Prediction of Credit default risk for companies listed at Nairobi Securities Exchange

Abstract

Corporate defaults are one of the main sources of loss for a bank and therefore there is a need for credit managers to make sound credit lending decision. This risk is critical since debt obligations due to a major deterioration of the credit standing of the borrower and, finally, formal bankruptcy and liquidation. Credit manager analyzes a borrower and provides a credit rating used in the lending decision. Creditworthiness of borrowers is determined by character, capacity, capital, collateral and conditions. In credit lending decision, concern is mainly on the serviceability of the loan to be advanced. Failure prediction model come in handy in such a case as the credit manager use the model in determining failure prediction score in making sound credit decision. Similarly a company may be having satisfactory DSCR (Ratio of Company free cash flows to Total debt repayments), but the Z score is below the “cut off” (Padhi, 2005). The objective of the study was prediction of credit default risk for companies listed in NSE. The study adopted a descriptive cross-sectional research design. The main goal of descriptive research is to describe the data and characteristics about what is being studied. Population of study was all companies listed in Nairobi Securities Exchange from 2003 to 2010. Failed companies are considered those that have either been suspended or delisted from the NSE excluded companies that delisted voluntarily. They are only 10 firms during this period. Non-failed companies are all entities listed in the NSE since the year 2003-2010. The data composed of full set of financial statements, which was collected from NSE and company websites. Failed firms data was collected for one year prior to bankruptcy. Previous research done on bankruptcy has demonstrated that financial information one year before bankruptcy predicts probability of the company going into bankruptcy more accurately than two to three years before. Data analysis was based on Altman Z score Model and DSCR. The study revealed that Altman Z score model was applicable in the prediction of credit default risk for companies listed in Nairobi Security Exchange. The DCSR for all failed companies was less than 1 demonstrating that calculation of DSCR ratio is critical in making solid credit decision.