Banks are essentially known for transferring financial resources from net savers to net borrowers. This intermediation is basically achieved through four transformation mechanisms: liability-asset transformation, size transformation, maturity transformation, and risk transformation. It is in this context that banks are exposed to various embedded risks such as market risk, credit risk and operational risk. Secondly, banks being highly leveraged, these inherent risks have enough potential to inflict catastrophic losses unless they are managed effectively. Hence, Merton Miller, the Nobel Laureate said: “Banking is 19th century disaster-prone industry.” This has resulted in the need for effective risk management across the financial architecture. For, failure of one bank can pull down a country’s very financial system.

Realizing the criticality of ‘contagion’ risk, and the need for its effective management, the Bank for International Settlement (BIS) came up with guidelines way back in 1988, which are popularly known as Basel I for implementation across the globe, so that all banks are supervised according to a set of broad principles. Under these norms, it was for the first time suggested that banks should maintain certain minimum capital as a ratio to its risk-weighted assets, so that a bank will remain capable of absorbing losses emanating from credit risk in the long run.

Basel I norms were simple: it adopted a straightforward ‘one-size-fits all’ approach. It failed to recognize that there could be a differing credit quality within the same class of assets. It failed to create a level playing field for banks—it taxed some activities while understating some risks of others. To obviate these limitations of Basel I, the Basel Committee came up with a revised framework—International Convergence of Capital Measurement and Capital Standards (Basel II)—in June 2006. Basel II is considered as more risk-sensitive than

Basel I. It essentially rests on three mutually reinforcing pillars: the first pillar prescribes minimum capital requirements for credit, market and operational risk; the second pillar prescribes supervisory review, risk management guidance to banks, and supervisory transparency and accountability; and the third pillar prescribes market discipline to complement the minimum capital requirements and the supervisory review processes.

One of the options for computing capital under credit risk is: Internal Rating-Based Approach—banks use their own internal rating systems for credit risk with explicit approval of the supervisory bank for estimating Probability Default (PD) while relying on supervisory estimates for other risk components; and Advanced Internal Rating-based Approach—under which banks provide their own estimates of PD, Loss Given Default (LGD), Exposure at Default (EAD), and Effective Maturity (EM). But internal credit rating system in most of the Indian banks is at an embryonic stage.

Against this backdrop, the authors, Monoshree Mahanta and Munindra Kakati of the first paper, “Effectiveness of Internal Rating Systems in Public Sector Banks of India”, evaluated the effectiveness of internal credit rating models of different banks in India using multiple criteria. The authors have assessed the predictive and discriminatory power of rating models using linear regression, discriminant analysis and logistic regression, both under univariate and multivariate situations. From the analytical results, the authors concluded that non-financial parameters are better default predictors than financial parameters; inclusion of more parameters does not necessarily mean high predictive and discriminatory power; three out of four models where the financial scores are significant, the scores appear to give counter-intuitive result, which may be due to borrowers inflating their financial figures or the financial score is in itself not a good predictor; transition matrices have not produced good transition matrix and in conclusion the authors opine that the models tested have exhibited weaknesses in one or more criteria which needs immediate correction. However, these findings are to be treated as tentative, for it is confined to a limited area. Nevertheless, these findings must be treated as eye-openers by Indian banks and aim at strengthening their respective credit models with appropriate parameters to strengthen their default prediction ability and thereby the health of the organization.

As a right sequel to this, authors, Manmeet Singh and R K Vyas, of the next paper, “The Impact of Portfolio Risk on Performance of Scheduled Commercial Banks in India”, assessed the impact of portfolio risk and other bank-level factors such as capital to risk-weighted assets ratio, non-interest income and net interest margin through a panel data study during the period 1997-2009. Their analysis has shown a significant impact of portfolio risk on performance of banks—banks having more risk in their asset portfolio have enjoyed better returns. They have also concluded that capital adequacy has a positive contribution towards profitability of banks as the cost of funding is reduced.

In the next paper, “A DEA and Malmquist Index Approach to Measuring Productivity and Efficiency of Banks in India”, its author, Vidya Sekhri, compared the performance of public sector banks with private and foreign banks in terms of efficiency and productivity using Data Envelopment Analysis (DEA) and Malmquist index over the period 2004-09. The analysis revealed that the foreign banks scored a high total factor productivity followed by private banks, more due to high technical efficiency. Public sector banks have, however, performed better than foreign banks in pure efficiency change index, highlighting the fact that they are efficient in their operations but need to hone up their technical competency.
Moving on to the next paper, “Investor View of Stock Performance of Indian Banks: Evidence Using the CANSLIM Approach”, the authors, Pratima Jain, Peeyush Bangur and Kapil Sharma, have attempted to determine the correlation, if any, between the financial performance of banks and its stakeholder’s decision to invest in it using the data from March 2007 quarter to March 2008 quarter of 10 banks that are listed in stock exchange. Based on their analysis, they ranked the banks studied for their potential for capital appreciation.

In the next paper, “Intertemporal Behavior of Technical Efficiency: A Study of Indian Commercial Banks”, its author, Ram Pratap Sinha, using window analysis model, compared the intertemporal efficiency behavior of 28 public sector banks for the period 2001-02 to 2005-06 and presented the findings that exhibited a secular declining trend.

In the last paper of the issue, “Modeling the Adoption of Basic E-Banking Services in Urban and Semi-Urban Regions in India”, its authors, Surekha Invalli, Raghurama A and Chandramma M, presented the findings of their study on the adoption of e-banking services offered by banks in urban and semi-urban regions of India, which revealed that demographic variables have influenced adoption of new banking services.

-- GRK Murty
Consulting Editor