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Wednesday, March 11, 2015

Banking & Research - XI : Basel II

As a counter to the challenges of recurring financial crisis faced by the international financial architecture since the early 1980s, the Bank for International Settlements has designed certain financial standards and codes that are commonly referred to as the Basel Committee recommendations. The first of such recommendations came in the form of a set of minimal capital requirements for banks, popularly known as Basel I standards. These recommendations primarily focused on the definition of the capital that can absorb losses resulting from credit risk. As recommended by the Narasimham Committee-I, the Reserve Bank of India implemented the Basel I norms in April 1992. The banking system of the country responded to these directives positively and implemented the norms quite successfully.

However, over a period of time, banking systems all over the world felt Basel I was just a ‘one-fit-all’ approach for capital regulation as all the corporate borrowings carried the same risk weight of 100%. Secondly, it resulted in a significant gap between the measurement of regulatory risk and  economic risk, as actually experienced by individual banks. Thirdly, the norm was considered to be procyclical as the default risks were normally linked to the levels of activity. Fourthly, with the convergence of financial markets and technology, banks have become more sophisticated in measuring and managing risks hence demanding a change in the regulatory norms. As a sequel to the Basel I norms, the Basel Committee on Banking Supervision drafted the Basel II norms, which are to be implemented by the end of 2006. Basel II rests on three essentials: One, the capital adequacy norms to be improved by making banks put aside higher levels of capital for high credit risk borrowers and vice versa; two, effective supervisory review of risk management and capital allocation by central banks; and three, banks are to be transparent in their public reporting so that market discipline can ensure better management of banks. The Reserve Bank of India has in turn released its draft guidelines on Basel II, thus directing banks to draw a road map for its implementation from March 2007.

Against this backdrop, the article, “Indian Banking System—Gearing up for Basel II” attempts to assess the preparedness of the Indian banking system for the New Basel Capital Accord. It also throws light on the challenges that the banking system may face while  implementing Basel II. The article reveals that the proportion of risk weighted assets to total funded assets is likely to go up by 15 to 30% owing to increased operational and market risk. This is likely to pose a challenge to the ability of nationalized banks other than the State Bank group and private sector banks, in order to maintain a capital adequacy of 12% after implementation of Basel II. To meet these challenges, the article proposes consolidation of banking system through an orderly merger and acquisition process, based purely on expected synergies. Secondly, it directs banks to build up reliable databases on risk management practices, particularly under credit risk, for a minimum period of five years to effectively switch over to Basel II. Thirdly, banks are advised to nurture a robust credit culture in terms of credit appraisal, delivery and its monitoring, which alone can help them remain competitive. Lastly, the Indian banking system has to put corporate governance of international standards into practice. The article, however, does not comment on other vital issues such as the competency of human resources to handle newer technologies being brought into banks for data management; risk management in forex and money markets and others; delivering business in new areas such as derivatives, securitization and so on; the need for developing and creating a pool of leaders who can think strategically and can provide direction for organizational rebuilding and repositioning in the complex time that lies ahead. The article, thus, throws open new areas under Basel II implementation for further research.

The next article, “Computation of EVA in Indian Banks”, throws light on the current soundness of Indian banking system by computing EVA for major banks, and states that contrary to the earlier belief, Indian banks are creating economic value for their shareholders. The study also reveals that public sector banks outperform their private counterparts, though their cost of capital is high. Interestingly, the article identifies a negative relationship between EVA and non-performing assets of banks. It also incidentally supports the assertion voiced by the previous article that Indian banks are today prepared well to adopt Basel II, than they were while implementing Basel I.

Market structure is an important determinant of both competitiveness and consumer welfare. The ongoing reforms in the banking sector are expected to result in a more competitive structure but the scope for emergence of a monopolistic market cannot be ruled out. The article, “Market Structure of the Indian Banking Sector”, attempts to examine the market structure of Indian banks, using standard methods like Herfindahl Index, Concentration Index and H-Statistic. The study reveals that the market structure is monopolistic. This conclusion, however, calls for further research as banking market structure, unlike other market segments, is governed by the Central Bank directives. Hence, the delivery process of the services, pricing of services, modalities of contracts, etc., tend to look alike and may mislead one to conclude that the market is monopolistic, though it is actually monolithic.

The relationship between exchange rates and exports is quite an exciting area of research. It is often believed that a depreciating domestic currency vis-à-vis a trading partner’s currency, makes exports more competitive thereby giving a big boost to exports. However, as more and more countries are deregularizing, and the exchange rate determination is moving away from the central banks’ regulation to market determination, depreciation or appreciation of currency is losing its potency in impacting exports. In fact, research reveals that international goods market and the foreign exchange market are jointly efficient in the random walk sense. As a result, there exists no room for arbitrage between the two markets to profit from temporary price discrepancies. Against this backdrop, the article “Exchange Rate Volatility and Trade Balance: An Indian Study”, makes an attempt to find the relationship between the trade balance of India and exchange rate volatility by using the data for the period, January 1993 to March 2004. The author has used two measures of volatility to find out its impact on the trade balance of India. The study reveals that exchange rate volatility has no significant impact on the trade balance of India, while exchange rate has a significant positive impact. World trade is found to influence the trade balance negatively. It is also revealed that lagged values of exchange rate do not have significant impact on the trade balance. In other words, the study states that there is no ‘J-curve effect’ on Indian economy.

As the corporate world is fast becoming multi-locational, and markets are getting integrated, forecasting of exchange rate has become a critical input for corporate decisions. Usually, those in the corporate world having exposure to foreign currencies stand exposed to two kinds of risks: Account exposure, where changes are effected in the value of a firm’s foreign currency denominated accounts due to the change in exchange rates; and  cash flow exposure, which has a direct impact on the profitability of a firm. Normally, exchange rates are forecast in two broad ways: By using a multivariate approach, where it is perceived that a country’s exchange rate has a relationship with other macroeconomic fundamentals such as money supply, inflation, interest rate, balance of payments, etc.; and by using univariate models, such as the autoregressive integrated moving average model. Against this backdrop, the article, “Forecasting Exchange Rate: A Univariate Out-of-Sample Approach” uses the Box-Jenkins methodology (ARIMA model) to forecast the exchange rate movement by using the data from March 1992 to December 2002, and checks its forecasting ability by using the data from January 2003 to June 2004. The study reveals that the ARIMA model provides a better forecasting of exchange rates than the simple autoregressive models or moving average models. The findings of the article encourages further research to check the superiority of newer models, such as the Bayesiam Vector Auto Regression, Bayesiam Vector Error Correction Model, Exponential Smooth Transition Auto Regressive Model,  and such others.

Courtesy : IJBM Vol IV No 2 2005


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