Sample Economics Coursework Paper on Risk of Credit Concentration

Risk of Credit Concentration

Introduction

Extension of credit through a nation’s federal saving associations, which are collectively, the National banks, saving institutions and credit unions, acts as one of the primary sources of revenue for a nation. Concurrently, credit extension is likely to pose risks to the capital and earnings of these banks. Limiting risk concentrations by banks is essential for a country and its bank supervisors. If banks in a given country have a large credit exposure to a single borrower, a group of borrowers who are related or a sector of the economy, it may result in massive financial loss or failure of the banks when an economic sector or creditor encounters financial problems (Garcia Cespedes et al. 2005). Management of risk of credit concentration, also referred to as a pool of exposures, involves ensuring that the performance of the collective pool credit is well management such that a bank is not affected by even one individual transaction within the pool. The risk of concentration of credit has been a key source of issues in the banking sectors of the majority of countries. The financial instability of the banking sector in European countries including the UK, France and Portugal resulted from the credit concentration risk. There are two different types of credit concentration risk that include the name concentration and it is associated with imperfect diversification (Düllmann & Masschelein 2006). This is concerned with idiosyncratic risk in the portfolio resulting from an exposure that is either small or large to particular individual obligors. Another type is the sector concentration associated with imperfect diversifications in factors of a given sector that are also referred to as systematic components of risk (Calabrese & Porro 2012).

Risk of credit concentration on developed countries

According to historical experiences in some developed countries, the concentration of credit risk in their asset portfolios had been a significant cause of distress in their banks. The concentration risks occurred in both individual banking institutions and the entire banking systems a country. Large borrowers such as Parmalat, Enron and Worldcom and are some of the institutions that have experienced huge losses in the banking industry. In the 1980, major banks in the U.S experienced financial problems as a result of their large exposures to countries that were less developed. These debts highlighted how the stability of an entire banking system can be affected by the excessive exposure to a single asset class. Additionally, in the U.S, banks in Texas and Oklahoma faced huge losses in the 1980s by lending to both commercial and corporate real estate businesses (Zakamouline & Koekebakker 2009). The losses could be explained by the strong correlation that existed between the local demand for commercial real estate and the health of the energy industry, which also had a high concentration of lending (Düllmann, 2005). These historical occurrences of credit concentration risk illustrate the significance of measuring concentration risk of banks credit portfolio that may result from not only exposure to a class of asset or single credit but also from the relationships between classes of assets.

Before these occurrences, there were no measures to prevent the risk of credit concentration because there was a gap that existed between the true underlying risks of a portfolio and the capital requirements. The countries banking systems operate under the guidance of the Basel Committee on Banking Supervision. The committee’s Basel II Framework had come up with an Asymptotic Single-Risk Factor Model that emphasizes the calculations of the internal ratings- based (IRB) approaches (Düllmann 2005). However, the presence of concentration risks portfolio violates the assumptions of this model. A stylized world behind the assumptions of the ASRF model exists. This stylized world deviates from the real world because there are significant deviations of economic capital from Pillar 1 capital charges in the IRB approach (BCBS, 2006).

The ASRF model framework assumptions are that the portfolios of banks are perfectly fine-grained implying that there is diversification of idiosyncratic risk. This assumption implies that the total portfolio exposure is only comprised of a smaller share of the largest individual exposures (BCBS, 2014). The second assumption is that only one source of systematic risk exists. Meaning that there is a proper diversification of bank portfolios across geographical regions and different sectors such that the performance of the economy is the only systematic risk remaining (BCBS, 2014). Thus, it is only possible to conduct a bottom-up risk assessment of a credit portfolio where these assumptions hold. This is because the idiosyncratic risk is fully diversified and the systematic component of risk is the only one that needs assessment. The assessment can then be done at the level of individual exposure, and the assessment of the whole portfolio is obtained by adding the results of each exposure. This IRB approach does not allow for the rich correlation structure that may exist between individual risks and it relies on individual credit assessments. For this reason, it was not possible to put measures in concentration risk (Bellalah et al. 2015).

Since the ASRF model does not support the explicit measurement of concentration risk, the Basel Committee on Banking Supervision launched a project that would help in identifying different methods that would account for concentration risk in portfolios. The methods focused on the two different types of concentration risk, name concentration risk and sector concentration risk (BCBS, 2006). These methods complement the single factor model that does not capture name and sector concentrations. The committee came up with a proposal that would allow for adjustments of Basel II for imperfect portfolio granularity. The revised method takes into consideration the recent analytical advancements and tackles some of the practical challenges in the earlier proposal. For sector concentration, various methods of dealing with it have been proposed such as the multiplicative adjustment to the ASRF model that uses a more general calibration to a multifactor model to incorporate concentration risk. Stress tests have also been used to detect the excessive concentration of either type and give an estimate of economic capital stress scenarios. For a stress test to be desirable, it has to be consistent and plausible to the credit portfolio model that is being employed to the portfolio that is being considered as well as be reportable to senior management. Technical issues that need to be in mind while dealing with the overall issue of concentration risk in credit portfolio includes the selection of a sector scheme that is adequate for the assessment of concentration risk. There should be a benchmark for concentration risk correction and issues related to data (Düllmann 2005).

In addition to the new models of measuring concentration risk, limits on large exposures have been are provided by regulatory authorities to prevent the occurrence of concentration risks. For instance, the European Union does not allow its credit institutions to offer credit to a customer or a group of customers who are connected amounting to a value that is higher than its funds by 25 percent. (This means that the amount of credit that can be offered should not exceed 25% of the funds held by the credit institutions) The percent limit is reduced to 20 percent where the client or group of connected clients is the parent or subsidiary of the credit institution or where they are one or more subsidiaries of the parent.  However, where other procedures or measures are used to provide specific monitoring, member states are exempted from exposures subjected to 20 percent limit. They are then supposed to reveal the contents of these measures to the Commission and the Banking Advisory Committee. A credit institution is not allowed to provide credit that will amount to 800 percent of its funds.

Risk of credit concentration on the Economic and Monetary Union of West Africa (WAMU) countries

Credit concentration on WAMU countries before the establishment of the Union

The West African Monetary Union was established in1948 as well as its regional currency zone. Before the formation of the Union, the majority of the credit institutions were facing serious problems and were in a state of quasi-bankruptcy (Gottschalk 2014). Distressed banks that had a share of 23% in total bank deposits contributed to about 30% of the credit to the economy. The banking industry was also characterized by a significant deterioration in the portfolio of the banking system that was comprised of non-performing loans. There was a serious problem of inadequate capital and inadequate level of resources. The financial structure had major imbalances, such as the short-term liquidity crunch which led to an inability to meet withdrawals made by the public and dependency on normal financing from the central bank and overdraft facilities (Gottschalk 2014).

 The central bank had to take some precautionary actions because of the distress the banking systems of the countries in the union were experiencing. The central bank introduced to the union specific ratios that were in line with the Basel Committee on banking supervision. These included a minimum capital requirement of CFAF 1 billion for the commercial bank and CFAF 300 million for Non-banking financial institutions. A minimum capital adequacy ratio of 4 percent was adopted while the minimum requirement for liquidity ratio was set at 60 percent. In the case of division of risk, individual norm limitation (% capital base) was set at 100 percent, and the global limit for loans representing more than 25 percent of the capital base was set at 10x capital base. The minimum coverage of medium or long-term liabilities by medium or long-term assets was adopted as 75 percent while insider lending (as % total lending) was adopted as 20%. The portfolio risk structure (% low-risk loans) was 60 % while the maximum ratio of fixed assets and equity investment to capital was 100%. The maximum ratio of the off balance sheet fixed assets to capital was 15 percent (Seck 2012).

The history of risk of credit concentration (same structure as developed countries) after the creation of the WAEMU

The customs union of the West African Economic and Monetary Union (WAEMU) was established in 1994 in the same zone with WAMU.  It is also referred to as UEMOA and comprises of eight countries that create a monetary zone, which uses the CFA Franc as a common currency. The currency is issued by Banque Centrale des États de l’Afrique de l’Ouest (BCEAO), the common central bank of the zone. The Union also enables the pooling of international reserves, free transferability within zones and a unified monetary policy. The monetary reserves of the member states are held in the central bank, which is also responsible for maintaining at least 65% of its foreign reserves at the French Treasury. The central bank regulates the expansion of credit throughout the region (Leon 2012).

Under the BCEAO, the region launched a Banking Commission in1990, which is tasked with the responsibility of regulating and supervising banks within WAMU. The commission carries out on-site inspections and scrutinizes the monthly statistics of all registered banks and financial institutions. The commission has the powers to put into effect ratios using sanctions such as increased monitoring as well as taking disciplinary actions. It is the responsibility of the Ministries of Finance to implement the decisions of the Banking Commission (Imam & Kolerus 2013).

WAEMU exposures involve the balance sheet risks like the held securities and off balance sheet liabilities. Borrowers are considered to be connected if they are persons or legal entities that represent a similar view of risk since one of them has holds direct or indirect controlling interest that may be either considerable influence, exclusive or joint control in the other. Secondly, it refers to the persons or legal entities that have an association whereby if one experiences a particular financial problem the other would similarly suffer from financial difficulties. This kind of link exists between persons or legal entities in various cases including being related to the first degree. They belong to subsidiaries of the same parent company, they are subject, de facto, to same management, and one of a public institution or local government and the other depends on it financially (Leon 2012).

The WAEMU Council of Ministers adopted a revised set of prudential ratios in July 1999 that came into effect in January 2000. In the new threshold, there have been no significant changes from the old ones under WAMU except for the minimum capital adequacy ratio, which is 8 percent. The minimum requirement for liquidity ratio is 75 percent (Imam & Kolerus 2013).  This means that West African Economic and Monetary Union, the total amount of risks that can be offered for exposure has a limitation of 75 percent of the effective capital of the financial institution or bank. The guidelines for risk where a single client is not allowed to borrow more than 75% of a bank’s funds has been violated by 43 banks, which represent 70% of deposits. In 2000, a share of 7.5% of non-performing loans in banks portfolios was experienced rising from 6.4% in 1999. This was as a result of overdue crop credits, necessitating changes in the structures of the cash cropping systems of a number of the WAEMU member states (Kablan 2007).

The WAEMU Council of Ministers also established the Rating Agreements mechanism in 1990 and amended it in September 2002. This framework requires banks and financial institutions within the Union to submit rating agreement applications to the BCEAO, for at least fifty largest credit risks in their portfolios. The BCEAO also came up with financial soundness indicators for all the countries in the union and the indicators highlighted there was relative soundness in the regional banking system (Kablan 2007). However, the concentration of financing on a few large businesses makes the system vulnerable to credit risks. The bank also undertook measures to prevent crises in the banking sector by introducing suitable tools such as coming up with a mechanism to conduct stress and early warning tests for banking crises in WAMU (Sy 2006).

History of Risk of credit concentration in Guinea-Bissau

Since Guinea-Bissau attained independence in 1974 from Portugal, it has experienced significant political turmoil and economic challenges. This made it impossible for the country to attain sustainable development outcomes. The economy has been highly dependent on cashews as its only cash crop. The financial sector in Guinea-Bissau is mirrored by its categorization as a fragile state by a majority of its development partners and donors (Beck et al. 2011). The 1998/99 civil war led to its complete collapse resulting to a financial system that is still largely undeveloped. Access to finance is still a major constraint for private sector business, and more than 25 percent of the lending by banks is associated with the production of cashew nut (Maimbo and Triki 2011).

Before Guinea-Bissau joined WAMU in 1997, the country’s central bank was the Banco Central da Guine-Bissau (BCGB). 1n 1989, the country reformed had radical reforms in its banking system. Currently, the country has two private commercial banks (IMF 2013)

Guinea-Bissau has a financial system that is comprised of a small banking sector characterized by four small banks whose balance sheet does not exceed XOF 100 billion. The country also has three insurance companies and about a dozen decentralized financing companies. Bank lending is mainly used in the area of pre and post cashew nut harvesting financing as well as to small processing plants and trading advances to exporters. Lending so much in the cashew sector is likely to lead to concentration risk. There should be policies that emphasize introduction of the sector and macroeconomic policies that support economic diversification.  The country has issues with the implementation of its capital adequacy requirements that are either less than or equal to those laid out in Basel 1. As at the end of 1012, the BCEAO banking committee reported that Guinea-Bissau credit institutions had a reduction of 4.6 percent in their total balance sheet as compared to 2011. Moreover, the outstanding overdue due rose by 521.3% from 2011 to 2012 and the volume of unpaid loans increased by 51 percent during the year 2012. These issues highlight the extent of financial vulnerability experienced by the nation that is associated with its inability to supervise and act on the issues.

Conclusion

Loan exposures may represent a credit concentration risk that cannot be mitigated or avoided easily. Developing countries may have their banks increasing concentration risk due to the limitations of their geographic markets and the situation of their local economies and the requirement that federal savings associations should have a portion of their portfolios in specific categories of assets. Developed countries may also develop of credit risk due to the limit of exposures that are found within the portfolio (Senbet and Otchere 2006). The management and control of the concentration of risk is paramount, and various ways can be applied in the mitigation of concentration risk. One of the ways is including in a portfolio of loans borrowers who are not involved in businesses that are correlated. Secondly, exposure limits can be altered which may involve adjusting commitment limits or amounts outstanding (Dabla-Norris et al. 2014).

References

Basel Committee on Banking Supervision., 2006. Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework – Comprehensive Version, (Basel: Bank of International Settlements.

Basel Committee on Banking Supervision., 2014. Supervisory Framework for Measuring and Controlling Large Exposures, (Basel: Bank of International Settlements).

Beck, T., Maimbo, S.M., Faye, I. and Triki, T., 2011. Financing Africa: through the crisis and beyond. World Bank.

Bellalah, M., Zouari, M., Sahli, A. and Miniaoui, H., 2015. Portfolio Credit Risk Models and Name Concentration Issues: Theory and Simulations. International Journal of Business20(2), p.111.

Calabrese, R. and Porro, F., 2012. Single-name concentration risk in credit portfolios: a comparison of concentration indices (No. 201214).

Dabla-Norris, E., Ho, G., Kochhar, K., Kyobe, A. and Tchaidze, R., 2014. Anchoring Growth: The Importance of Productivity-Enhancing Reforms in Emerging Market and Developing Economies. Journal of International Commerce, Economics and Policy5(02), p.1450001.

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Düllmann, K., 2005. Measuring business sector concentration by an infection model (No. 2006, 03). Discussion Paper, Series 2: Banking and Financial Supervision.

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Gottschalk, R., 2014. Institutional Challenges for Effective Banking Regulation and Supervision in Sub-Saharan Africa.

Imam, P. and Kolerus, C., 2013. West African Economic and Monetary Union: Financial Depth and Macrostability. International Monetary Fund.

IMF., 2013. Article IV Consultations – Guinea-Bissau, IMF Country Report No 13/197.

Kablan, S., 2007. Measuring bank efficiency in developing countries: The case of WAEMU (West African Economic Monetary Union). African Economic Research Consortium, pp.113-138.

Leon, F., 2012. Financial Sector Competition in West African Economic and Monetary Union. Centre d’études et de recherches sur le développement international, Études et Documents, (2012/14)..

Maimbo, S.M., Faye, I. and Triki, T., 2011. Financing Africa: Through the Crisis and Beyond. World Bank Publications.

Seck, D., 2012. Fifteen Years of WAEMU: Results and Strategies for the Future. In Wealth through Integration (pp. 19-42). Springer New York.

Senbet, L.W. and Otchere, I., 2006, January. Financial sector reforms in Africa: perspectives on issues and policies. In Annual World Bank Conference on Development Economics 2006: Growth and Integration (pp. 81-120).

Sy, A.N., 2006. Financial integration in the West African economic and monetary union (No. 2006-2214). International Monetary Fund.

Zakamouline, V. and Koekebakker, S., 2009. Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance. Journal of Banking & Finance33(7), pp.1242-1254.