Beyond the CAMELS Rating – A Model For Predicting Bank Failures in Nigeria

In the year 1968, a financial economist called Edward Altman, then an Assistant Professor of Finance at New York University published what is popularly known in the global finance community as the Z-Score formula for predicting corporate bankruptcy. With the published formula, it was possible to use historical accounting data to predict the failure of publicly-quoted American manufacturing firms two (2) years prior to the declaration of bankruptcy. In effect, the range of predictive accuracy of the model was found to be between seventy two percent (72%) to eighty percent (80%).

For four (4) decades following the publication of the original Z-Score Model and with a great deal of adjustments/modifications, the predictive value of the z-score has remained outstanding to date. Although, the original z-score model was prepared for publicly-quoted U.S. manufacturing firms, adjustments were later made in the model to cater for firms in non-manufacturing sector, privately-owned companies and those firms that were strictly in the service business.

Professor Altman developed the z-score model as a financial analysis tool for use in the academia. However, its practical relevance to a wide range of firms and industries has stood the test of time. The model was developed using the sample of sixty six (66) U.S. manufacturing firms, half (33) of which had gone bankrupt at the time. From the financial statements of all these firms, some key accounting ratios were calculated and investigated over time. The pattern and effect of these ratios were brought together in the z-score model which is subsequently used to determine whether a firm was heading for bankruptcy or not.

This is the year 2009. Like most countries, Nigeria is presently in the throes of a banking crisis. Although the Central Bank of Nigeria insists that No Nigerian Bank Will be Allowed to Fail. I take it to mean that No Nigerian Bank Will be Allowed to Go Under (or to be declared bankrupt). Judging from the critical importance of banking to our National economy, that is the logical and humane position. But it does not imply that things have not or will not go wrong in Nigerian banking. In fact, in my view the famous five technically failed. Because there is the opportunity of a lifeline (whether it is solicited or compelled upon the institution), they will certainly never be allowed to go under.

Having superintended bank failures, I believe it is time for the CBN to be more proactive in regulating the industry. Some analysts have argued that it is the failure of regulation that has led to this situation. How do you explain away the hundreds of billions of Naira of lifeline support through the Expanded Discount Window? As if that was insufficient, another 420 billion Naira is being required just to stabilize chronic mismanagement.
Imagine what could happen if other critical sectors of the Nigerian economy such as education and health have access to this kind of lifeline support?

The purpose of the above analogy is just to draw some attention to some of the financial cost of the ongoing banking crisis. A stitch in time they say saves nine. Now, just imagine the benefits that could have accrued to the entire Nigerian economy had the CBN correctly predicted the bank failures two (2) years prior to now. Perhaps there would have been no need for the Expanded Discount Window and no need for the 420 billion Naira bailout fund! Those funds could have been channeled to other critical needs of the economy.

The traditional model of assessing the performance of financial institutions has been the CAMELS Rating. CAMELS is an acronym for Capital Adequacy, Asset Quality, Management Quality, Earnings Potential, Liquidity and Sensitivity to Market Risk. While the CAMELS Rating is an excellent measure, I believe it is time for the regulator to develop once and for all a reliable model for predicting bank failures in the country. This will enable the regulator closely and easily monitor the performance of the banks and take remedial actions long before things get out of hand.

Because Nigeria has had ample cases of bank failures in the past, it will not be too difficult to come up with a model similar to Professor Altman’s z-score. But adjustments have to be made for the unique nature of banking services, the Nigerian economy, the industry peculiarities and the way and manner in which the financial statements of the banks are presented. Banking thrives on sound liquidity management. This assertion itself can serve as the foundation for any form of analysis or modeling framework that can be developed for the industry.

It is important to note that I am not proposing a wholesale adoption of the z-score model. A separate model can be developed for our own unique environment using basic principles that are similar to those used for the z-score model. I am aware that sometimes it is argued that bank financial statements are difficult to understand and that banks use a lot of off-balance sheet items. Regulation remains the best response to the above problems. There is need to simplify, streamline and standardize financial statement reporting. There is also need for sufficient disclosure of off-balance sheet items. That is why full disclosure and full provision for bad debts is a step in the right direction. Ultimately, the boys will be separated from the men.

Last but not the least, a situation of Garbage In Garbage Out must be avoided. This is key as the financial statements (particularly the balance sheet and income statement) that will serve as source documents for the calculation of the financial ratios on which the analytical model will be based MUST show a true and fair view. The accuracy and integrity of the financial statements MUST not be in doubt. This again poses further challenges for regulation. However, I conclude that this moment and time is perhaps the best for addressing some of the major issues raised above.