Detection of Financial distress and Financial Fraud



In view of the failure of many high profile firms, bankruptcy prediction has become a topic of high interest. In this paper we have briefly reviewed the various techniques for the financial distress and financial fraud prediction. These techniques consist of statistical techniques like logitic regression, multiple discriminant analysis, multivariate CUSUM methods etc. and Artificial Neural Network techniques. Kumar and Ganesalingam (1994) used some of these techniques in distinguishing between trustee and non-trustee stocks in Singapore. We have also used these techniques to Australian and U.S. stock market data and results are found to be very encouraging. We have also used Benford Law to detect financial fraud.




Dr Kuldeep Kumar did his PhD from University of Kent at Canterbury, U.K. He has taught in The Indian Institute of Management, National University of Singapore and currently he is Associate Professor of Statistics at Bond University, Australia. Winner of Young Statistician award of ISI, Commonwealth Fellowship, CEC Post Doc Fellowship and Bond -Oxford Fellowship, Dr Kumar is also winner of Teaching Excellence award. He has published more than 80 papers in various areas of statistics. His current research interest is in Financial distress and bankruptcy prediction, finnacial fraud prediction, multivariate techniques, ANN and soft computing methods.



6/23(Thurs) 3.30pm


NCCU, Social Science College, Room271034


  ppt    excel