, including insurance companies, their own sales representative, general
agencies, and independent agencies or brokerages. According to the data reported by the Taiwan Insurance Institute (TII), from
1995 to 2001 less than 1.5 percent of total premium income came from agencies and brokerages. The remaining premiums were
earned through insurance companies’ own sales representatives. After deregulation and bancassurance emerged in 2002, the
primary model of insurance selling channel in Taiwan changed to leveraged bank distribution. This model requires a large bank
with a range of effective distribution channels, including branches, mail, phone, ATMs, and a trust sales force.
Even though deregulation has effectively removed the restrictions on combining banking and insurance, banks in Taiwan are
prohibited from directly distributing insurance products over their branch network. Insurance companies are not permitted to offer
banking activities directly in insurance companies either. However, according to the report of the Financial Supervisory
Commission in 2007, over 80 percent of banks formed alliances with insurance agencies or brokerages and usually have 100
percent ownership of their agency or brokerage subsidiaries. The bancassurance business practices of Taiwanese banks clearly
differ from those of universal-type financial firms that provide a range of financial products or services within the same firm.
Bancassurance activities can be formed by several corporate strategies of banks and insurance companies. According to the
OECD (1992), for banks the main structural operations for bancassurance may take the form of minority or majority holdings,
full-fledged acquisition, creation of subsidiaries, or joint ventures with holding companies. Due to the importance of
bancassurance mergers to both the European and the American financial systems (Fields, Froser, Kolarl, 2007), most studies deal
with bancassurance formed through mergers and acquisitions (M&A) and transactions (e.g., Carow, 2001; Fields, Froser, Kolarl,
2007; Boubakri, Dionne, Tri Ki, 2008). Few researchers have explored efficiency in alternative structural operation strategy where
bancassurance products from a bank
subsidiary are considered in-house products (OECD, 1992) (see Figure 1).
2
Prior empirical studies mainly evaluate the efficiency of bancassurance in banks independently. Mckillop, Glass, and
Morikawa (1996) investigated the cost efficiency of large Japanese banks and found that different cost function specifications led
to different results. Bergendahl (1995) claimed that the economic reasons for banks selling multiple products include efficiently
using fixed capacity resources, customer demand for several products from a single channel, and product combination strategy. No
research has yet compared the efficiency between different insurance product channels. To fill this research gap, this study focuses
on the bancassurance model formed through creation of subsidiaries and compares the efficiency of this model to that of
traditional insurance channels in Taiwan. This study employed the Data Envelopment Analysis (DEA) approach to compute the
efficiencies of bancassurance (through creation of subsidiaries) and traditional channels (through an insurer’s own sales
representatives) separately.
The empirical results confirm the efficiency of both bancassurance channels through subsidiaries and traditional selling
through an insurer’s own sales representatives in Taiwan. By comparing the efficiency between these two different insurance
selling channels, the marketing decision-maker in life insurance companies can make a more informed choice of selling channel
Literature Review
Background on Efficiency Measurement
Management defines efficiency (or cost-efficiency) either as a characteristic of organizational outputs (“effectiveness”,
‘equity”, “quality”, etc) or inputs (“economy”, “cost”) or as a relationship between outputs and inputs (Meimand, Cavana, and
Laking, 2002). In each case, efficiency can be viewed as a transformation ratio: “what has been produced or the value of what has
been produced per unit of what has been consumed, or the value of what has been consumed in the process of production” (Kao
and Hwang, 2007).
The efficiency measurement has been applied to numerous fields over the past few years, including marketing (e.g., Keh,
Chu, and Xu, 2006; Wu, 2003), athletic (e.g., Garcia-Sanchez, 2007), technology (e.g., Jerzmanowski, 2007), information systems
(e.g., Gebauer and Schober, 2006; Philip, 2007), public policy (e.g., Durlauf, 2005;
Vine, Hamrin, Eyre, Crossley, Maloney, ,
and Watt. 2003), banking efficiency (e.g., McCune, 2007; Yao, et al. 2007), bancassurance, and even insurance.
The Efficiency of Bancassurance
Many studies of bancassurance focused on benefits or enhanced value in bank-insurance consolidation. Bergendahl (1995)
claimed that the economic reasons for banks selling multiple products include efficiently using fixed capacity resources, customer
demand for several products from a single channel, and product combination strategy .In contrast, early research findings of
Baumol, Panzar, and Willing (1982) implied that there was no benefit from bank-insurance consolidation for existing insurance
companies. But Diamond (1984) proposed that spanning both short-term and long-term liability/asset structures in the financial
intermediation process and attracting and keeping individual customers and corporate clients better make bank-insurance
consolidation beneficial to both insurers and banks. Other studies of the effect of bank expansion into non-traditional industries
mainly focus on the risk reduction and value enhancement effects of bank consolidation (e.g., Hughes, Lang, Mester, and Moon,
1999; Carow, 2001; Mamun, Hassan, and Maroney, 2005). Saunders and Walter (1994) and Hughes, Lang, Mester, and Moon
(1999) show that bank consolidation is consistent with risk reduction. Felgren (1985) argued that banks had greater cost
advantages in selling insurance products than insurance companies because of offices and so forth. Carow (2001) found that bank
3
stock prices after bank entry into the insurance industry do not change significantly.
Most early research results about bancassurance agreed that banks gained benefits or cost advantages in bank-insurance
consolidation, but the findings were not consistent when they looked at insurers’ benefits from the bancassurance. The studies on
bank-insurance consolidation revealed no consensus on whether bancassurance would be a profitable strategy to an insurance
company. There were also many studies on the efficiency of insurance companies which evaluated the performance of various
insurance business activities.
The Efficiency of Insurers
Many studies employed the traditional Data Envelopment Analysis (DEA) to explore the efficiency of insurers’ business
activities (see Figure 2). Pree and Chauncey (1995) utilized the DEA to help insurance companies monitor and control legal
service and costs. Cummis, Tennyson, and Weiss (1999) used the DEA to examine the relationship among mergers and
acquisitions, efficiency, and economies of scale in the US life insurance industry over the period 1988-1995. They found that
acquired firms achieve greater efficiency gains than firms that have not been involved in mergers or acquisitions. Lin (2002)
applied the DEA to measure efficiency scores and to examine whether life insurers in Taiwan have fully recognized the new
market structure after deregulation. Results showed no change for overall efficiency, no pure technical efficiency change, and no
scale efficiency change after deregulation. Mahlberg and Url (2003) analyzed a panel of Austrian insurance companies over the
period 1992 through 1999 to assess the response to the challenges of the single market for the insurance industry by means of the
DEA. Their efficiency measure is likely to identify such insurance companies as inefficient compared to other companies,
although these companies may offer favorable terms to consumers. Tone and Sahoo (2005) applied the DEA model to examine the
performance of the Life Insurance Corporation of India and found a significant difference in the cost efficiency scores over the
period 1994-2001. Brockett et. al. (2005) used the DEA coupled with distribution-free rank-order statistics to study the relative
efficiency of the different organizational structures used by US property and liability insurance companies. Meimand, Cavana, and
Laking (2002) described a modified DEA process to solve the problem of assessing relative branch performance in the Accident
Compensation Corporation, the New Zealand state-owned, no-fault, personal injury compensation insurance company. The factors
in their DEA inputs were rehabilitation and compensation costs and number of full-time cases and claims managers in the branch.
On the output side, the factors included right the first time, number of claimants managed starting each month, number of
claimants starting each month expected to have left in less than 12 months, and number of weekly compensation payments
meeting the target dates. Yao, Han, and Feng (2007) used a panel data set of 22 insurance companies over the period 1999-2004 to
evaluate their efficiency by applying a DEA approach. In their study, labor and capital were input factors while premium, benefits
and claims costs were output factors to measure the efficiency of insurance companies. Similarly, by using the DEA approach,
Jeng et al. (2007) examined the efficiency changes of US life insurers before and after demutualization in the 1980s and 1990s.
The inputs used in their model were labor, business service, eEquity cost, assets and underwriting and investment expenses. On
the output side, the factors included benefit payments and return on assets.
To gain valuable managerial insights for insurers, the latest studies used a modified DEA approach to evaluate the efficiency
4
of an insurance company. Hwang and Kao (2006) and Kao and Hwang (2007) modified the conventional DEA by taking into
account the series of relationships of the two sub-processes within the whole process (see Figure 3). The relational model
developed in their papers was more reliable in measuring the efficiencies and could identify the causes of inefficiency more
accurately. The inputs used in the first stage are operating expense and insurance expense. The outputs of the system, which were
also the outputs of the second stage, are underwriting profits and. investment profits. There were also two intermediate products in
the system, which were the outputs of the first stage as well as the inputs of the second stage: direct written premiums and
reinsurance premiums. Wu et al. (2007) and Yang (2005) employed a two-stage DEA approach to assess production and
investment efficiency simultaneously for the Canadian life and health insurance industry. This model allowed integration of the
production and investment performance for the insurance companies, provided management with an overall performance
evaluation and suggested how to achieve efficiency systematically for the insurers involved. The input factors in their DEA model
were labor expense, general operating expense, capital equity and claims incurred. The outputs were net premiums written and net
income.
Summary of Literature Review
Previous studies of bank-insurance consolidation reported that bancassurance is a profitable strategy to a bank, but there is
no consensus on whether insurers gain benefits or cost advantage in selling insurance product through bancassurance channels.
Early studies on the efficiency of insurance, no matter what stage they evaluated, did not focus on insurance marketing
channels, nor did they mention the efficiency comparison between direct and indirect marketing channels (see Figure 4).
5
The inputs and outputs used for evaluating the efficiency of insurance companies in prior studies are reported in Table 1.
Accordingly, this study selects some appropriate inputs and outputs to assess the efficiency of traditional selling channels and
bancassurance channels
Table 1: The Inputs and Outputs Used for Evaluating the Efficiency of Insurance Companies
Methodology
The DEA Methodology
According to the concept of efficiency for the performance evaluation method, the main comparison is between input-output
relations. The DEA efficiency assessment model used envelope line technology to replace the general economics of individual
production function, whose basic theory was based on Farrell’s work (1957) on the concept of technical efficiency. Three scholars
(Charnes, Cooper and Rhodes,1978) expanded the single input single output model to the concept of multiple inputs-multiple
outputs, creating a form to assess the decision-making units’ relative efficiency. This can use non-identical units for a number of
inputs and outputs various renovation to a single value, which was obtained for a value prefecture institutions organizational
efficiency, commonly known as CCR model.
This study used the CCR model to measure the decision-making units’ (DMU) operating efficiency. The theoretical
description follows:
6
Charnes et al. (1978), following
Farrell (1957), assessed the efficiency of the theoretical basis, through two inputs, the
outputs of a single model, and expand to multiple inputs and multiple outputs model, the fixed pay scale under the assumption that
using linear programming method, the production border, and to assess each unit for the relative efficiency, the law is known as
the DEA model CCR. Suppose k DMUs, each DMU k（k=1,⋯ ,N）, using the m input species  ik （i=1,⋯,m；k=1,⋯,N）＞0,
production n outputs y rk （r=1,⋯,s；k=1,⋯,N）＞0, as can be in a DMU k expected that the efficiency values are :
n
u y
r
Max
Hk =
rk
r=1
m
v 
i
ik
i=1
n
u y
r
subject to
Hk =
rk
r=1
m
v 
i
1
(1)
ik
i=1
y rk ：amount of the r th output for the k th DMU；
 ik ：amount of the i th input for the k th DMU；
u r ：the weight assigned to the r th output；
v i ：the weight assigned to the i th input；

: Non-Archimedean Quantity, is arbitrary small positive values
Because
the scores-planning (Fractional Programming) model is not easy to solve, Charnes et al., (1978) converted it to
the linear programming (Linear Programming) model:
n
H k =  u r y rk
Max
r=1
n
subject to
m
 u y - v 
r
rk
r=1
i
0
ik
(2)
i=1
u r ,vi   > 0 ; i=1,
,m ; r=1,
,n ; k=1,
,N
Formula (2) in the input items portfolio weighted average value of the one cases, the items for output weighted average
portfolio maximum efficiency is used to indicate the relative value. But its limitations - the number (n + k + m + l) - was
significantly more than the number of variables (n + k), can use dual conversion pairs (duality) mode, reducing restrictions on the
number of convenience-type solution, as follows:
n
 m

Min H k = k -   Sik- + Srk+ 
r=1
 i=1

N
 
subject to
k
ik
- k  ik +Sik- =0
k=1
N

k 1
k
1
N
 
k
ik
-Srk+ = y rk
(3)
k=1
 , k , Sik- , Srk+  0 ; i=1,
-
+
Formula (3) Sik , Sik and
,m ; r=1,
,n ; k=1,
,N,  unconstrained
k for all DMU and the best allocation of DMU combination of linear equations, the weights θ
-
+
efficiency of a practical value. Sik and Sik are the input and output variables variance, the representative of the actual value
and the best efficiency of the difference between the value that can be used to understand the inputs and outputs of the number of
7
-
+
rooms for improvement. When θ = 1, Sik = Sik = 0, the DMU stayed relatively efficient. When DMU relative efficiency, and
can be adjusted through the following and achieving optimum efficiency goals:
ik* = k* ik -Sik-*
y*rk =y rk +Srk+*
(4)
Defining Input- Output Factors in DEA Model
The input-output factors used in this paper are in Table 2.
Results and Conclusions
Based on (2) and (3), an evaluation of input-output information published in the “Life Insurance Review of Republic of
China” by the Taiwan Insurance Institute (TII) was conducted. The input-output data of traditional selling channels and
bancassurance channels are shown in Tables 3 and 4. Results, including efficiency scores and rankings of the traditional selling
channels and the bancassurance channels evaluated by the DEA method, are shown in Table 5.
8
9
There are nine life insurance companies that are relatively efficient in
traditional selling channels: Global Life, ING Life,
Life Insurance Dept. of CTC, China Life, Shin Kong Life, Global Life, Sinon Life, Singfor Life, and Allianz President Life. The
two life insurance companies which are relatively efficient in bancassurance channels are Cathey Life, and Allianz President Life.
Some life insurance companies such as Global Life, ING Life, and Singfor Life, may be relatively efficient in traditional selling
channels but perform poorly in bancassurance channels. Cathey Life is the only life insurance company that performs relatively
efficiently in bancassurance channels but poorly in the traditional selling channels. There are six life insurance companies that
perform equally poorly in both the traditional and bancassurance channels: New York Life, Manulife Limited (Taiwan Branch),
Nan Shan Life, MassMutual Mercuries Life, and Hontai Life. The only life insurance company that performs relatively efficiently
in both traditional and bancassurance channels is Allianz President Life.
10
The researchers conducted the Mann-Whitney U test and the Spearman Rank Correlation test to determine whether there is a
significant difference between inefficiency score and rank between traditional and bancassurance channels. Table 6 shows that
there is a significant efficiency score difference between the traditional and the bancassurance marketing channels (U = 87.00, p =
0.001 < 0.05). The efficiency mean of the traditional channel is higher than that of the bancassurance channel. Table 7 shows the
Spearman’s Rank correlation statistics, which indicate that there is no efficiency rank relationship for the 21 life insurance
companies between the bancassurance and the traditional channels (p = .170 > 0.05).
Table 6: Mann-Whitney U Test of Efficiency Comparison in the Traditional Selling and Bancassurance Channel
Efficiency Score Mean
Std. Dev.
Mann-Whitney U (p-value)
Traditional Selling Channel
0.7620
0.26038
87.000
Bancassurance Channel
0.4198
0.32835
(0.001)
Table 7: Spearman’s Rank Correlation Coefficients of Efficiency in the Traditional Selling and the Bancassurance Channel
Traditional Selling Channel – Bancassurance Channel
Spearman's rho
.311
p-value
.170
The Mann-Whitney U test (see Figure 5) and the Spearman Rank Correlation test (see Figure 6) indicate that the efficiency
of traditional selling channels is significantly higher than that of bancassurance channels. The efficiency rank of traditional selling
channels was independent of the bancassurance channel. In other words, there is no efficiency rank relationship between a life
insurance company’s own sales representatives and its bancassurance representatives in Taiwan.
Managerial Implications
This study suggests four managerial implications:
1.
The efficiency score of a life insurance company’s own sales representatives is significantly higher than that of its
11
bancassurance representatives. Companies such as ING Life , Global Life, and Singfor Life should try to improve their
bancassurance efficiency by changing the banks they partner with.
2.
The efficiency relationship between the bancassurance channel and the traditional selling channel is independent. The life
insurance companies that perform better in
traditional selling channels may not perform similarly in bancassurance channels.
From the viewpoint of insurers, how bancassurance representatives perform has nothing to do with the insurer’s own sales
team but it is related to the banks they select. Therefore, to perform better in bancassurance channels, choosing appropriate
partner banks becomes the most important factor for most of the life insurance companies in Taiwan.
3.
The
research findings suggests that a marketing efficiency evaluation of a life insurance company, when divided into
different marketing channels for evaluation, can provide meaningful results for decision-makers in determining marketing
strategies
4.
According to the report of the Insurance Institution of Taiwan (IIT) in 2007, the majority of products sold by insurers’ own
sales representatives are life insurance products. The only product that bancassurance representatives prefer to sell is
investment-linked insurance. Therefore, whether the efficiency difference in different marketing channels can be attributed to
different products sold is a topic for future research..
12
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