Virtual bank failures: an investigation

Purpose - The purpose of this paper is to identify the causes behind the failures of virtual banks. This work underscores the importance of the differing financial metrics in the virtual and brick and mortar banking channels, when analyzing bank failures. Design/methodology/approach - “Probit” analysis on the failed virtual banks and the failed brick and mortar banks revealed that the interest incomes in both banks are significantly different. The non-interest income and non-interest expense (NIE) of the surviving banks and the failed banks are explored to examine the causes for failure. Findings - Similar to previous research it was found that the brick and mortar banks failed due to bad asset quality, but the failure of virtual banks is mainly due to high NIEs. For virtual banks to succeed, the institutions must focus on controlling the burden. Research limitations/implications - A larger sample size would have been preferable and non-availability of data limited the scope of the study. Continuing studies could explore the performance of Internet channels of existing brick and mortar banks. Practical implications - This study accentuates the importance of the differing business models underlying the two banking channels (virtual banks and brick and mortar banks). These channel specific differences underscore the significance of the financial metrics in operational evaluation. Originality/value - This is probably the first study to examine the causes of failures of virtual banks and contrast them with brick and mortar banks.

[1]  F Jones,et al.  CURRENT TECHNIQUES IN BANKRUPTCY PREDICTION , 1987 .

[2]  Krishnan Dandapani,et al.  Success and failure in Web-based financial services , 2004, CACM.

[3]  Leon Korobow,et al.  Performance measurement of early warning models: Comments on west and other weakness/failure prediction models , 1985 .

[4]  Edward I. Altman,et al.  Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience) , 1994 .

[5]  Marc Blum.  FAILING COMPANY DISCRIMINANT-ANALYSIS , 1974 .

[6]  R. C. West.  A factor-analytic approach to bank condition , 1985 .

[7]  Daniel Martin,et al.  Early warning of bank failure: A logit regression approach , 1977 .

[8]  James B. Thomson,et al.  Predicting bank failures in the 1980s , 1991 .

[9]  C. Zavgren.  ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS , 1985 .

[10]  J. Sinkey.  A MULTIVARIATE STATISTICAL ANALYSIS OF THE CHARACTERISTICS OF PROBLEM BANKS , 1975 .

[11]  E. Altman,et al.  ZETATM analysis A new model to identify bankruptcy risk of corporations , 1977 .

[12]  Robert DeYoung,et al.  The financial performance of pure play Internet banks , 2001 .

[13]  P. Meyer,et al.  PREDICTION OF BANK FAILURES , 1970 .

[14]  James W. Kolari,et al.  Predicting large US commercial bank failures , 2002 .

[15]  Edward I. Altman,et al.  FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY , 1968 .

[16]  J. D. Vinso,et al.  Estimating the probability of failure for commercial banks and the banking system , 1977 .

[17]  Pouran Espahbodi,et al.  Identification of problem banks and binary choice models , 1991 .

[18]  David C. Wheelock,et al.  Why do Banks Disappear? The Determinants of U.S. Bank Failures and Acquisitions , 2000, Review of Economics and Statistics.

[19]  W. Beaver.  Financial Ratios As Predictors Of Failure , 1966 .