March 2008 working paper no. 330 Issn 1975-5163 Joon-Ho Hahm
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Non-Interest Income of Commercial Banks
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- . Introduction
- . Literature Review
- . Methodology and Empirical Results
Keywords: Commercial Bank; Non-interest Income; Bank Profitability; Bank Risk; Macroeconomic Volatility JEL Classification: G2; E5 1 Ⅰ. Introduction The evolution of Korea’s banking industry since the 1997 financial crisis can be characterized by both financial consolidation and conglomeration. While bank consolidation is a result of merger and acquisitions within the same industry, conglomeration is a result of strengthened cross-sector activities between bank and non- bank financial institutions. The conglomeration trend in the banking industry is a global phenomenon driven by deregulation and increased competition, both of which have eroded traditional comparative advantages of banks. Banks in the US and Europe have reacted to declining market share and profitability by expanding non-traditional businesses. Korean banks are also making effort to diversify their revenue sources toward non-interest income such as fee-based financial services. However, it is uncertain whether these shifts can lead to higher and more stable earnings for commercial banks. The profitability and risks of banks can be impacted by financial conglomeration through various channels. First, profitability and earnings potential can be enhanced if banks exploit and realize scope economies from product diversity and cross-selling opportunities. For instance, banks in a financial group can share marketing and distribution channels as well as database and IT systems, spreading out their fixed costs. With enhanced profitability and cost efficiency, bank insolvency risk can be reduced, and higher charter value in turn reduces moral hazard incentives of banks. 2 Second, conglomeration may lower the riskiness of individual banks since it provides greater opportunities for risk diversification. Cross-industry diversification may contribute to reductions in earnings variability if returns are sufficiently heterogeneous across different financial services. On the other hand, banks can be exposed to unexpected shocks, arising from the capital market and other financial sectors, through their non-bank financial affiliates. Third, while large and complex banking organizations may be able to benefit from the scale and scope economies and risk diversification, operational risk may substantially increase with growing organizational complexity, inefficiencies in management and internal control, and difficulties of harmonizing risk management. (Group of 10, 2001) Furthermore, for the financial system as a whole, banking sector consolidation and conglomeration may increase systemic risk potential. Although the extent of diversification may increase at individual bank level, large banking conglomerates tend to share increasingly similar characteristics in their business portfolios and asset structures. This paper studies implications of the changing revenue structure of commercial banks in the era of financial conglomeration. On a bank level, we can take the amount of revenue generated through non-bank activities as a proxy for bank conglomeration. By focusing on the non-interest income share of commercial banks, this paper empirically assesses benefits, risks, and potential determinants of bank revenue diversification. Since the shift toward non-interest income has been a global phenomenon caused by recent progress in financial deregulation and disintermediation, we investigate multi-country 3 evidence by utilizing firm level data of 662 relatively large commercial banks in 29 OECD countries. More specifically, this paper addresses the following questions: What are the factors that influence the degree of non-interest income diversification on a bank level? In addition to bank specific factors, are macroeconomic factors important determinants of the non-interest income ratio? What are the impacts of the expansion toward non-interest income on bank profitability, capital adequacy, profit variability and insolvency risks? What are the impacts of the increasingly homogeneous bank revenue structure within countries on macroeconomic volatilities? The paper is organized as follows: Section 2 overviews the existing literature. Section 3 describes data, methodology and empirical findings. Section 4 summarizes and concludes. 4 Ⅱ. Literature Review The structure of the international financial industry has changed dramatically over the past twenty years and these changes have been documented extensively in the literature. One notable feature of this change is in the composition of financial institutions’ businesses and product lines, namely, a movement towards financial conglomeration. This shift stems from a more competitive market environment in which financial institutions are actively seeking strategies to cut costs and enhance revenue. In order to better understand the effects of conglomeration, we must first understand factors driving the recent surge in banks’ shares of non-interest revenue. Widespread deregulations accompanied by technological development have reshaped the profit structure of banks. There now exist more efficient means of production of financial information and better techniques for assessing and pricing risks, which have shifted firms’ financial demands from traditional bank loans to non-bank funding sources such as corporate bonds and commercial papers. At the same time, there have been changes in the structure of financial savings with household portfolios moving away from bank deposits towards more diverse non-bank and capital market related products (Davis and Tuori, 2000). Under the increased competition and with the increased demand for diverse financial products, commercial banks have been increasingly diversifying their financial services as a means of realizing scope economies. 5 On a bank level, there are several factors that have led to banks’ decisions to diversify their revenue structure. Rogers and Sinkey (1999) find that bank size is positively correlated with non-interest income, while net-interest margins and core deposits are both negatively correlated with non-interest income. Banks with fewer core deposits and lower net-interest margins earn less revenue from traditional interest income sources and so they must transition into non-traditional banking in order to remain profitable. De Young and Hunter (2003) and De Young et al. (2004) laid forth two banking strategies that help to explain the role that bank size plays in conglomeration. Relatively large banks make use of economies of scale in order to dominate the production of consumer loans. Despite their low unit costs, the market for these products is very competitive, and in order to make this model profitable, large banks must supplement their revenue stream with non-interest income. Smaller banks are able to earn higher interest margins, despite their relatively high unit costs. This is because they can charge higher interest rates due to higher switching costs on the part of borrowers. They can also pay lower interest rates because of their relatively loyal customer bases. Therefore, for smaller banks, non-interest income is less important. The diversification of bank revenue sources has also led to empirical research on the question of how non-traditional bank activity affects profitability and risk. The evidence seems to be mixed and varies from study to study. Saunders and Walter (1994) review 18 of the related studies that examine whether non-bank activities reduce bank risk. 6 They conclude that the evidence is mixed, with differing results across geographical regions. In the US, most studies agree that the diversification benefits of non-interest income are somewhat limited and that it often serves to increase bank risk. In Europe results have been more in line with the conventional wisdom that non-interest income stabilizes profit and thus offers diversification benefits. In analyzing the risk associated with non-interest income the empirical literature has taken two broad approaches: counterfactual simulation studies and studies that use data from banks that are actually involved in diversification. The counterfactual studies simulate mergers between banking and non-banking institutions and then analyze the riskiness of the simulated financial institution. These studies seem to support the hypothesis that small scale non-banking activity can reduce risk and increase profits. Wall et al. (1993) find that for 1981-1989 diversifications into insurance, mutual funds, securities brokerage, or real estate led to higher returns and lower risk. Boyd et al. (1993) use data for 1971-1987 and find that a bank holding company can reduce risk by merging with insurance firms, but will increase risk by merging with securities or real estate firms. Recently, Lown et al. (2000) find that diversification into life insurance has the biggest potential to reduce risk. Recent studies that directly investigate banking data to analyze profit and risk show mixed evidence on the impact of non-interest income. Using US data, Stiroh (2004a) finds that, in the aggregate, non-interest income is quite volatile and increasingly correlated with interest income, suggesting that there are few diversification benefits 7 associated with non-interest income. At the bank level, he finds that a greater reliance on non-interest income, especially trading income, tends to decrease risk-adjusted profits and increase risk. Stiroh (2004b) finds similar results for smaller community banks. De Young and Rice (2004) find that well-managed banks expand more slowly into non-interest activity and that greater levels of non-interest income are associated with poorer risk- return tradeoffs. De Young and Roland (2001), using 472 US commercial bank data between 1988 and 1995, find that non-traditional activities of banks are associated with both higher revenue volatility and higher total leverage. They suggest three observations as potential explanations for why fee-based banking is not necessarily more stable than traditional banking. First, there are considerable costs associated with changing lenders; so traditional loans are usually quite stable. These costs are not associated with abandoning fee-based services. Second, increasing fee-based services often requires substantial fixed costs. Banks must invest in new technology and staff. These costs serve to increase the operational leverage of banks. Third, fee-based services do not have significant regulatory capital requirements, suggesting that they increase financial leverage and thereby risk. Since, many of the characteristics that lead to conglomeration are country specific, the levels of non-banking activity may also differ across borders (Davis and Tuori, 2002 and Smith et al., 2003). Also, since cost-efficiency frontiers differ across borders, efficiency changes are likely to differ depending upon geography. Fecher and Pestieau (1993) find that measures of efficiency are correlated with levels of regulation and 8 competition in OECD countries. It follows that empirical analyses of non-interest income in Europe draw different conclusions than the work conducted on banks in the US. Smith et al. (2003) use a portfolio view of banking to analyze 2,655 banks within 15 European countries from 1994-1998. They find that, although non-interest income is positively associated with revenues, the positive effect is offset by the higher operating costs that accompany fee-based services. Furthermore, they find that, while volatile, the income from these services serves to stabilize profits. They also draw a different conclusion than Stiroh (2004a) about the relationship between non-interest income and interest income, finding that the two are negatively correlated suggesting potential diversification benefits. This difference could stem from the fact that fee-based banking has played a minor role in Europe than in the US (Davis and Tuori 2002). Valverde and Fernandez (2007), using European bank data, also find that revenue and market power increase as output becomes more diversified towards non-traditional activities in banking. As for the system-wide risk, there is concern that as the industry moves toward conglomeration, systemic risk potential may increase. First, increased concentration of the financial industry around a small number of large banking conglomerates that are too big to fail may significantly increase systemic risk potential. The emergence of a few large banking institutions may also undermine the effectiveness of financial supervision and market monitoring. Increasing complexity of financial conglomerates would make it more difficult for regulators and market participants to comprehend risks and take early corrective actions. As a consequence, excessive risk taking and moral hazards on the part 9 of large banks may lead to higher systemic risk potential. Increasing degree of interdependence among the large and complex banking conglomerates is another source of systemic risk potential. The Group of 10 Ferguson report (2001) indicates that areas of direct interdependency include mutual credit risk exposures through inter-bank loans, on and off-balance sheet activities such as financial derivatives, and payment and settlement relationships. The systemic risk potential may also increase if large conglomerates are simultaneously and similarly exposed to adverse shocks due to homogeneity in asset and revenue structures. While banking conglomerates are able to diversify within each group, they are getting more homogeneous as business areas become increasingly similar. Resulting indirect interdependencies among large conglomerates may raise systemic risk potential as well. Finally, financial conglomeration may aggravate the problem of systemic risk as banks expand their involvement in high risk activities that are closely tied to non-bank financial firms and capital markets. As a result, banking institutions would be more vulnerable to contagion risks from non-bank and non-financial sectors as well as capital markets. Examples include banks’ active securitization of mortgage and credit card loans. The use of identical brand names for affiliated non-bank subsidiaries may also erode the firewall within a conglomerate and increase pressure for banks to bail out affiliated non- bank subsidiaries. The shift of financial savings from bank deposits to affiliated non-bank financial subsidiaries also implies a de facto extension of the public safety net. The body of empirical literature on systemic risk is somewhat limited. G10 report 10 (2001) suggests that interdependencies among large and complex banking organizations have increased over the last decade in the US and Japan and began to increase in Europe. De Nicolo and Kwast (2002) investigate the systemic risk potential presented in the US banking industry over the period of 1988-99 based upon correlation measures of stock returns of large and complex banking organizations. They find a positive consolidation elasticity of stock return correlations and interpret the evidence as suggesting that systemic risk potential increases with consolidation in the banking industry. As for the cross-country studies, empirical evidence seems to be mixed. Beck et al. (2003), using a logit model, find that banking crises are less likely in countries with a more concentrated banking system. On the other hand, De Nicolo et al. (2003) report that the aggregate z- score index obtained from the top 5 banks in each country is significantly negatively associated with the degree of bank concentration. Namely, bank consolidation is positively associated with the systemic risk potential. In Korea, some recent studies examine the consequences of financial conglomeration on profitability and risks of commercial banks. As the conglomeration trend is a relatively recent phenomenon, the empirical evidence is still mixed. Kang (2001) investigates the risk impact of non-interest income using z-score and return on assets’ variability for commercial banks. He finds that the expansion of non-interest businesses such as securities trading contributes to the reduction of banks’ earnings risk. Bae (2006) also finds that non-interest income contributes to higher profitability as well as lower profit variability in Korea, and interprets this positive evidence as resulting from the fact 11 that Korean banks focus on relatively stable fee income and credit card businesses rather than securities, foreign exchange and derivative activities. Hahm and Kim (2006) perform a more general study of the z-score index and its risk components for financial conglomerates in Korea. In their panel regressions, they find that, during the post-crisis period of 2001-03, asset size is significantly positively related to profitability and significantly negatively related to risk as measured by the standard deviation of ROA. However, they find no significant conglomeration effects on profitability and risk after controlling for the size effect. Oh et al. (2007) investigate the systematic and idiosyncratic components of risks as measured by stock prices of Korean banks and find that financial conglomeration tends to stabilize financial risks. As for the systemic risk potential, Hahm and Hong (2003) provide a diagnostic analysis of various channels through which financial consolidation and conglomeration influence financial stability. They find that both direct and indirect interdependencies among large banks have increased substantially after the crisis in Korea, which may have also raised the potential for systemic risk. Using bank panel data from 1999 to 2004, Kang (2007) also finds that herd behavior among Korean commercial banks has increased after the crisis. He also reports evidence that increases in asset size and expansion of retail businesses have negatively affected bank stability, while business diversification and governance transparency have exerted positive effects on bank stability. |
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