What are the efficiency gains of bancassurance? A two-side analysis: the banking and the insurance standpoint
Emerging Scholars in Banking and FinanceContemporary Issues in Financial Markets and Institutions
Cass Business School, London 9th December 2009Franco Fiordelisi, University of Roma Tre, Bangor Business SchoolOrnella Ricci, University of Roma Tre [email protected]
Agenda•Introduction and motivations•Literature Review•Methodology•Data and variables
▫banking side▫insurance side
•Results▫banking side▫insurance side
•Conclusions
Introduction and motivations (1)
• The development of bancassurance is the result of many factors…▫Regulatory Framework
EU Second Banking Directive, 1989 USA Gramm-Leach-Bliley Act, 1999
▫Economic rationales Drop in the interest margin from traditional banking
activity Development of life products
o progressive ageing of population in all developed countries o decrease in welfare state protection offered by governments
Existence of some similarities and complementaries between the banking and the insurance activities
Introduction and motivations (2)• Most studies dealing with bancassurance have only been
descriptive in nature (Chen et al. 2008)• Empirical analyses focus on the risk diversification
hypothesis (Boyd et al. 1993, Genetay and Molyneux 1998, Laderman 2000, Estrella 2001, Fields et al. 2005, 2008, Chen et al. 2006, Nurullah and Staikouras 2008), while cost and revenue synergies resulting in efficiency gains are still a poorly investigated issue
• The aim of this paper is to assess if bancassurance results in efficiency gains from both the banking and the insurance sides, answering the following research questions:
1) Are banks engaged in the insurance business more cost and profit efficient than their competitors specialized in traditional and investment banking?
2) Are bancassurance companies more cost and profit efficient than independent companies operating in the life business?
3) Which model of bancassurance reaches the best performance?
Literature Review (1)• Efficiency hp “banking side”
• There are no studies focussing on bancassurance in an exclusive way!
ALLEN & RAI (1996)Universal banking countries more cost efficient than separated banking countries in 1988-1992
Universal banking as combination between traditional combination between traditional and investment bankingand investment banking
VANDER VANNET (2002)Financial conglomerates more revenue efficient than specialised banks in 1995-96
Financial conglomerates as combinations between combinations between traditional and investment traditional and investment banking/insurancebanking/insurance
CASU & GIRARDONE (2004) Profit efficiency increase for Italian financial conglomerates over 1996-99
Financial conglomerates as all all Italian banking groupsItalian banking groups (experimenting a trend towards conglomeration over the observed period)
Literature Review (2)• Efficiency hp “insurance side”
• Bancassurance as a distribution channel or as equity links in a mutually exclusive way
• In other studies investigating the relationship between efficiency and distribution, bancassurance is only marginally considered (Trigo-Gamarra 2007) or completely ignored (Klumpes 2004)
HWANG & GAO (2005) Higher cost efficiency for life insurance companies using bank branches for the distribution of their productsIrish market 1991-2000
Bancassurance as a distribution channeldistribution channel
BARROS et al. (2006) Higher cost efficiency for life companies controlled by banking institutions Portuguese market 1995-2003
Bancassurance as
equity link/ownershipequity link/ownership
Literature Review (3)• We can find only one study (Verweire 1999) analysing both
sides of the phenomenon, but it is based on balance sheet ratios
• The comparison of different structures of financial alliances between banks and insurance companies has been discussed only in studies adopting a managerial point of view (Voutilainen 2005, Staikouras 2006, Lin et al. 2009)
• Overall, our paper aims to advance the existing literature by: 1) measuring potential cost and profit efficiency gains of
bancassurance from both the banking and the insurance points of view
2) dealing with bancassurance from both an ownership and a distributional perspectives
3) providing quantitative findings to compare the performance attained by different organisational models
4) analysing the unexplored case of the Italian financial industry
Methodology: base SFACost efficiency
Profit efficiencyitititititit uvxTC ,ln
- xit ln output/netput quant
and input prices
- vit ~ N(0; σv2) random error
- ui ~ N+(0; σu2) inefficiency
Comparison based on common frontiers require that all firms share the same technology and environmental conditions. In the case of sample heterogeneity, efficiency estimates can be strongly biased (Bos et al. 2005, 2008)
i jjiij
i jjiij
i jjiij
i jjj
pygppdyyc
pbyaaTPTC
lnlnlnlnlnln2
1
lnln)(ln 110
itititititit uvxTP ,ln
• It assumes that all sample firms share the same production technology, but some firm specific factors - out of the management control - influence the distance from the best practice
• The deterministic kernel of the frontier is the same as in the base model, while the inefficiency component is now assumed distributed as uit ~ N(it; σu
2), where
• Using this model we can account for the heterogeneity problem and still benchmark all firms against a common frontier. We also measure the impact of exogenous factors on efficiency without incurring in the problems of a two step procedure
Methodology: TE Model (1)
Firm specific factors
• The best predictor for single firm efficiency is the conditional expectation of uit given the observed it
• With the TE Model, we obtain gross measure of efficiency. If we want net measure, we have to substitute in the above expression *****
2** 5.0expexp itituE
it
M
jitjj z
1,0* 1
22* 1 s
222vus 22
su
M
jitjj z
1,min
…assuming that all sample firms face the same optimal exogenous conditions (minimising inefficiency)
Methodology: TE Model (2)
Data and variables “banking side” (1)• We start from the operational definition of Vander Vennet
(2002); a bank is a financial conglomerate when:▫ It is engaged in investment banking and/or insurance trough
an in-house department or a consolidated subsidiary▫ The ratio of not interest income to total revenues exceeds 20%
• We restrict these criteria in order to focus only bancassurance combinations, BC. A bank is a BC if:▫ It consolidates at least one insurance company (captive or joint
venture)▫ It has a ratio of not interest income to total revenues
exceeding 20%• Banks not satisfying these criteria are defined as a
residual cluster (Not Bancassurance-oriented Institutions, NBI) Type 2005 2006 Total
BC 23 24 47
NBI 18 15 33
Total 41 39 80
Source of financial data:ABI BANKING DATASource of data on the group structure Companies' web sites
Data and variables “banking side” (2)
• 2 different input/output specifications
DEP VARTC Total cost = interest expenses + operating expenses
TP Total profit = pre-tax profit
OUTPUT QUANT
Value added approach Value added approach Resti 1997, Fiordelisi & Molyneux 2006, Fiordelisi 2007
Y1 Total loans Y2 Other earning assets
Y3 Customer deposits
Traditional and non traditional Traditional and non traditional banking outputbanking outputRogers 1998, Vander Vennet 2002
Y1’ Interest income
Y2’ Not interest income
INPUT PRICES
P1 Price of labour = personnel expenses / n° employees
P2 Price of fixed assets = depr&amort./fixed assets
P3 Price of capital = interest expenses/(deposits + other funding)
NETPUT Z Equity
Data and variables “banking side” (3)• We choose the firm specific factors on the basis of two criteria:
▫ Influence on efficiency on the basis of theory and empirical literature▫ Significant differences in means between the two subgroups
LN_TA TCR% %INS LN_INTG
COMM LISTED
NBI_mean 15.2271 0.12034 0.0000 9.6064 0.4848 0.2121BC_mean 17.5177 0.09874 0.0297 13.1348 0.6383 0.7021diff NBI-BC -2.2905 0.0216 -0.0297 -3.5283 -0.1534 -0.4900t-stat -10.8054 2.6295 -7.3075 -9.0847 -1.3550 -4.9576p-value 0.0000 0.0126 0.0000 0.0000 0.1800 0.0000
• SIZE ln total asset (LN_TA)• RISK Total capital ratio (TCR%)• DIVERSIFICATION ratio between the book value of the insurance
companies and the consolidated equity (%INS)• INTANGIBLES ln total investment in intangibles assets (LN_INTG)• INSTITUTIONAL TYPE commercial or cooperative (COMM)• LISTING listed or unlisted institution (LISTED)
Data and variables “insurance side” (1)
Type 2005 2006 Total
CB 13 12 25
IC 49 51 100
JV 21 22 43
Total 83 85 168
Source of financial data:INFOBILASource of data on the distribution system ANIASource of data on the ownership structure Companies' web sites
• Analysing the case of Italy (4° life insurance market in Europe and 6° in the world) we dispose of detailed and reliable data provided by ANIA
• Sample composition (ownership criterion)▫ Insurance companies controlled by banks (CB)▫ Joint ventures between banking and insurance partners (JV)▫ Independent companies (IC)
Data and variables “insurance side” (2)
• In order to define input and output variables, we choose the value added approach adopted in the most recent insurance studies (e.g. Fenn et al. 2008)
DEP VAR
TC Total operating cost from the life technical account
TP Net earned premiums + investment income – total cost
OUTPUTQUANT
Y1 Claims net of reinsurance, plus bonus and rebates, plus additions to reserves
Fenn et al. 2008Trigo-Gamarra, 2007
INPUT PRICES
P1 Net operating expenses plus other technical charges/Total assets P2 Investment charges/Total assets
Bikker and Van Leuvensteijn, 2008
NETPUTZ1 Total equity capital in t-1 Fenn et al. 2008
Z2 Total technical provisions in t-1 Fenn et al. 2008
Data and variables “insurance side”(3)
• In order to overcome the heterogeneity problem, we include in the model the following firm specific factors:▫ Z1_%banc, the percentage of premiums collected by bank branches▫ Z2_MS, the market share with reference to the Italian life industry▫ Z3_%fin, the weight of policies with an high financial content (falling
into the III or the V class under the 96/1992 Directive - respectively unit/index linked and capital redemption)
▫ Z4_comp, a dummy indicating if the firm is a life specialist or a composite company
Variable
Mean Difference in means
Total CB IC JV IC-CB JV-CB JV-IC
Z1_%banc
0.4406
0.7956
0.1648
0.8758
-0.6308**
* 0.0802 0.7110*
**
Z2_MS0.011
7 0.017
7 0.007
5 0.018
2 -
0.0103** 0.0005 0.0108*
**
Z3_%fin0.494
7 0.407
3 0.433
8 0.687
1 0.0265 0.2798*
**0.2533*
**
Z4_comp
0.3452
0.0400
0.4600
0.2558 0.42*** 0.2158
-0.2042*
*
*** p value<0.01; ** p value<0.05; * p-value<0.1
Results “banking side” (1)
COST EFFICIENCY INPUT/OUPUT SPECIFICATION NBI
MEANBC
MEANT-
STATa
P-value
Value added approach 0.8134 0.8197 -0.1719 0.86Traditional and non traditional banking
output0.8951 0.893 0.0850 0.93
ALTERNATIVE PROFIT EFFICIENCYINPUT/OUPUT SPECIFICATION NBI
MEANBC
MEANT-
STATa
P-value
Traditional and non traditional banking output
0.7858 0.7356 1.1694 0.25
a Two sample t-test of differences in mean H0: mean(NBI)-mean(BC)=0 H1: mean(NBI)-mean(BC)0
COST EFFICIENCY PROFIT EFFICIENCY(value added
approach)(traditional and non traditional output)
(traditional and non traditional output)
VARIABLE COEFFICIENT COEFFICIENT COEFFICIENTLN_TA -0.483*** -0.316*** -0.217**TCR% -2.794*** -4.193* -7.908***INS% 2.432** -2.429 -5.460***
LN_INTG 0.192*** -0.0154* 0.406***COMM -0.302** -0.1755 -0.457LISTED 0.480** -0.3188** -0.077
• Results from the model including firm specific factors
Results “insurance side” (1)• Gross cost efficiency from the TE model
• Impact of firm specific factors
• Net cost efficiency from the TE model
Type Mean
Std. Dev Min Max
CB 0.939 0.033 0.876 0.974IC 0.902 0.085 0.620 0.988JV 0.953 0.034 0.830 0.985
Groups Diff. Eff(IC)-Eff(CB) -0.0368*Eff(JV)-Eff(CB) 0.0142
Eff(JV)-Eff(IC)0.051**
*Variable Coeff.Cost 0.191**Z1_
%banc -0.465**Z2_MS -6.334**Z3_%fin -0.713*Z4_comp -0.308**
Type Mean
Std. Dev Min Max
CB 0.967 0.014 0.939 0.984IC 0.946 0.066 0.698 0.990JV 0.972 0.018 0.887 0.988
Groups Diff.Eff(IC)-Eff(CB) -0.0217Eff(JV)-Eff(CB) 0.0042
Eff(JV)-Eff(IC)0.0259*
*
Results “insurance side” (2)• Gross profit efficiency from the TE model
• Impact of firm specific factors
• Net profit efficiency from the TE model
Type Mean
Std. Dev Min Max
CB 0.916 0.107 0.579 0.984IC 0.911 0.118 0.498 0.988JV 0.830 0.113 0.620 0.972
Groups Diff. Eff(IC)-Eff(CB) -0.0052Eff(JV)-Eff(CB) -0.0855**
Eff(JV)-Eff(IC)-
0.0803***Variable Coeff.
Cost-0.571***
Z1_%banc -0.136Z2_MS 3.898Z3_%fin 1.19***Z4_comp -0.298**
Type Mean
Std. Dev Min Max
CB0.9875
3 0.000810.9850
70.9887
9
IC0.9873
9 0.000770.9848
70.9889
2
JV0.9872
1 0.000760.9854
50.9889
4
Groups Diff.Eff(IC)-Eff(CB) -0.0001Eff(JV)-Eff(CB) -0.0003
Eff(JV)-Eff(IC) -0.0002
Conclusions (1)1) Are banks engaged in the insurance business more cost and profit efficient than their competitors specialized in traditional and investment banking? Bancassurance combinations (BCs) and Not Bancassurance-oriented institutions (NBIs) show very similar levels of cost and profit efficiency, under both the value added and the alternative approach used to define input and output variablesThe firm specific factor measuring diversification into the insurance business shows results very sensitive to the input and output specification. The relationship with cost efficiency is negative under the valued added approach and positive (but not significant) under the specification with traditional and non traditional banking output. Moving to the profit side we also find a positive and significant relationship between diversification in insurance and the attained performance The supposed cost and revenue synergies resulting from the alternative approach, however, are probably of a scarce magnitude or compensated by other diseconomies, given that the medium level of cost and profit efficiency is very similar for BCs and NBIs
Conclusions (2)2) Are bancassurance companies more cost and profit efficient than independent companies operating in the life business?
Considering gross efficiency scores, we find a significant cost advantage for bancassurance companies. When we observe net scores the advantage of CBs over ICs disappears while that in favor of JVs is strongly reduced, revealing that the bancassurance overperformance is mainly explained by some positive features, such as the share of premiums collected by bank branches and the proportion of high financial content policies in the business mix, that are not exclusive of insurance companies wholly or jointly owned by banks
On the profit side we do not find any strong evidence in favor of bancassurance: the relationship between the performance attained and the share of premiums collected by bank branches is still positive, but not statistically significant. The percentage of product with an high financial content is negatively related to profit efficiency in a significant way, revealing that these policies are less costly to manage than protection insurance but less profitable
Conclusions (3)3) Which model of bancassurance reaches the best
performance?Results seem to be in favor of JVs for the cost side and
present a substantial parity among sample firms on the profit side
The convenience of bancassurance as a distribution channel is relevant and consolidated while the success of insurance products with an high financial content is more volatile and strictly dependent on current market trends, requiring a continuous revision of the business mix
So the existence of ownership links is not necessarily the best strategy for the realization of cost and revenue synergies between the banking and the insurance activities and the subjects involved should consider also the alternative of more flexible and reversible forms of cooperation, such as cross selling agreements and non equity strategic alliances
The identification of the best bancassurance model probably depends also on the characteristics of the subjects involved and undoubtedly deserves further investigation
Top Related