Vol 4 (2007) - Issue 2

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Default Risk of Corporate Entities – A Critical Assessment

The aim of this article is to present the ‘state of the art’ techniques that have been developed in the last 30 years in financial economics regarding corporate failure. We critically analyse the more traditional accounting-based credit-scoring systems as well as more recent techniques such us option pricing models, mortality rate models/aging approach, neural network analysis and the term structure approach of deriving credit risk. We believe that in-depth understanding of credit risk models is a critical component of a comprehensive approach to risk management for all of those who need to make informed decisions i.e. industry professionals, regulatory authorities, shareholders and investors in their attempt to avoid investing in companies where losses are probable.

1. Introduction

Corporate failure is a term used to describe the collapse or failure of a company that is deemed to have defaulted – that is, in the legal sense, if it has entered liquidation, receivership or administration. The literature on credit risk and corporate failure has developed rapidly over the past 30 years. Yet, it is fair to say that after the economic recession in the USA and the major industrialised economies of the late 1980s and early 1990s, interest on credit risk analysis has slightly declined. This is because of the consecutively uninterrupted
economic growth and productivity acceleration that the American economy faced for about ten years. Given that the American economy, along with the German, are considered to be the ‘locomotive’ for the rest of the world economies, the abovementioned economic growth had positive side effects to the rest of the developed economies in Europe and elsewhere. However, the Asian financial crisis in 1997, the Russian debt crisis in the summer of 1998, the collapse of NASDAQ1 stock prices in the USA between 2001 and 2003, the expansion of the ‘off-balance sheet’ derivative products with inherent default risk,2 the increase in bankruptcies of companies as well as the more recent corporate scandals (Enron, Parmalat, WorldCom) have reversed the optimistic sentiments in the financial markets and the positive economic momentum that had been built up around the world in the mid-1990s. These incidents came to remind everyone that credit risk cannot disappear; because of the contagion effect it is only transferred from one financial market to another. The events in the late 1990s stimulated once again market participants’ interest in corporate failure and made them all understand that credit risk is always worth bearing in mind, irrespective of the position of the economies in the business cycle phase and the general economic circumstances. Academics, practitioners, regulatory authorities and banks had to deal with the repercussions of the Asian financial crisis, the Russian debt crisis and the general increase in bankruptcies of companies in the late 1990s. They responded to these challenges in different ways.
More specifically, academics have responded to the new challenges not only by developing more sophisticated credit-scoring systems but also by developing new models which price credit risk of both ‘on balance sheet’ and of ‘off balance sheet’ instruments.
A number of financial institutions and consulting firms have developed proprietary risk analysis systems to measure the risks involved in holding portfolios of credit-sensitive instruments. In this respect, they have moved away from the standard subjective expert systems3 towards more objectively based systems (quantitative internal rating systems4), which can give better answers to modern complex problems that arise in the new risky economic environment. These include the Credit Monitor from KMV,5 which estimates the ‘expected default frequency’ or EDF,6 CreditMetrics from JP Morgan,7 which provides a framework for estimating the forward distribution of the values of loan portfolios and CreditRisk+ framework from Credit Swiss Financial Products, which uses an actuarial model to derive the loss distribution of a bond/loan portfolio and the required capital reserves to meet those losses. Lastly, Credit Portfolio View from McKinsey is based on the casual observation that default probabilities as well as migration probabilities are linked to the state of the economy. Recent empirical work has stressed the need to evaluate the accuracy of the forecasts generated by these proprietary risk analysis systems.