Applicability of financial crisis predictive model to bank failures in Kenya

Abstract

This study set out to achieve the following two objectives: 1. Test the applicability of the theories of financial crisis predictive model to bank failures in Kenya. 2. Identify the key macroeconomic variables In predicting bank failure in Kenya. The Interest rates, monetary, business cycle and stock market volatility theories were operationalized into four macro-economic variables namely interest rates, reserve money, Gross Domestic Product and the Nairobi Stock Exchange index. A multivariate bank failure predictive model was formulated to test the significance of each of the macroeconomic (Independent) variables in predicting bank failure. The annual average changes in the macro-economic variables were regressed against the percentage of failed banks to total banks per year as the dependent variable. The study covered the period 1984 to 1998 when a total of 37 banks failed in Kenya. Secondary data was obtained from various published sources and analyzed by use of multiple regression modelling. The Microsoft (MS) Excel statistical package was used. The results of the study indicate that the interest rates and stock market volatility theories are applicable in Kenya and that interest rates and the Nairobi Stock Exchange (NSE) 'index are key macroeconomic variables in predicting bank failures in Kenya. A predictive model using these two variables is established in the study. An increase in interest rates leads to increased interest burden on loans, which may lead to borrowers defaulting. This increases non-performing loans (loans in arrears and not being regularly serviced) in a bank's loan portfolio, which may ultimately lead to bank failure. The NSE index mirrors the country's economic performance whose deterioration leads to a decline in the index. Deteriorating economic performance increases the probability of failure of banks.