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Bank merger and acquisitions activity in the EU much ado

Bank merger and acquisitions activity in the EU much ado
Bank merger and acquisitions activity in the EU much ado

Bank merger and acquisitions activity in the EU:much ado

about nothing?

Catarina Figueira ?and Joseph Nellis

Policy,Strategy and Performance,School of Management,Cran?eld University,Cran?eld,

Bedfordshire,MK430AL,United Kingdom

(In ?nal form 9May 2007)

This paper investigates the patterns of consolidation within the European banking

industry and examines the ef?ciency of the banks involved in the merger and

acquisitions (M&A)activity to determine whether their performance improved as a

result of M&A decisions.The performance of these banks is compared with that of

other large banks,which have chosen alternative routes of development.The period

covered is 1998to 2004.The ?ndings suggest that banks involved in M&A activity

are more ef?cient after the M&A or when compared with other large banks.

Country-speci?c characteristics appear to play an important role in explaining the

results.

Keywords:M&As;EU banking;ef?ciency

Introduction

The EU banking industry has undergone important developments over the last years,

which were driven by the introduction of new ?nancial products and processes,the estab-

lishment of the European Single Market and the globalisation of ?nancial markets

(Lindblom &van Koch,2002).In order to face the new challenges and remain competi-

tive,some banks have chosen to embark on merger and acquisitions (M&A)activity.

However,according to Hamoir,McCamish,Niederkorn,and Thiersch (2002),Europe’s

banking industry is still remarkably fragmented in comparison with other industries (it

still consists of approximately 15,000?nancial institutions).

The EU banking industry ?nds itself in a mature phase of its life cycle with impli-

cations for growth and pressures on margins.The process of consolidation is one response

of the EU industry to the current challenges.Strategic alliances are also becoming increas-

ingly important as a response to competition from traditional players and from non-

traditional providers of ?nancial products and services (Dyer,Kale,&Singh,2004;

Johnson,Scholes,&Whittington,2005)and have become an important source of

revenue growth in recent years.A third option to develop is via organic growth,which

tends to focus on the cost side of operations,as described by Johnson et al.(2005).

The ef?cacy of these measures is evidenced by the signi?cant reduction in banks’cost-

to-income ratios in the last few years.

This paper investigates the patterns of consolidation within the European banking

industry and examines the ef?ciency of the banks involved in the M&A activity to deter-

mine whether their performance improved as a result of M&A decisions.The structure

ISSN 0264-2069print/ISSN 1743-9507online

#2009Taylor &Francis

DOI:10.1080/02642060902749476https://www.doczj.com/doc/cc5465939.html,

?Corresponding author.Email:Catarina.Figueira@cran?https://www.doczj.com/doc/cc5465939.html,

The Service Industries Journal

Vol.29,No.7,July 2009,

875–886

876 C.Figueira and J.Nellis

of the paper is as follows.Section2describes the process of consolidation in the EU banking industry.It also discusses the changes that have taken place in the economic,regu-latory and political environment,which have underpinned the process of deregulation and integration of the EU banking systems.Section3presents an overview of the data and dis-cusses the patterns of M&A activity in the EU that emerge from the data.Section4 describes the statistical technique employed in this study,to assess the ef?ciency of?nan-cial institutions and provides a discussion of the main?ndings.Finally,Section5con-cludes by providing possible explanations for the results presented and it also identi?es key challenges that need to be addressed if M&A activity is to expand. Consolidation in the EU banking industry

The need to transform a highly segmented Europe into an integrated one has been recog-nised since the mid-1950s(1957Treaty of Rome).Since then,several steps have been taken aimed at the deregulation and harmonisation of the EU banking regulatory frame-work.The establishment of the European Single Market in1993was an important devel-opment because it made it possible for?nancial institutions to open branches and offer services in other EU members.Moreover,the operation of banking activities has since changed signi?cantly,with the adoption by many?nancial groups of the so-called universal banking model,as described by Nellis,McCaffery,and Hutchinson(2000).

Since then,the adherence by12EU members to the European Monetary Union has also made it possible for savers to diversify their portfolio,as a result of no exchange rate risk.This has therefore contributed to important changes in the structure of the cor-porate bond and equity markets.However,this important step towards European inte-gration has also changed the approach by?nancial institutions to the management of credit risk.Policies set by the European Central Bank may not always be adequate to all EU members and,as a consequence,?nancial institutions may need to consider an international diversi?cation of their loan portfolios.

Consideration has also been given to prudential rules and practices,as suggested by Hamoir,McCamish,Niederkorn,and Thiersch(2002).This culminated in the establish-ment of The Financial Services Action Plan,which was adopted in1999by the European Commission as an attempt to develop legislative and non-legislative frameworks required to support an optimal single?nancial market.

Finally,the2004Basel II Accord also set out minimum regulatory capital require-ments for banks(Kanbay,2005),in an attempt to minimise potential risks faced by the ?nancial system in periods of economic turbulence(Caruana,2005;Claessens, Krahnen,&Lang,2005)and therefore promote international convergence of capital measurement and capital standards.It is believed that,by encouraging the strengthening of banks’capital adequacy,these requirements are indeed promoting mergers between banks.

As a result of the above developments,the EU banking industry has been experiencing an intensi?ed phase of consolidation,particularly since the early1990s as noted by Altun-bas and Iba′n?ez(2004).While cross-border mergers are still limited in number,with the exception of Scandinavia and the Benelux countries(Boot,2003),domestic mergers, mostly between large universal banks,have played a key role in the banking industry. Examples of such mergers are the one between the Union Bank of Switzerland and Swiss Bank Corporation,another one between the National Westminster Bank and Royal Bank of Scotland and a third one between Paribas and Banque National de Paris, to name a few.

The Service Industries Journal877 In a fast changing environment,many?nancial institutions are turning to mergers and acquisitions to ensure the survival and/or growth of their businesses.The decision to con-solidate should,in principle,be motivated by the desire to increase shareholder value(Walter &Barney,1990),but it often re?ects agency con?icts between shareholders and managers,as suggested by Berkovitch and Narayanan(1993),Brouthers,van Hastenburg,and van den Ven (1998)and Berger,Demsetz,and Strahan(1999).

Bearing the above points in mind,we now turn to the investigation of the patterns of the data used in this paper.We will also describe the measures used to examine the ef?-ciency of banks that have chosen M&A activity as a route of development.

The data and performance measures

In this study,we use data for the period1998–2004,the latest year for which we could obtain adequate details on banks’balance sheets and income statements.The focus is on the performance of banks in?ve European countries:France,Germany,Italy,Spain and the UK.For completeness,we also provide a descriptive analysis of the overall pattern of M&As in Europe as a whole.

The data were drawn from two databases:Bankscope,published by the London-based International Bank Credit Analysis Ltd and SDC Platinum,published by Thomson.A number of banks(and M&As)included in the databases had to be excluded because of gaps in the statistical series.The?nal sample is composed of80M&As involving banks in2001and a further957large banks,not involved in consolidation in the same year. The choice of2001for examining M&A activity is due to the fact that it allows for the examination of the performance of banks three years before and three years after the merger or acquisition,which is generally regarded in the literature as a suf?cient period from which useful conclusions can be derived concerning the impact of the merger or acquisition on the performance of the combined institution(Cornett&Tehranian,1992).

Both databases are well known and have been used extensively in banking studies (Altunbas,Gardener,Molyneux,&Moore,2001;Bikker&Haaf,2002;Bonin et al., 2005;Figueira,Nellis,&Parker,2006).Bonin,Hasan,and Wachtel(2005)argue that data from Bankscope should be dealt with carefully in order to ensure that a reliable sample is being used.Following their suggestion,the data used were subject to a consider-able amount of editing,in order to avoid problems associated with double counting of institutions,to ensure consistent accounting standards and to check that non-bank?nancial institutions were excluded from the sample.

The following subsection presents an overview of the trends in M&A activity in the last few years in the EU,which will be followed by a detailed examination of the perform-ance of banks involved in M&A activity in2001.

Patterns of M&As in the EU

Figure1presents the deal values of banking industry M&As that took place in the EU between1998and2004.In total,683deals were considered.Deals where the M&A had not been completed by the end of2004or where the value was not disclosed have been excluded.The?nancial institutions considered in the analysis are part of one of the following categories:commercial banks,savings banks,real estate and mortgage banks as well as investment banks.

The M&A activity has been divided into?ve categories:the?rst one shows M&A activity in the UK(in2001,57%of all EU banking sector M&As took place in the

UK).A second category includes the other core economies of the EU,comprising France,

Germany,Italy and Spain.Collectively,the Benelux countries constitute the third

category.A fourth category includes Greece,Ireland and Portugal.Austria,Finland and

Sweden,which joined the European Union in 1995,together with Denmark constitute

the ?nal category.In the graph,we also present the value of M&As across all categories

and this is named All .Due to insuf?cient information,the 10countries which joined the

EU in May 2004have been excluded from this research.

The ?gure below shows that after an increase in the value of total M&A activity

between 1998and 1999for some groups of countries and 2000for others,there has

been a notable decline.This follows a similar pattern to the number of deals completed

(Figueira,Nellis,&Schoenberg,2007b).

Figure 1exhibits pronounced peaks in the UK in 2000and 2004and in the other ‘core’

countries in 1999.These are the result of major M&A deals which were completed in these

years.Such large deals have important implications for the banking structure in the

respective nations.

However,how important is M&A activity in the overall banking system across the

EU?Figure 2provides evidence of the magnitude of M&As in EU banking over the

same period.The graph shows the annual M&A deal value as a percentage of the total

market value of the EU banking industry.The graph shows that the value of the M&A

activity each year was less than 10%of the market value of the banking system (excluding

the year 2000).It will also be seen that,after an intensive period of consolidation within

the industry,the relative scale of M&As has now faded to levels similar to those experi-

enced in the mid-1990s (ECB,2000).This could be the result of potentially limited oppor-

tunities for economies of scale from which ?nancial groups can bene?t by merging with

other groups.Another reason for the decrease in M&A activity may be related to the fact

that most of the M&A deals have so far been concentrated in domestic markets.This may

suggest that further reforms to EU and domestic regulations (Flier et al.,2001),as well as

the removal of non-regulatory obstacles (Nicoll &Schoenberg,1999),need to be put in

place to foster cross-border deals.

Table 1highlights the sharp distinction between within-country and cross-border

deals and shows that most of the M&A activity still takes place within a

country,

Figure 1.M&As deal value in EU banking,1998–2004.

878 C.Figueira and J.Nellis

whether we examine M&As in terms of value or number of transactions (with the excep-

tion of 2004,when Abbey National (UK)was taken over by Banco Santander Central

Hispano (Spain)).The limited amount of cross-border M&A deals raises a question

concerning the in?uence of the European regulatory reforms in fostering European

integration.

Having described the overall patterns of M&As in the EU banking industry,the fol-

lowing section describes the technical method used to analyse the performance of banks

involved in M&As and the results obtained.

Method and empirical results

This study uses Data Envelopment Analysis (DEA)in order to assess banking perform-

ance.DEA was ?rst developed by Charnes,Cooper,and Rhodes (1978)on the assumption

of constant returns to scale (CRS)and was later extended to allow for variable returns to

scale (VRS)by Banker,Charnes,and Cooper (1984).This technique uses a piece-wise-

linear technology,which involves mathematical programming to establish an ef?ciency

frontier.In this case,the ef?ciency of each bank is established by measuring its position

in relation to the frontier.

Table 1.M&As by value and number,disaggregated by within-country and cross-border,1998–

2004(in percentages).

Years

Value of deals

Number of deals Within-country Cross-border Within-country Cross-border 1998

85.5114.4961.8038.201999

79.5120.4971.8828.132000

64.2635.7459.8140.192001

79.8320.1769.3730.632002

87.0112.9982.1117.892003

82.1117.8979.4120.59200438.6061.4072.29

27.71

Figure 2.M&As annual deal value as a proportion of the EU banking industry market value.

The Service Industries Journal 879

Assume that there are M inputs and S outputs,for each of N banks.The ef?ciency esti-mates can be obtained by solving the following DEA linear programming problem:

min u;l u

s.t.ày itY l!0;N n0l?1(convexity constraint)

u x iàX l!0;l!0;

where u is a scalar,N N is an N?1vector of ones.x i is the column vector for the i-th bank in the M?N input matrix,X,and y i is the column vector for the same bank in the S?N output matrix,Y.The difference between the CRS and VRS formulations resides in the convexity constraint.While in a CRS model a bank may be benchmarked against banks of different sizes,in a VRS model an inef?cient bank is only benchmarked against banks of similar size.Therefore,l weights will sum up to a value that will usually differ from one.The ef?ciency of each unit,in this case each bank,is established by measuring its position in relation to comparable frontier banks with frontier banks having a relative ef?ciency score of100.More details on how the DEA linear programming model obtains ef?ciency estimates can be found in Coelli,Rao,and Battese(1998)and Thanassoulis(2001).

DEA has been used extensively in the banking literature(for recent examples of the application of this technique see,for example,Emel,Oral,Reisman,and Yolalan (2003)and Mercan,Reisman,Yolalan,and Emel(2003)for the Turkish banking system;Casu and Girardone(2004)for European banks;Halkos and Salamouris(2004) for Greek banks;Kao and Liu(2004)for Taiwanese banks,Portela and Thanassoulis (2006)for Portuguese banks and Figueira,Nellis,&Parker(2007a)for Polish banks).

The DEA approach to the measurement of relative performance has the advantage that it does not require the prior speci?cation of a functional form and the distribution of the error term(unlike the Stochastic Cost Frontier approach).This can be important where the functional form may be expected to vary,for example across countries.However, DEA has the disadvantage of attributing all deviations from the ef?ciency frontier to pro-duction inef?ciency.If any noise is present in the data,due for example to measurement error,this will affect the position of the frontier and,as a consequence,the measurement of bank inef?ciencies.DEA results are also biased by outliers in the data because they too can affect the position of the frontier.In this study,we minimise this problem by exclud-ing the top and bottom5%of our sample,as obtained in our initial DEA model.In addition, we use both input-oriented and output-oriented variable returns to scale DEA models.In the former case,banks should minimise the use of inputs given a certain amount of outputs pro-duced and in the second case,they should maximise the amount of outputs,given a certain amount of inputs.The choice of variable returns to scale relates to the fact that it is more appropriate to benchmark each bank against banks of similar size(Thanassoulis,2001).

The intermediation approach,developed by Sealey and Lindley(1977),was con-sidered in order to select the mix of inputs and outputs to be used in the DEA model. As such,the inputs to the production process of the banks are captured by total costs vari-ables,encompassing a range of costs,namely personnel and administrative costs,interest and non-interest costs.The output variables considered capture the main activities of the ?nancial institutions,i.e.lending(captured by the variable loans)and non-lending activi-ties,which have signi?cantly increased in importance in the last few years(captured by the variable other earning assets).Off-balance sheet activities have,however,been excluded due to lack of available data.A brief description of the data used can be found in the 880 C.Figueira and J.Nellis

The Service Industries Journal881 Appendix,which sets out summary statistics of the variables used in DEA.The following is a description of the results obtained using the DEA technique.

The empirical results

Table2provides a summary of the results obtained.At the?rst glance,the results suggest that?nancial institutions involved in M&A activity in2001have tended to perform slightly better after2001,when either one-year or three-year post-M&A periods are con-sidered.A few merged institutions also seem to perform worse,on average,in the second year.As can be seen from the table,in2003the standard deviation increased substantially. The average increase in performance in merged institutions,although small,is consistent whether the DEA scores are input-or output-based.

In order to establish a benchmark for the results obtained for the merged institutions, the sample of banks used to form the DEA frontier also included large https://www.doczj.com/doc/cc5465939.html,rge banks were de?ned as banks which have a total amount of assets of at least US$1 billion,as de?ned in the Bankscope database.All other banks have been excluded. Merged institutions result,on average,in large institutions and therefore,it seems appro-priate to compare them with individual large banks.To include smaller-sized banks in the sample may bias the results.

Table2.Ef?ciency estimates by year,1998–2004(excluding2001–year of M&A activity).

Years

DEA estimates199819992000200220032004 Merged institutions

Input-based

Mean60.0060.6360.9160.1644.2961.84 Median53.7352.4050.4951.0739.2456.97 Maximum100.0100.0100.0100.0100.0100.0 Minimum9.4719.8512.4611.00 2.808.81 Standard deviation19.4222.9720.9921.2232.3120.68 Output-based

Mean57.0561.1059.4263.9654.5861.92 Median52.0953.8353.1854.7950.2254.68 Maximum100.0100.0100.0100.0100.0100.0 Minimum14.1214.1410.217.347.398.16 Standard deviation22.4024.1823.1621.4427.2721.64 Large banks not involved in M&As in2001

Input-based

Mean52.0847.5750.2649.0029.7052.42 Median49.0644.6547.8245.9724.4148.61 Maximum100.0100.0100.0100.0100.0100.0 Minimum29.3325.9515.6915.17 1.1310.44 Standard deviation12.8411.6211.0711.5821.5413.42 Output-based

Mean47.4248.6347.8953.8545.3853.07 Median42.4444.8243.9950.2741.1049.31 Maximum100.0100.0100.0100.0100.0100.0 Minimum17.4217.5223.6933.8522.3015.75 Standard deviation15.0513.3612.9312.5215.7014.21 Note:The year of2001was excluded because it is the year when the M&A activity takes place.

Table3.Ef?ciency estimates by year and country(excluding2001–year of M&A activity).

Country

199819992000200220032004 Mean S.D.Mean S.D.Mean S.D.Mean S.D.Mean S.D.Mean S.D.

Merged institutions

Input-based

France56.7718.7160.0728.9159.3328.9066.9534.1666.6037.8168.6932.66 Germany57.2920.8754.4721.7655.8019.6653.0017.9927.5628.1055.5018.10 Italy61.5317.2363.7120.1963.8816.9462.4015.1652.0823.7862.8415.23 Spain66.0717.5875.0315.5169.0417.5766.7816.8866.7724.1876.2216.37 UK69.8317.5874.3725.7877.1521.9681.0418.7271.2115.5071.5920.89 Output-based

France59.0222.2264.1128.0763.1728.0971.3531.9169.8335.1470.4131.62 Germany50.5623.9352.3223.3350.3521.8954.9918.0241.4123.1953.5119.37 Italy61.5316.8466.6118.5666.1916.8367.6015.6660.4221.2264.4714.24 Spain67.0419.5477.3819.2370.8919.2875.3816.1975.5323.0279.1916.77 UK71.5617.2278.1821.8480.1118.6986.2015.4375.6813.0575.0017.96 Note:The year of2001was excluded because it is the year when the M&A activity takes place.882

C. Figueira and J. Nellis

The Service Industries Journal883 Table2also shows DEA scores for the group of large banks,not involved in M&As in2001.From the results,it can be seen that this group tends to underperform those which have been involved in M&As in2001by an average margin of8–10%.Moreover, it is also the case that this margin has been sustained throughout the period1998–2004. The statistical evidence for this difference raises the point that the new wave of M&As that had been taking place in the EU in the last few years could possibly be based on better risk and cost management than has happened throughout most of the1980s and 1990s.

Another conclusion that can be taken from the results shown on the table above is that, in general,banks tend to be increasingly more ef?cient,even if they are not involved in M&A activity.This seems to be a direct effect of the need for banks to be able to respond to the increased competitive pressures they face.

Table3presents the DEA ef?ciency scores by country.The patterns described above seem to be consistent across the?ve countries considered.However,there are differences in terms of overall ef?ciency among these countries.For instance,the UK seems to be the country where institutions are most ef?cient during most of the period of analysis,but it has recently been overtaken by Spanish?nancial institutions,which have become increas-ingly more competitive.Banks operating in France,Germany and Italy tend to be less ef?-cient,even though their ef?ciency has improved when the2004scores are compared with those for1998.This is probably due to the effects that country-speci?c characteristics may have on the cost side.For example,it could be argued that labour market institutions remain quite in?exible in the latter three countries,which together with substantial differ-ences in terms of taxation and other regulations,impose serious obstacles to further improvements in ef?ciency in such countries.

Conclusions

This paper has investigated M&A activity in the EU banking https://www.doczj.com/doc/cc5465939.html,ing data for the period1998–2004,the?ndings suggest that,overall,banks involved in M&A activity are slightly more ef?cient after the M&A and when compared to other large banks. In fact,banks that have been involved in M&As tend to outperform other large banks by an average of8–10%.

These results raise the issue that,due to competitive pressures from the market,M&A activity is underpinned by a set of measures,which may provide better knowledge of the risk and costs involved than had happened in the1980s and in the beginning of1990s.The results also provide evidence that,overall,banks have generally increased in ef?ciency over time.This could be the result of banks being more market aware and more focused on customer needs,and hence striving for product differentiation,so that they can achieve higher non-interest-based revenues.

However,there remain important differences across Western European countries,as a consequence of a signi?cant level of heterogeneity in terms of the regulatory frameworks, corporate taxes and the operation of labour markets.

Over the last few years,there have been important drivers of change in the political, social and economic environment within the EU,which have been signi?cant in under-pinning the integration of the European’s banking system.Such changes include the completion of the European Single Market,the enlargement of the EU to25member states,the establishment of the Euro and the establishment of the Financial Services Act Plan.Other changes,based on the Basel Accords,have also taken place in the global regu-latory framework and these have been signi?cant in decisions relating to bank consolidation

884 C.Figueira and J.Nellis

in and across countries.Therefore,it can be argued that signi?cant progress has been made towards the establishment of a legislative environment that is more conducive to more suc-cessful M&As.

Overall,the prospect of further consolidation in the banking industry appears promis-ing.However,this is not to say that M&As are not a high risk route of development. In fact,as documented by Schoenberg(2006),almost half of all cross-border acquisitions fail to meet their initial aims.Consolidation often gives banks access to more customers but does not always lead to pro?table growth or an improvement in the quality of the loan portfolio and it sometimes destroys shareholder value.A solid,differentiated client proposition,together with a competitive cost structure remain crucial ingredients for banks that aim at becoming more ef?cient and ultimately grow successfully via M&A activity.

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Appendix:Summary statistics of the variables used in DEA

France Germany Italy Spain UK Banks involved in M&As in2001

Total cost

Average12,365,3743,679,2144,629,3748,619,12610,950,183 Median3,205,75297,824715,2081,276,0871,273,347 Maximum51,690,36738,660,65829,384,38137,093,27728,559,564 Minimum75,3704621113717,380196,336 Standard deviation17,377,4798,690,7326,741,9587,527,29818,172,295 Loans

Average97,377,99736,954,92749,362,60179,370,147113,838,260 Median21,848,3261,038,3207,531,15420,775,28673,357,271 Maximum558,449,112471,629,257248,052,280471,735,862492,390,297 Minimum13,31837,57340,198113,5221,212,805 Standard deviation143,901,47989,960,95569,602,796111,797,182126,311,052

(Continued)

886 C.Figueira and J.Nellis

Appendix Continued

France Germany Italy Spain UK Other earning assets

Average124,338,24130,418,21024,145,33558,545,74195,134,464 Median19,010,676505,6635108,08017,465,56880,379,531 Maximum740,882,756613,233,156188,026,485375,553,558431,418,032 Minimum294,87634,05725,961228,049709,366 Large banks not involved in M&As in2001

Total cost

Average1,339,269375,822328,127457,9601480,030 Median275,07194,60593,358217,587333,944 Maximum28,006,15723,334,1499,486,8926,303,93937,119,515 Minimum11,55158348747281312,864 Standard deviation3,663,2471,563,197812,315786,3493,725,388 Loans

Average8,598,4543,655,5473,357,9517,111,04216,955,318 Median2,493,079969,8371,070,1303,251,7842,241,835 Maximum262,024,627229,289,701104,127,027125,038,543667,338,149 Minimum14,667503410,2678171331 Standard deviation22,640,52413,928,4668,421,51812,861,11351,704,996 Other earning assets

Average11,629,4813,601,0821,991,8403,066,54410,745,616 Median1,278,773581,081539,9181,175,4001,490,156 Maximum408,372,834464,537,70349,119,47439,823,199293,137,747 Minimum1582472276352331331

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