Clear Accountability Frameworks Which Enable

Published Date: 02 Nov 2017

The literature review will include an analysis of key research, policy, previously undertaken literature reviews and other relevant documentations. It will also cover any relevant publications elsewhere, where such findings may prove helpful.

The main aim of the literature review is to better understand, the following principles relating to risk assessment based on sound evidence and analysis:

- Tools and other approaches to risk assessment which advice, rather than replace professional judgment;

- Clear accountability frameworks which enable professional autonomy;

- A common inter-agency understanding and language of risk assessment;

- Risk assessment approaches that are integral to the overall management and risk minimization.

Brown Bridge (1998) observed that these problems (Bad Credits and bankruptcies) are at their acute stage in developing countries. The problem often begins right at the loan application stage and increases further at the loan approval, monitoring and controlling stages, especially when CRM guidelines in terms of policy and strategies/procedures for credit processing do not exist or they are weak or incomplete.

Lending has been, and still is, the foundation of banking business, and this is more true to emerging economies like Tanzania where capital markets are not yet well developed. To most of the transition economies, however, and Tanzania in particular, lending activities have been controversial and a difficult matter. This is because business firms on one hand are complaining about lack of credits and the excessively high standards set by banks, while CBs on the other hand have suffered large losses on bad loans. It has been found out that in order to minimize loan losses and so as the CR, it is essential for CBs to have an effective CRM system in place. Given the asymmetric information that exists between lenders and borrowers, banks must have a mechanism to ensure that they not only evaluate default risk that is unknown to them ex ante in order to avoid adverse selection, but also that can evolve ex post in order to avoid moral hazards.

Cutts, Van Order, and Zorn (2000) developed a theoretical framework in which lending markets expand as more information about borrowers becomes available. Recent improvements in credit scoring that provide lenders with information to distinguish between high and low credit quality borrowers make this framework relevant for today's modern credit markets. This model predicts that fewer borrowers should be denied credit access since lenders can segment them into different markets and charge riskier groups higher rates to compensate for the possibility of poor payment performance. Under this framework, different treatment of borrowers in terms of credit availability and rates charged should be viewed as evidence of well-functioning consumer credit markets since borrowers do not exhibit homogeneous loan repayment behavior.

Economists have shown interest in finding evidence of risk-based pricing. For example, Duca and Rosenthal (1994) investigated whether mortgage rates were influenced by observable differences in household default characteristics. They concluded that lenders do not vary rates across borrowers on the basis of differences in credit risk. Of course, the authors, using the 1983 SCF data, were limited to a question that asked households if their loan payments in the past year were paid as scheduled or "sometimes made later or missed." Because this question does not adequately distinguish respondents with severe repayment problems from those who may have simply forgotten to mail the regular payment on time, it was difficult to find empirical evidence for risk-based pricing. Consequently, very little research on risk-based pricing in consumer credit markets exists since credit history information was (and still is) largely proprietary and unavailable to academics.

The more recent SCFs contain better questions for identifying high-credit risk households, so this source of publicly available data is more useful for studying credit pricing. Edelberg (2003) uses the SCFs from 1989 through 1998 to construct interest rate risk premiums paid on mortgage and automobile loans over time. She demonstrated that both interest rate premiums and debt levels have risen since the 1995 SCF, which is consistent with the Cutts, Van Order, and Zorn theoretical framework and the emerging practice of risk-based pricing. However, her research does not directly address whether the lack of borrower information or lack of creditworthiness is important for explaining credit rejections.

Richard (2006) overviewed in his article that financial institutions (FIs) are very important in any economy. Their role is similar to that of blood arteries in the human body, because FIs pump financial resources for economic growth from the depositories to where they are required. Commercial banks (CBs) are FIs and are key providers of financial information to the economy. They play even a most critical role to emerging economies where borrowers have no access to capital markets. There is evidence that well-functioning CBs accelerate economic growth, while poorly functioning CBs impede economic progress and aggravate poverty.

CBs face various risks that can be categorized into three groups; financial, operational and strategic. These risks have different impact on the performance of CBs. The magnitude and the level of loss caused by CR compared to others, is severe to cause bank failures. Over the years, there have been an increased number of significant bank problems in both matured and emerging economies. Various researchers have studied reasons behind bank problems and identified several factors. Credit problems, especially weakness in credit risk management, have been identified to be a part of the major reasons behind banking difficulties. Loans constitute a large proportion of CR as they normally account for 10-15 times the equity of a bank. Thus, banking business is likely to face difficulties when there is a slight deterioration in the quality of loans. Poor loan quality has its roots in the information processing mechanism.

Koch and MacDonald (2000) described loans that constitute a large proportion of the assets in most banks' portfolios are relatively illiquid and exhibit the highest CR. The theory of asymmetric information argues that it may be impossible to distinguish good borrowers from bad borrowers, which may result in adverse selection and moral hazards problems. Adverse selection and moral hazards have led to substantial accumulation of non-performing accounts in banks. The very existence of banks is often interpreted in terms of their superior ability to overcome three basic problems of information asymmetry namely; ex ante, interim and ex post. The management of CR in banking industry follows the process of risk identification, measurement, assessment, monitoring and control. It involves identification of potential risk factors, estimate their consequences, monitor activities exposed to the identified risk factors and put in place control measures to prevent or reduce the undesirable effects. This process is applied within the strategic and operational framework of the bank.

Hogarth and Hilgert (2002) use the 1995 and 1998 SCFs to look at the profile of borrowers who pay mortgages with very high rates of interest. They found that older, minority, low-income, and limited-educated respondents were more likely to hold high-interest rate home loans; and many of these consumers used high-rate loans for debt consolidation. However, this study was limited to home loans, and the authors also admitted to having problems with low sample size.

Kealhofer (2003) has proposed several risk-adjusted performance measures. The measures, however, focus on risk-return trade-off, i.e. measuring the risk inherent in each activity or product, and charge it accordingly for the capital required to support it. This does not solve the issue of recovering loan amount. Effective system that ensures repayment of loans by borrowers is critical in dealing with asymmetric information problems and in reducing the level of loan losses, thus the long-term success of any banking organization. Effective CRM involves establishing an appropriate CR environment; operating under a sound credit granting process; maintaining an appropriate credit administration that involves monitoring process as well as adequate controls over CR. It requires top management to ensure that there are proper and clear guidelines in managing CR, i.e. all guidelines are properly communicated throughout the organization; and that everybody involved in CRM understand them.

Considerations that form the basis for sound CRM system include: policy and strategies that clearly outline the scope and allocation of a bank credit facilities and the manner in which a credit portfolio is managed, i.e. how loans are originated, appraised, supervised and collected. Screening borrowers is an activity that has widely been recommended. This recommendation has been widely put to use in the banking sector in the form of credit assessment. According to the asymmetric information theory, a collection of reliable information from prospective borrowers becomes critical in accomplishing effective screening.

Bryant (1999) argued that the assessment of borrowers can be performed through the use of qualitative as well as quantitative techniques. One major challenge of using qualitative models is their subjective nature. However, borrowers attributes assessed through qualitative models can be assigned numbers with the sum of the values compared to a threshold. This technique is termed as "credit scoring". The technique cannot only minimize processing costs but also reduce subjective judgments and possible biases. The rating systems if meaningful should signal changes in expected level of loan loss. Chijoriga (1997) concluded that quantitative models make it possible to, among others, numerically establish which factors are important in explaining default risk, evaluate the relative degree of importance of the factors, improve the pricing of default risk, be more able to screen out bad loan applicants and be in a better position to calculate any provisions needed to meet expected future loan losses.

Heffernan (1996) has clear established process for approving new credits and extending the existing credits has been observed to be very important while managing CR. Further, monitoring of borrowers is very important as current and potential exposures change with both the passage of time and the movements in the underlying variables and also very important in dealing with moral hazard problem. Monitoring involves, among others, frequent contact with borrowers, creating an environment that the bank can be seen as a solver of problems and trusted adviser; develop the culture of being supportive to borrowers whenever they are recognized to be in difficulties and are striving to deal with the situation; monitoring the flow of borrower's business through the bank's account; regular review of the borrower's reports as well as an on-site visit; updating borrowers credit files and periodically reviewing the borrowers rating assigned at the time the credit was granted.

Benveniste and Berger (1987) have defined tools like covenants, collateral, credit rationing, loan securitization and loan syndication have been used by banks in developing the world in controlling credit losses. It has also been observed that high-quality CRM staffs are critical to ensure that the depth of knowledge and judgment needed is always available, thus successfully managing the CR in the CBs. Donaldson (1994) observed that computers are useful in credit analysis, monitoring and control, as they make it easy to keep track on trend of credits within the portfolio. Marphatia and Tiwari (2004) argued that risk management is primarily about people – how they think and how they interact with one another. Technology is just a tool; in the wrong hands it is useless. This stresses further the critical importance of qualified staff in managing CR.

Ryals and Knox (2006) in their research have prepared a relationship scorecard for business customers of an insurance company according to nine main factors they had extracted. Their factors were extracted by semi-structured interviews with KAM’s (Key Account Management) team of an insurance company. This relationship risk scorecard was then used to analyze the 10 key accounts for which full data was available. In our research, the extraction of the factors is done through Delphi method which is an expert survey. Delphi method’s objective is to develop a technique to obtain the most reliable consensus of a group of experts. In our research we too needed to have a valid list of qualitative factors based on which a score could be assigned to customers.

Delphi seemed a more suitable method than semi-structured interviews since the output of Delphi method would be a list of attributes on which the experts have consensus and this feature would let us use this compromised list with high certainty for further computations.

Gronroos (1994) suggests a relationship definition of marketing. Marketing is to establish, maintain, and enhance relationships with customers and other partners, at a profit, so that the objectives of the parties involved are met. This is achieved by a mutual exchange and fulfillment of promises.

It is proposed that closer attention is paid to the long-term financial benefits, and other benefits of retained customers, is the main reason being that competition in the marketplace has intensified. To achieve growth, it is argued; organizations must change their paradigm to that of relationship marketing. In the financial services industry as well, more than ever before, managers must understand their best customers’ needs and prevent them from switching to other companies.

Bharath et al. (2005) have been one most successful approach to address these issues would be relationship banking which is that if a financial intermediary’s decision to supply various services to a firm is based on borrower-specific information that the intermediary collects over multiple interactions and further, if this information is proprietary, the intermediary is engaged in relationship banking. In contrast, transaction-oriented banking is based on identical transactions with various customers, so that transaction based lending is financing according to that particular transaction rather than being aimed at an information based relationship. It is important for prudent lenders to gather information about the creditworthiness of the borrowers. There are several ways to obtain this information, but one method that is especially well suited for new firms is the development of long-term lender-borrower relationships which enables the lender to better know the borrower and offer suitable services at the right time to the right borrower. The aim of relationship banking then would be resolving problems of asymmetric information. As a subset of relationship banking, relationship lending is defined as a long term implicit contract between a bank and its debtor.

Researchers have mentioned several benefits of relationship lending which could come from multiple sources such as the ability to share sensitive information, more flexible contracts, the ability to monitor collateral, and the ability to smooth out loan pricing over multiple loans.

Behr and Guttler, (2007) show in their research that strong past lending relationships significantly increase the probability of securing future lending and investment banking business. Many factors have been considered effective in relationship lending in financial service industry, an important one is the risk. The constructs of risk are investigated by many researchers and each of these researches indicates; the risk factor for a specific financial service varies in a specific country. For instance, the amount of return on sales and size of the firm for relationship borrowers of German banks are investigated, or Ryals and Knox (2006) have prepared a Journal of Money, Investment and Banking - Issue 9 (2009) relationship scorecard for business customers of an insurance company according to nine main factors they have extracted from a KAM’s team. These factors included number of customer relationships within the company, number of products bought by the customer, longevity of relationship or how good is the company’s understanding of customer’s company and industry.

Elsas (2005) has investigated the duration of a bank–borrower relationship and the basic idea is that duration reflects the degree of relationship intensity over time. The number of bank relationships is associated with a higher riskiness of the borrowers according to Foglia et al. (1998) because when a large number of lenders are involved, monitoring of the borrower tends to be weaker. Multiple banking relationships could also be due to inefficient judicial systems and poor enforcement of laws of a country, or even the size of the firm; the larger the firm, the more the number of relationships.

Baas and Schrooten (2006) have defined, there are four types of lending in financial services in which the first is based on soft information and the other three are based on hard information. Relationship lending is based on the experience of a given bank with a specific borrower and therefore on soft information collected over time. So if financial data is limited, relationship banking is the technique of choice. Financial statement lending is based on evaluating information from the firm’s financial statements. The decision to lend depends largely on the strength of the balance sheet and income statements. Asset-based lending is principally based on the quality of the available collateral. This type of lending causes high monitoring costs and requires high-quality receivables and inventory available to pledge. That is why it is generally used as a substitute for relationship lending if the term of the relationship is short.

Small business credit scoring is an adaptation of statistical techniques used in consumer lending. In addition to information about the financial statements, the creditworthiness and history of the owner is heavily weighted.

Boot (2000) overviewed, a contractual benefit of relationship lending is that bank loan contracts can more easily and safely accommodate collateral requirements to secure loans. Iranian private banks started to establish in 2001 after a twenty-year gap, and now they add up to six banks. During the past 7 years, KB has proved to be a pioneer not only in offering new services to its customers but also to adopt new banking concepts in Iran, one being the relationship banking concept. For this reason, we considered KB as the best potential for providing our case study. KB has been officially established as the first Iranian private bank in operation on January 1, 2001. Since lending relationship of KB and its business customers has been the subject of the case study in our research, we will take a look at lending technique at KB to get an understanding of ineffectiveness of this process and will see that relationship lending seems the best technique for current situation of lending for this bank.

Jimenez et al., (2006) found empirical evidence that relationship lending pays off for borrowers in terms of a lower likelihood that bank will require them to pledge collateral in new loans. In another research, Jimenez et al., (2006) show that collateral is a way to decrease the risk of the loan operation. Also Boot, (2000) mentions another benefit of collateral as exposure of valuable information to the bank over time. For example, a bank with inventories and accounts receivable as collateral, may learn valuable information about the business and it (collateral) can actually mitigate moral hazard and adverse selection problems of relationship lending.

When a loan application is filed by a firm at KB, the credit committee of the bank will decide on the amount of loan that could be granted to the firm. This committee, which differs in number and expertise of members from one bank to another, includes four members at KB which decides on the basis of financial/non-financial criteria along with credit policies of the bank. The financial factors are mostly unreliable in Iran due to false or fake financial statements of the firms and non-financial criteria are checked by subjective knowledge of the committee members about the firm and its industry. The problem with non-financial criteria is that there is no valid reference of attributes for the committee members based on which they could decide. Each member would evaluate the firm according to his own frame of reference which would cause inaccuracy of final decisions.

(START WORKING FROM HERE, Work of Grammers)

Decressin et al. (2003) propose that recent weak bank profitability in Germany appears to be related with structural factors rather than the macroeconomic cycle. Some anecdotal evidence and financial ratio analyses are also presented to support this claim. The motivation of this paper is to study the issue of bank profitability in a coherent and rigorous econometric framework with a large panel data set of the German banking industry. Another main motivation is to go beyond the factors explored in the IMF paper in explaining why the profitability of the German banking system has been relatively low and trended downwards over recent years. For example, over 20 per cent of Germany's commercial banks in the Fitch IBCA database did not earn a rate of return for their owners that exceeded the rate of a risk-free treasury bill. This immediately leads to the question of how the structure and the organisation of the German banking system can be changed to safeguard banks' profitability and the sector's stability.

These three pillars are all different with respect to ownership and objectives. For example, most of the public sector banks are effectively owned by state and local governments, which operate commercially but also have a public mandate and currently benefit from a government guarantee. The second group in the German banking industry is the cooperatives. This group of banks was founded as self-help organizations for craftsmen, workers and farmers. Cooperative banks concentrate on their respective local markets and do not compete with one another. Finally, the major part of private sector banks, are commercial banks. Commercial banks comprise the big four banks, which account for roughly two thirds of this sector's business. The private sector banks also include the Postbank, foreign banks, and numerous smaller banks. The biggest four commercial banks comprise Deutsche Bank, HypoVereinsbank, Dresdner Bank, and Commerzbank. Like the cooperative banks, they do not benefit from a public sector guarantee, and thus are at a disadvantage relative to the state banks in tapping capital markets. Neglecting the different ownership structure, co-operations and public banks exhibit a quite similar behavior.

Generally speaking, from the Fitch IBCA database, we can observe that savings banks and cooperatives currently have higher returns on equity than commercial banks.

After reviewing the German banking system, we come back to the argument of how structural factors affect the German banking profitability. Many propose that the relatively low profitability of the German banking system could possibly reflect that profit maximization is not always the paramount objective of public sector banks and cooperatives. Furthermore, a high number of banks per capita leads to an intense competition. For instance, they point out that competition in Germany appears to be more intense than in the United Kingdom and France. In the following part, we will try to find out how the market structure affects banks' profitability by examining a model that can distinguish between three competing profit-structure hypotheses.

Keeley (1990) who reasons that the surge of bank failures in the US during the 1980s had been caused by various deregulation measures and market factors that reduced monopoly rents. Edwards and Mishkin (1995) argue that the erosion of profits due to competition from financial markets can be held responsible for the excessive risk-taking observed in the 1980s in the USA. Chapelle et al. (2005) suggest that substantial savings can be achieved through active risk management techniques, although the effect of a reduction of the frequency or severity of operational losses depends on the calibration of the aggregate loss distributions.

The remainder of this paper is structured as follows. The next section outlines the functional form and measurement methodologies adopted in this study. Followed by the section that discusses the data sources. The penultimate section shows the estimation and results. In a final section, we summarize our findings and give suggestions for the future industrial organization of the German banking sector.

Brewer et a. (2003) defined the relationship between market structure and the profitability of banks is of concern to bank managers and to banking regulators. Particularly, the banking regulators have to weigh the potentially beneficial effects of mergers on the combined banks' profitability and viability against the possible detrimental impact on consumer welfare. For example, increased competition from financial deregulation in the banking sector may force banks to invest into higher yielding assets by increasing their risk exposure beyond a reasonable level. Based on this consideration, we will pay particular attention to the delicate balance between profitability and risk. They incorporate aspects of banks' ex-post risk-taking behaviour into a framework developed by Berger (1995) to evaluate alternative theories of the profit-structure relationship. All three hypotheses, the structural-conduct-performance hypothesis, the market-power hypothesis and the scale-efficiency version of efficient-structure hypothesis, are represented by different variables. The major equation (1) is shown to be a valid reduced form for all of the hypotheses and any or all of them may be found to be consistent with the data. For instance, if the structural-conduct-performance hypothesis holds, the coefficient of concentration is significant and positive but the coefficient of market share is not in this case. This result indicates that the positive profit-concentration relationship occurs because concentration affects price and price affects profit. On the other hand, if the coefficient of market share is positive and significant, but the other coefficients are not in this case, the relative-market-power hypothesis holds. Under the relative-market-power hypothesis, market share becomes the key exogenous variable since banks with large market shares have well-differentiated products and are able to exercise market power in pricing these products.

By contrast, if the scale-efficiency version of the efficient-structure hypothesis is accepted, the coefficient of the scale efficiency variable will be positive and significant. An important limitation of the reduced-form profit equation (1) is that it tests only one of the three necessary conditions of the efficient-structure hypotheses. In order to explain the profit-structure relationship spuriously, two more conditions (equations (2) and (3)) should be met, since both profits and the market structure variables (concentration rate and market share) must be positively related to the variable of scale efficiency. For instance, equation (3) means that more efficient firms have greater market shares. This can be explained by the fact that more efficient banks obtain greater market share through price competition or through acquisition of less efficient banks. Finally, the risk factors in this specification model are evaluated by incorporating capital risk and portfolio risk.

Broadbent et al. (2004) that German financial institutions have not adequately priced loans to the corporate sector. The intention of the Basel II recommendations on risk-adjusted capital adequacy ratios will presumably force German banks to differentiate loan pricing on the basis of internal or external ratings and finally improve the return on loan portfolios. At the same time, it may become increasingly more difficult for German medium-sized companies without access to the capital markets to obtain bank financing.

Furthermore, we observe that the coefficient of market share is still negative and significant at the 1 per cent critical level in the major equation (1). This means that the relative-power hypothesis is still rejected. Moreover, the coefficient of capital risk is statistically significant at the 5 per cent critical level in the major equation (1), but the factor of capital risk only brings a slightly negative effect on the German banking profitability. Finally, the coefficient of scale economy efficiency is always statistically insignificant in the three empirical cases under consideration. It maybe inferred that the scale-efficiency version of efficient-structure hypothesis does not contribute to explain the profit-structure relationship in the German banking market.

It should be pointed out that after the factor of portfolio risk is added into this specification model, adjusted R 2 is considerably improved from 4 to 32 per cent. We can conclude that German banking profitability is not only determined by the market structure but also the factor of portfolio risk.

To answer the questions posed in our introduction, the empirical evidence gathered in this paper shows that market structure plays a significant role in determining German banks' profitability. Analysis on a panel of 298 German banks from 1998 to 2003 supports the structural-conduct-performance hypothesis. As a new finding compared to previous studies of the German banking sector, portfolio risk is shown to contribute positively to banks' profitability.

Another important finding in this paper is that incorporating portfolio risk can significantly increase the adjusted R 2 of our specification model of the profit-structure relationship. This empirical result indicates that the management of the risks in asset portfolios is a key factor in determining German bank profits. It can be inferred that the German banking sector should be able achieve higher profitability by increasing portfolio risk. Certainly, appropriate portfolio risk management systems still need to be in place. If the latter is not the case and competition becomes too intense, increased risk-taking by banks may even threaten the stability of a country's financial system.

Flannery and James (1984) defined in the finance literature continues to address the interest sensitivity of commercial bank stocks. Interest rate risk occurs regardless of the managed interest rate risk in the balance sheet. Even if the maturities of assets and liabilities are well matched, the asymmetric response of loan prepayments to interest rate changes generates interest rate risk. The recent expansion of mark-to-market valuation of investment securities will enhance interest rate risk and make it difficult for banks to hide the decline in asset values caused by increases in interest rates. Moreover, because of the higher capital requirements of loans generated by the risk-based capital standards, the commercial real estate loan debacle of the late 1980s, and regulatory pressure, bank managers are reluctant to make loans. To avoid the scrutiny of regulators regarding problem loans and reduce capital requirements, banks make fewer loans and invest more funds in securities such as Treasury bonds. Because commercial loans are short term and the securities that replace them are long term, banks can lengthen the average maturity of assets. While banks are now positioned to profit from an upsloping yield curve and declining interest rates, they could suffer serious losses if interest rates turn up or the yield curve inverts. Therefore, regulators have proposed an interest rate risk component of the risk-based capital standards.

Interest sensitivity of bank stocks remains an important topic and should be studied using recent data to show timely effects for bank managers. Many studies focus on 1976-85 because interest rates were volatile and were at unprecedented high levels. Studies using recent data may be flawed. Neuberger (1991) does not test for structural breaks in the regression coefficients but performs annual regressions.(1) We determine whether changes occurred in the estimates of regression coefficients. Moreover, Neuberger's (1991) definition of money center, superregional, and regional is based on bank size rather than banking practices. We divide the sample of banks into money center, superregional, and regional banks by common practices to determine whether the results differ by bank type.

Choi, Elyasiani, and Kopecky (1992) use dummy variables to show the breaks in regression coefficients without first testing for heteroskedasticity between periods. While they separately study the regression results of money center banks, there may be differences in the results of superregional and regional banks. We test for heteroskedasticity between periods and perform separate regressions when heteroskedasticity occurs. We also isolate the results for banks other than money center banks. Choi, Elyasiani, and Kopecky (1992) address the effects of foreign exchange rates on bank risk. However, they theorize but do not prove that foreign exchange risk is tied to un-hedged foreign loan exposure. We estimate the relation between foreign exchange risk and un-hedged foreign loan exposure.

Stone (1974) derives a two-index model to measure market risk and suggests that financial institutions' stock returns may be sensitive to changes in interest rates. Lloyd and Shick (1977) find that bank stock betas are not significantly different from zero and that interest rate risk does add explanatory power, albeit marginally.(2) Some authors find significant sensitivity to interest rates. In contrast, Chance and Lane (1980) find that few banks show interest sensitivity regardless of whether the index is long term or short term. There is no difference in the results whether anticipated or unanticipated rate changes are used. Interest sensitivity is unstable over time. Interest sensitivity is related to the measure of gap.

According to Baas and Schrooten (2006), there are four types of lending in financial services in which the first is based on soft information and the other three are based on hard information. These lending techniques are shown in Table 1: Lending techniques adapted from Baas and Schrooten 2006 Relationship lending is based on the experience of a given bank with a specific borrower and therefore on soft information collected over time. So if financial data is limited, relationship banking is the technique of choice. Financial statement lending is based on evaluating information from the firm’s financial statements. The decision to lend depends largely on the strength of the balance sheet and income statements. Asset-based lending is principally based on the quality of the available collateral. This type of lending causes high monitoring costs and requires high-quality receivables and inventory available to pledge. That is why it is generally used as a substitute for relationship lending if the term of the relationship is short. Small business credit scoring is an adaptation of statistical techniques used in consumer lending. In addition to information about the financial statements, the creditworthiness and history of the owner is heavily weighted.

According to Boot (2000), a contractual benefit of relationship lending is that bank loan contracts can more easily and safely accommodate collateral requirements to secure loans. Also Jimenez et al., (2006) found empirical evidence that relationship lending pays off for borrowers in terms of a lower likelihood that bank will require them to pledge collateral in new loans. In another research, Jimenez et al., (2006) show that collateral is a way to decrease the risk of the loan operation. Also Boot, (2000) mentions another benefit of collateral as exposure of valuable information to the bank over time. For example, a bank with inventories and accounts receivable as collateral, may learn valuable information about the business and it (collateral) can actually mitigate moral hazard and adverse selection problems of relationship lending.

According to Schmidt (1997), ‘‘without this step, there is no basis to claim that a valid, consolidated list has been produced.’’ Some experts’ lists had major changes in some cases such as adding the factors from the consolidated list to their own list. We put the consensus condition of this stage to be that if more than 80% of the experts reject an attribute to be on the list, the attribute is omitted. The condition of consensus is set by Delphi researchers and there is no specific rule for that, but the more the rounds of the Delphi method and the more restrict the set rules, the more reliable the results. Three of the factors were identified as "influential factors in commencement of lending relationship with a new customer" by 18 experts. These factors were 1) Relationship of the firm with its clients, 2) Performance of the firm in the banking system, and 3) Credibility of the referee of that firm to the bank, and were all omitted from our list. The other omitted factor was the extent of word of mouth the firm could bring for the bank which was considered "non related to the research purpose" or "value creating indicator" by the experts, so was omitted from the list. So the output of this phase of our Delphi was a verified list of 22 factors. In our third questionnaire we asked experts to identify (and not rank) at least 10 factors (from 22 factors) that they thought were the most important risk factors in relationship lending. We repeated this step for three times and selected attributes which had got more than or equal to 12 votes (50%) in all three rounds. The reason for omitting some attributes is that we want to find the attributes that experts have consensus on their importance. We got total of 13 attributes at this stage which became our final compromised list.

Molyneux and Thornton (1992) described in brief, these three profit-structure hypotheses have emerged in the banking literature to explain the profit-structure relationship. They are the structural-conduct-performance hypothesis, the relative-market-power hypothesis, and the scale-efficiency version of the efficient-structure hypothesis. The structural-conduct-performance hypothesis states that banks set prices that are less favourable to consumers in more concentrated markets because of an imperfect competition. The relative-market-power hypothesis suggests that only banks with large market shares and well-differentiated products can exercise market power in pricing these products and earn supernormal profits. Finally, under the scale-efficiency version of the efficient-structure hypothesis, all banks have equally good management and technology (the same X-efficiency), but some banks simply produce at more efficient scales than others. Under the scale efficiency version of the efficient-structure hypothesis, since these banks which locate on more efficient scale are also assumed to gain large market shares that may result in high concentration, the positive profit-structure relationship is spurious. At the end of this paper, we try to look beyond market structure and factors of macroeconomic cycle to consider risk as an additional explanatory variable in the profit-structure relationship. Our consideration is that the risk-taking behaviour of financial institutions has in recent years come to the forefront of the debate on the stability of the banking system. Recent interest in the risk issue has been resurrected by the seminal article.

Mahajan et al. (1996) use SURE to analyze the panel data for the translog cost function system of banks. Since, they will include the direct measure of scale economies in the specification model of the profit-structure relationship model; we summarize all empirical results from our translog cost function system here. They find that the coefficient of labor cost (ln P 2) and branch number (B) are positively significant. Labor cost (ln P 2) plays a more influential role in determining total cost. According to the coefficients of all outputs, we may infer that for German banks, producing one more unit of interbank assets (Q 2) will cost much more than producing the other three outputs: total loans (Q 1), equity investment (Q 3) and other investments (Q 4). Since, the coefficient of time (t) is significantly negative; this may imply that technology (e.g. computer, software of exchange system, information system and so on) has helped German banks to reduce their total costs over time. They obtain an average value of overall economies of scale for the German banking industry of 0.2545. This empirical result means that from a cost standpoint, all German banks can obtain the benefit from overall economies of scale by increasing their bank asset size. This conclusion is the same as the results from studies cited in the literature review of Molyneux et al. (1997), although the value is smaller. However, this difference can be explained by the choice of a completely different data set, sample period, number of outputs and definitions of outputs and inputs. For example, based on the choice of our sample set, there is a wide range of asset size within the 298 biggest German banks and until the 298th banks, already quite a lot of small asset size banks are included. This will also affect the shape of the translog cost function. Furthermore, we make use of separate samples to provide us with a comprehensive treatment of the banking industry and determine whether the results are stable across environments. From table IV, we can see the average value of overall economies of scale of public sector banks is 0.3735 and the value of private sector banks is 0.3276.

Cheng and Ariff (2007) take a new approach using factor analysis to identify potential bank-relevant factors to examine if these factors in addition to earnings are also correlated with abnormal returns of bank shares. Factor analysis is used to reduce 21 accounting and financial ratios into four factors, which were then input in the regressions. Their results show high R-square in the regression between abnormal returns and (a) earnings change factor, which indicates a better fit than in studies of nonbanks on the earning-to-price relation. Further evidence found that (b) credit risk factor has significant information content beyond earnings change in the regression with abnormal returns of bank shares.

The other three factors were not found to be significant. In the accounting literature, the study on the earnings response coefficient has basically concluded that earnings effect share prices one is to one (Ball, Kothari and Watts, 1993, Collins and Kothari 1989, Cheng, Ariff and Shamsher, 2001). These studies on response coefficients have spun off other studies in the incremental content literature, when factors other than earnings were used in the multiple regressions. This area of research has identified many other factors that may impact on the earnings response coefficients. This study aims to extend the earnings response query as a research to banks by measuring the influence of bank-related risk determinant characteristics for Australia banks. Australia banking industry has experience six decades of financial inquiries. The Royal Commission of 1937 and Campbell Inquiry of 1981 have completely revamped the Australia financial regulatory regime. The latest Wallis Committee Inquiry in 1997 has separated prudential regulation from Reserve Bank of Australia (RBA) and put it in the hands of a new federal mega regulator, the Australian Prudential Regulation Authority (APRA) in 1998.

Some pertinent highlights of this study are identified. This study is about contemporaneous accounting/financial earnings effect on share prices of banks in Australia market with institutional characteristics quite widely documented as being well deregulated having a liberalized financial system and classified into as a developed economies. As this is a first study of such, we designed this research simply on the basis whether the quite robust generally accepted findings about risk determinants in the returns-to-earnings documented in Cheng and Ariff (2007) can be extended to banks in Australia.

The findings in this paper suggest that accounting earnings is a price relevant variable for banks as well and earnings has a contemporaneous impact on share prices for banks in Australia market. The risk determinants affect the magnitude of the earnings response coefficients that stock prices change in a statistically significant manner in response to earnings increases and decreases are quite evident, as is the case of existing findings. The credit risk factor of banks contributed significantly to the returns-to-earnings relation, which suggests that this is an important factor that enters the investors’ revaluation of bank share prices.

They could compare these results to other banking literature studies, for example, Wetmore and Brick (1990), Chen and Chan (1989) on the interest rate sensitivity. Their findings are that stock returns of banks appear to be more responsive to rising interest rates. Gibson’s (2000) studied the information content of bank loan loss disclosure and found evidence that is consistent with signaling model, that banks taking the largest write-offs turn out later to be the strongest banks, with fewest restructured loans. Such studies however are looking at one aspect of the total risk. This paper moved a step forward by analysing four financial ratios that covered all financial risk factors faced by banks. Therefore, the findings in this study led to the discovery that the credit risk factor does certainly enter banks share valuation in addition to the earnings changes. Finally, three other bank risk factors were not significant.

Borio and Zhu (2008) argue that financial innovation together with changes to the capital regulatory framework (Basel II) have enhanced the impact of the perception, pricing and management of risk on the behavior of banks. Similarly, Rajan (2005) suggests that more market-based pricing and stronger interaction between banks and financial markets exacerbates the incentive structures driving banks, potentially leading to stronger links between monetary policy and financial stability effects. Using a large sample of European banks, we find that bank risk plays an important role in determining banks’ loan supply and in sheltering it from the effects of monetary policy changes. Low-risk banks can better shield their lending from monetary shocks as they have better prospects and an easier access to uninsured fund raising. This is consistent with the "bank lending channel" hypothesis. Interestingly, the greater exposure of high-risk bank loan portfolios to a monetary policy shock is attenuated in the expansionary phase, consistently with the hypothesis of a reduction in market perception of risk in good times.

Reichert and Wall (2000) described in surveys from the banking perspective can be found in reviews the literature on market model estimation. Evidence based on bank accounting data suggests little evidence of diversification. DeYoung and Roland (2001) show that fee-based activities are associated with increased revenue volatility, higher leverage, and increased earnings volatility, while Stiroh (2004a, 2004b) finds that a greater reliance on non-interest income, particularly trading revenue, is associated with more volatile returns and lower risk adjusted profits. DeYoung and Rice (2004b) identify a variety of banking strategies and show clear risk/return trade-offs that may make several strategies viable, e.g., high risk and high return in corporate banking vs. low risk and low return in community banking. Stiroh and Rumble (forthcoming) argue that diversification benefits exist for BHCs that expand into non-interest generating activities, but these gains are typically more than offset by increased exposure to more volatile activities so risk-adjusted performance suffers. That is, the increased share of volatile activities outweighs the traditional diversification effect via the covariance. In terms of diversification of lending activities, Acharya et al. (2002) report that diversification of loans does not typically improve performance or reduce risk, while Morgan and Samolyk (2003) examine geographic diversification and report that a broader presence is not associated with greater returns (ROE or ROA) or reduced risk and Pilloff and Rhoades (2000) show that geographically diversified banks do not have a net competitive advantage. Studies of banks using equity market data offer a mixed picture.

This study contributes to the literature in several ways. First, this study illustrates the usefulness of combining two SCF data sets to obtain sample sizes. Information from both 1998 and 2001 SCFs is used to observe loan-pricing patterns in the collateralized credit (mortgage and automobile) and credit card markets. The larger sample sizes will increase the reliability of descriptive and multivariate tests. Second, this study takes advantage of questions in the recent SCF to identify households with more severe delinquency problems and proxy for poor credit history. With this proxy, credit rejections are reexamined to see if creditworthy borrowers face binding credit constraints or if these rejections are justified given the information on borrower creditworthiness (or lack thereof). Third, after demonstrating that most credit denials can be justified on the basis of credit quality, consumer participation in various credit markets will be evaluated by observing credit pricing patterns and anomalies. Certain pricing anomalies may now serve as better indicators of credit market inefficiencies.