Abstract

This paper empirically determines the significant determinants, among credit risk variables, of US bank failure. Applying the Probit Model the paper finds that among the five credit risk variables, the credit loss provision to net charge off, loan loss allowance to non-current loans, and non-current loans to loans are significant for predicting bank failures. These factors predict 76.8 percent to 77.25 of total observation correctly. The model predicts 97 out of 121 failures i.e. 80.17 percent correctly. Net charge off to loans and loan loss to non-current loans, though most reliable measures, are not significant predictors for the US bank failures during 2009.

Highlights

  • There were 25 bank failures in 2008 (Samad & Lowell, 2012). 140 banks went burst in 2009 and 157 banks were wipped out in 2010 (Time, January 2012). Such a large scale bank failure hasnot happened in the financial history of the United States since the Great Depression

  • The objective of this paper is to identify the credit risk ratios that are significant in predicting the US bank failures during 2009

  • Since dependent variable—failure=1 and success=0—is binary, the Probit Model is used for identifying the credit risk ratios that are significant and have predictive power

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Summary

Introduction

There were 25 bank failures in 2008 (Samad & Lowell, 2012). 140 banks went burst in 2009 and 157 banks were wipped out in 2010 (Time, January 2012). 140 banks went burst in 2009 and 157 banks were wipped out in 2010 (Time, January 2012). Such a large scale bank failure hasnot happened in the financial history of the United States since the Great Depression. It has resulted in global financial crisis in Europe and around world. One of them is the insolvency theory. According to the insolvency theory, a bank fails when the value of bank assets fall and becomes less than its liabilities. In most cases the value of assets fall due to credit risk resulting from nonperformance of loans.

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