Failure prediction models: performance, disagreements, and internal rating systems. NBB Working Papers. No. 123, 13 December 2007

We address a number of comparative issues relating to the performance of failure prediction models for small, private firms. We use two models provided by vendors, a model developed by the National Bank of Belgium, and the Altman Z-score model to investigate model power, the extent of disagreement between models in the ranking of firms, and the design of internal rating systems. We also examine the potential gains from combining the output of multiple models. We find that the power of all four models in predicting bankruptcies is very good at the one-year horizon, even though not all of the models were developed using bankruptcy data and the models use different statistical methodologies. Disagreements in firm rankings are nevertheless significant across models, and model choice will have an impact on loan pricing and origination decisions. We find that it is possible to realize important gains from combining models with similar power. In addition, we show that it can also be beneficial to combine a weaker model with a stronger one if disagreements across models with respect to failing firms are high enough. Finally, the number of classes in an internal rating system appears to be more important than the distribution of borrowers across classes

Failure prediction models : performance, disagreements, and internal rating systems

We address a number of comparative issues relating to the performance of failure prediction models for small, private firms. We use two models provided by vendors, a model developed by the National Bank of Belgium, and the Altman Z-score model to investigate model power, the extent of disagreement between models in the ranking of firms, and the design of internal rating systems. We also examine the potential gains from combining the output of multiple models. We find that the power of all four models in predicting bankruptcies is very good at the one-year horizon, even though not all of the models were developed using bankruptcy data and the models use different statistical methodologies. Disagreements in firm rankings are nevertheless significant across models, and model choice will have an impact on loan pricing and origination decisions. We find that it is possible to realize important gains from combining models with similar power. In addition, we show that it can also be beneficial to combine a weaker model with a stronger one if disagreements across models with respect to failing firms are high enough. Finally, the number of classes in an internal rating system appears to be more important than the distribution of borrowers across classesBasel II, failure prediction, internal ratings, model power, rating systems, ROC analysis.

Is there a difference in treatment between solicited and unsolicited bank ratings and, if so, why?

This paper analyses the effect of soliciting a rating on the rating outcome of banks. This type of analysis sheds light on an important policy question, namely whether there is a difference in treatment between banks which request a rating and those which do not. Using a sample of Asian banks rated by Fitch Ratings, I find evidence that unsolicited ratings tend to be lower than solicited ones after accounting for differences in financial and non-financial characteristics between banks. This downward bias does not seem to be explained by the self-selection hypothesis, which states that banks with more favourable private information self-select into the solicited group because they can obtain higher ratings by doing so. Rather, unsolicited ratings appear to be lower because they are only based on public information and, as a result, they tend to be more conservative than solicited ones. This is shown by testing the public disclosure hypothesis, which states that the difference in treatment between solicited and unsolicited ratings disappears when banks with an unsolicited rating release enough public information to compensate for the absence of private information. Overall, the findings of this study have important policy implications for the reform of the credit rating industry and for the Third Pillar of the New Basel Accord.unsolicited ratings, treatment effect, switching regression, public disclosure

The impact of the 1988 Basel Accord on banks' capital ratios and credit risk-taking: an international study

The purpose of this paper is to see whether and how G-10 banks have complied with the 1988 Basel Accord. The interest of this study lies in the fact that the standardized approach to credit risk in the New Basel Accord is conceptually similar to the 1988 agreement. However, very little is known about the reaction of non-US banks to the imposition of minimum capital requirements that make use of risk-weight categories. Building on previous studies, this paper uses a simultaneous equations model to analyze adjustments in capital and credit risk at banks from G- 10 countries over the 1988-95 period. The results show that regulatory pressure was successful in raising the capital to assets ratios of undercapitalized banks in Canada, Japan, the UK and the US but not in France and Italy. In addition, there is no evidence that undercapitalized G-10 banks increased or decreased their credit risk over the period studied. Interestingly, these findings are robust to the inclusion of a variable measuring the role of market discipline in influencing bank capital and risk choices. All in all, the results suggest that the 1988 Basel standards were effective in that, subsequent to their adoption, undercapitalized G-10 banks generally increased their capital but not their credit risk.1988 Basel Accord, capital requirements, credit risk

Credit ratings and the standardised approach to credit risk in Basel II

This paper simulates the minimum capital requirements for the wholesale exposures of a medium-sized bank in each EMU country depending on the credit rating agencies chosen by the bank to risk-weight its exposures in the standardised approach to credit risk in Basel II. Three main results emerge from the analysis. First, although the use of different combinations of credit rating agencies leads to significant differences in minimum capital requirements, these differences never exceed 10% of EMU banks’ regulatory capital for wholesale exposures on average. Second, the standardised approach provides a small regulatory capital incentive for banks to use several credit rating agencies to risk-weight their exposures. Third, the minimum capital requirements for the wholesale exposures of EMU banks will be higher in Basel II than in Basel I. I also show that the incentive for banks to engage in regulatory arbitrage in the standardised approach to credit risk is limited. JEL Classification: G21, G28capital requirements, credit rating agencies, New Basel Capital Accord

Is there a difference between solicited and unsolicited bank ratings and if so, why ?

This paper analyses the effect of soliciting a rating on the rating outcome of banks. Using a sample of Asian banks rated by Fitch Ratings ("Fitch"), I find evidence that unsolicited ratings tend to be lower than solicited ones, after accounting for differences in observed bank characteristics. This downward bias does not seem to be explained by the fact that betterquality banks selfselect into the solicited group. Rather, unsolicited ratings appear to be lower because they are based on public information. As a result, they tend to be more conservative than solicited ratings, which incorporate both public and nonpublic information.Credit rating agencies, Unsolicited ratings, Selfselection, Public disclosure, Accounting transparency

Credit ratings and the standardised approach to credit risk in Basel II

This paper focuses on the standardised approach to credit risk in Basel II. The minimum capital requirements for the corporate, interbank and sovereign loan portfolios of a representative bank in each EMU country are evaluated by means of Monte-Carlo simulations depending on the credit rating agencies chosen by the bank to risk-weight its exposures. Three main results emerge from the analysis. First, although the use of different combinations of credit rating agencies leads to significant differences in minimum capital requirements, these differences never exceed 10% of banks’ regulatory capital for loans to corporates, banks and sovereigns on average in the EMU. Second, the standardised approach provides a small regulatory capital incentive for banks to use several credit rating agencies to risk-weight their exposures. Third, the minimum capital requirements for the corporate, interbank and sovereign loan portfolios of EMU banks will be higher in Basel II than in Basel I. I also show that the incentive for banks to engage in regulatory arbitrage in the standardised approach to credit risk is limited.New Basel Accord, capital requirements, credit rating agencies