2.1 Literature Review
2.2 Performance Measurements
126.96.36.199 Efficiency Ratio
188.8.131.52 CAMELS Rating
184.108.40.206 Economic Value Added (EVA)
220.127.116.11 Risk-adjusted Return on Capital (RAROC)
18.104.22.168 Return on Assets (ROA) / Return on Average Assets (ROAA)
22.214.171.124 Return on Equity (ROE)
126.96.36.199 Cost-to-Income Ratio (CIR)
188.8.131.52 Net Interest Margin
184.108.40.206 Total Shareholder Return
220.127.116.11 Price-Earnings Ratio (P/E Ratio)
18.104.22.168 Price Book Ratio
2.3 Research Motivation
3.1 Structure of the Analysis
4. Empirical Analysis
List of Illustrations
Illustration 1 – Efficiency Ratio
Illustration 2 – Cost Income Ratio
Illustration 3 – Z-Ratio
Illustration 4 – ROA and ROE
Illustration 5 – Net Interest Margin
List of Tables
Table 1 – OLS model for CAMELS Rating
Table 2 – Key Ratios for Credit Unions with Assets of $50 million or more
Table 3 – Shortcuts for all 24 Swiss cantonal banks
Table 4 – Efficiency Ratio
Table 5 – Cost Income Ratio
Table 6 – ROE
Table 7 – ROA
Table 8 – Z-Ratio
List of Abbreviations
Abbildung in dieser Leseprobe nicht enthalten
In the opening section, the topic of this paper will be introduced and the objective of the analysis revealed. Furthermore, a short summary on the structure of the study provides a better understanding of the subject.
Banks around the world are eager to perform well in order to be able to survive in the industry, which is known to be one of the toughest in terms of competition. Above average financial results are not only supporting the operating business, but it is also crucial regarding the perception of the banks towards all kinds of stockholders. Although people make up their own opinion about institutions, the media greatly influence the public’s verdict on how an institution performed. Therefore it is a key priority for banks to convince the public with solid performance results. In the end, stockholders base investment decisions on such financial outcomes - in case of a positive signal, leading to the acquisition of shares, the purchase of a house through a mortgage or the opening of a bank account.
The return on equity (ROE) has been one of the most frequently quoted performance measurements for banks throughout the last decades. As one of the traditional key figures it mirrored if a bank was operating profitable, which represented an easy-to-understand guidance for investors. Throughout the years, when the ROE became the most common measure for performance, the banks understood that it will be in their best interest to be able to present high ROE figures. Recent events have shown that this measurement also has a flip side, namely that prosperous profitability and limited equity capital go hand in hand with each other. Especially in volatile market conditions this can eventually result in re-financing issues for the bank institutions and more severely insolvency. The latest financial crisis which started in 2007 showed that corporations with high ROE were struggling with their leverage situation and had to raise even new capital under some circumstances. More and more critical views about this return measurement were discussed and created the opportunity for other performance figures to step into the light.
To clear the misconception at the beginning, alternative bank measurements have been invented and used for quite some time but due to the recent unpredictable environment awareness about them has increased. These performance measurements try to better depict the actual health of an institution in order to predict its future outcomes. Especially the long-term perspective of certain figures is an eminent positive aspect, something that ROE lacked. During a financial crisis it is important to be able to predict the future market conditions most accurately in order to maintain your business or investment alive. Currently, it is commonly accepted that the worst times of the financial crisis are behind and that the markets show a positive trend, so it is interesting to see how various banks achieved different performance measurements throughout these years. This will be the starting point for this paper.
As outlined above, besides the most common bank performance measurement, ROE, there are various other methods which are referred to as alternative figures. The objective of this paper is to introduce the reader to these alternative performance procedures, which are widely used but not as well-known as ROE.
A second objective will be the adaption of these bank performance measurements to the Swiss banking sector. In particular, the focus will lie on all 24 Swiss Cantonal banks, which represent small as well as large institutions. By means of a comparative analysis, the key figures will be calculated and discussed for the time period of 2006 until 2011.
In general, an interesting aspect of the analysis will certainly be the difference of the performance measurements, since their calculations contain several distinct financial statement figures. Are the results of all ratios similar or do we face deviations between the approaches? Can we observe differences between the alternative ratios and the more traditional approaches?
Another key question in this study arises naturally when the time period is taken into a closer perspective. The interval is obviously chosen with an ulterior motive and includes the years around the latest financial crisis. Starting in 2006 we expect to register still increasing returns and high performance figures, whereas during the following years, the banks endured a complicated market environment with decreasing margins and declining profits. Could it be that the Swiss Cantonal banks were able to escape the downturn in the banking industry or has the effect been even more tremendous?
The performance results of all 24 different cantonal banks provide us with a variety of questions which are interesting to consider. In the comparative analysis we will compare and contrast the different measurements for the banks and we will analyse if there are any differences among the institutions. We will see if the institution’s size, which differs greatly, is an aspect for the performance to be better or worse.
The introduction states the topic at hand and set the boundaries for this paper’s analysis. It gives a brief insight in the current market environment in which the research is based and which objectives are studied. The structure section shortly outlines the five chapters along with their content.
In a second part the bank performance measurements are introduced and broadly explained. Advantages, similarities and differences are illustrated to be able to distinguish the figures, which bear mutual concepts. In the literature review, current papers are examined and their results are discussed in detail. The research motivations behind these studies are analyzed in order to understand the impulse behind this paper.
The methodology will be schematised in the third chapter, where the structure of this paper’s analysis is discussed. The hypotheses are introduced, which are studied in the next section. The data which is used mainly originates from two kind of sources, which will be explained the last part of the chapter.
The fourth section of the paper accommodates the empirical analysis regarding the bank performance measurements for the Swiss banking sector. In three subdivisions, the results are stated and discussed in broad details. Coherences are derived from the dataset to interpret the insights provided in this study. Furthermore, it will be interesting to see the aspect of extension to the current fields of research.
To sum up the paper, the last chapter includes a summary over the whole paper along with conclusions and inferences regarding the topic analysed. An outlook in terms of further research and studies starting points along with extensions to this paper are stated.
In this section of the paper, the proposed literature is discussed. The literature review provides the alternative performance measurements on which this paper is based. These key figures will then be defined and explained in detail. At last, the research motivation behind this study is explained.
2.1 Literature Review
In contrast to the most papers regarding bank performance, the study by Hays, De Lurgio and Gilbert Jr. (2009) does not discuss commercial but the much smaller community banks. The industry underwent dramatic changes and the banks have been adversely affected by a decrease in liquidity in the overall financial system1. In their paper, they analyse around 1400 community banks in the US, based on their financial year-end results during 2007-2009. By means of the efficiency ratio these institutions are divided into high and low efficient groups. The CAMELS rating system developed by the federal banking regulators is adopted and represents a performance measurement for the community banks. The six CAMELS variables are entered in a linear discriminant model and tested on their correct classification into the before-mentioned groups. The model a high overall classification accuracy (88% to 96%) and can be considered as a good representation of the actual bank performance for these community banks.
Kimball’s (1998) focus in his article is on the economic profit and related performance measurements. He introduces the risk-adjusted return on capital (RAROC) but mainly talks about another figure, the economic value added (EVA) developed by the consulting firm Stern Stewart & Co. A positive aspect of EVA is that it can be calculated for the whole company as well as for specific business units. Kimball also points out the difficulties with this performance measurement – one of them being relatedness of operations. Business units rely on each other and share expenses, which are not easily separated and assigned to the causative unit. This drawback is discussed on the topic of incentive systems for managers and solutions on this issue such as linked incentive, hierarchical grouping and hybrid incentive systems are suggested. In the paper’s last section, Kimball provides several approaches of capital allocation methodologies. The analysis is based on a fictional bank with different segments, which are consolidated at the end. On the basis of the Z-Ratio the business units efficiency is calculated which then can be used to optimally assign the equity to each part of the bank. Other methods are interested in the diversification or proportional scaling effects. Finally, while the concept of economic profit has powerful conceptual appeal, the ambiguities that surround its calculation indicate that no single measure of economic profit is able to capture all the subtle complexities, and the managers need to employ many specialized performance measures.2
Efficiency and competition are not directly observable but have a tremendous impact on the performance of banks. The focus lies on the more palpable short-term performance exhibited in quality services and affordable prices.3 The analysis includes 20 methods to measure efficiency and competition applied to 46 countries. By means of five models and representative indicators the competition level within countries is estimated and analysed. The data at hand is from Fitch IBCA’s BankScope and from the OECD and covers the ten-year period between 1996 and 2005. The indicators used for efficiency, costs, profit and market structure are only moderately correlated (~ 0.5). Bikker applies a principal components analysis (PCA) to measure the variation across countries within the set of correlated variables. Expert views about competition agree that Anglo-Saxon countries resemble higher competitive markets compared to Germany or France. The empirical analysis of the indicators leads to the result that the expert views are not completely reproduced and therefore need to be adjusted. Additionally, the indicators should not be applied indiscriminately for competition. Bikker examines the information value of the indicators on the basis of three aspects: economic interpretation, predictive validity and the use of an index. Appropriate indicators which contain the relevant information are reliable explanatory variables to estimate competition. The analyses lead to the conclusion that the efficiency and competition in banks could improve on several layers.
The report of the BSC (Banking Supervision Committee), which is a part of the ECB (European Central Bank), sets the focus on issues related to bank performance measurements. Their main indicator is the return on equity, which is examined thoroughly but the study additionally expands their research into the field of complementary approaches to the ROE, so-called alternative performance measurements. At first, bank analysts, consultants and rating agencies have been interviewed and ranked various measures by priority of usage. The result shows that the value of an indicator can be quite different from one stakeholder to the other. Therefore it is advisable to take not only one performance measurement into perspective when studying a bank. The analysis includes twelve large European and US banks and focuses on the dynamic performance measurements throughout the latest financial crisis. The report thereby identifies three limitations of ROE as a measure of performance. First, the indicator is not risk-sensitive. ROE is an instrument which interprets the bank’s short-term profitability. As a result, the long-term perspective is missing and during a volatile environment, such as financial crisis, the indicator is not suitable to interpret the future of the institution. A third drawback, the ECB lists the room for manipulation and wrong incentives. Due to a lack of transparency, unrecognised losses can swell ROE in a fallacious way.4 The short-term focus leads to unexpected risk levels which clearly prove to be the false motivation of the management. In the fourth part, the report suggests several refinements and issues to consider in future bank performance measures, such as risk-adjusted returns, asset or capital quality. The last section points out additional factors to be considered when analysing a bank’s performance. The main aspect of this report is that ROE is a useful indicator but when assessing the profitability of a company other measurements and factors should be included to provide a more thorough understanding. Furthermore, governance and bank’s risk management need to consider additional long-term assessments in order to better align their capital and improve the dialogue between all market participants.
2.2 Performance Measurements
A growing trend leads towards alternative bank performance measurement and the so-called traditional ratios, such as return on equity, are slowly fading from the spotlight. In this chapter, five different approaches are introduced and their advantages and disadvantages are outlined.
22.214.171.124 Efficiency Ratio
The paper of Hays, De Lurgio and Gilbert Jr. introduces the efficiency ratio as a basic performance measurement. This popular tool is widely used by bank analysts and calculates the effectiveness of the institution with their income and expenses. The efficiency ratio is calculated by dividing overhead expenses by the sum of net interest income and non-interest or fee income.
The indicator is sensitive to changes in salaries and benefits, technology or labour productivity. Economies and diseconomies of scale as well as utilisation of physical facilities drive the ratio. Unlike most performance measurements, a decrease in the efficiency ratio is optimal and is considered a positive sign, while negative figures resemble an inefficient business model. Overstaffing, disproportionate salaries and benefits or branch expansion plans can decrease the efficiency of a bank. On the other hand increased income earnings through new customers will influence the ratio in a positive way. An acceptable efficiency ratio was once in the low 60s. Now the goal is 50, while better-performing banks boast ratios in the mid-40s.5 The authors of the before-mentioned paper define community banks with a ratio below 51 as efficient and the ones above 81 as inefficient. The measurement is also applicable for other industries such as chemicals, car production or steel manufacturing.
126.96.36.199 CAMELS Rating
In 1987 the National Credit Union Administration (NCUA) adopted the CAMELS rating system to accurately monitor credit union’s financial operations and health. The NCUA is an independent federal agency, which was set up by the U.S. Congress to supervise, regulate and charter credit unions. The board of directors and the bank management receive a score on the bank’s performance which ranges from 1 to 5, where 1 is the best and 5 the worst rating. Banks with a score of 4-5 are considered problematic and limited in their operations.6 During the latest financial crisis the system has been used to monitor the overall bank performance and to evaluate the company’s requirement for additional capital. The CAMELS acronym stands for C apital adequacy, A sset quality, M anagement, E arnings, L iquidity and S ensitivity. The tool was not invented as a reporting indicator due to the fact that the information on the rating may induce a bank run on a troubled bank leading to a loss in public confidence about the banking system in general.7 Therefore, these figures are only calculated as an internal guidance to detect deficiencies in the company and inform the management about certain aspects of improvement. The CAMELS system can be approximated by financial income statement figures. The only difficulty is to measure the “management”, since in the official assessment the bank examination staff is forming a subjective opinion about the leadership of the firm and assigns a score. These proxies can be implemented in a linear discriminant model to eventually measure the efficiency of a bank.
Abbildung in dieser Leseprobe nicht enthalten
α = Constant
E2TA = Equity Capital to Total Assets (Capital)
NCO2L = Net Loan Charge-offs to Loans (Asset quality)
SalAA = Salaries and benefits to Avg. Assets (Management)
ROAA = Return on Average Assets (Earnings)
1 Hays, Fred H., De Lurgio, Stephen A. and Gilbert Jr., Arthur H. (2009): Efficiency Ratios and Community Bank Performance. Journal of Finance and Accountancy, Vol. 1, p. 2
2 Kimball, Ralph C. (1998): Economic Profit and Performance Measurement in Banking. New England Economic Review, July/August, p. 53
3 Bikker, Jacob A. (2010): Measuring Performance of Banks: An Assessment. Journal of Applied Business and Economics 11 (4), p. 142
4 European Central Bank (2010): Beyond ROE – How to measure bank performance. Appendix to the report on EU banking structures.
6 Hays, Fred H., De Lurgio, Stephen A. and Gilbert Jr., Arthur H. (2009): Efficiency Ratios and Community Bank Performance. Journal of Finance and Accountancy, Vol. 1, p. 7
7 Lopez, Jose (1999): Using CAMELS Ratings to Monitor Bank Conditions. FRBSF Economic Letter
- Quote paper
- Master Silvan Lehner (Author), 2013, Traditional and Alternative Performance Measurements for Banks, Munich, GRIN Verlag, https://www.grin.com/document/313246