“Bankruptcy” is a legally declared inability or impairment of ability of an individual or organizations to pay their creditors. Creditors may file a bankruptcy petition against a debtor in an effort to recoup a portion of what they are owed. Bankruptcy prediction is very important because it serves two main purposes under the bankruptcy law. First, bankruptcy law gives creditors some payment on their debts if a debtor (the one who owes the debt) can afford to pay them. Second, bankruptcy law gives debtors a fresh start, by cancelling many of their debts, through an order of the court called a discharge. If an organization is not willing to get into such an adverse circumstances, then one can have sound bankruptcy prediction techniques in place.
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Bankruptcy prediction has become increasingly important over the last few decades. The number of corporate bankruptcies has been growing ever since the economical depression of 1930. Bankruptcy prediction is a classification problem, with two classes: bankrupt or non-bankrupt (healthy). Over the past few decades financial crisis was observed in some emerging sectors like banking. Bankruptcy prediction of banks has been an extensively researched area since late 1960s. Bankruptcy can affect all the areas where the sufferers are creditors, auditors, stock holders and senior management. So, they are all interested in predicting the bankruptcy. Researchers used CAMELS rating for prediction in the early days. But, because of its in effectiveness they moved towards other theoretical models.
Recently researchers reported the effective use of soft computing techniques toward bankruptcy prediction in banks. Refer to the following resources for further studies.
Books: Advances in Credit Risk Modelling and Corporate Bankruptcy Prediction by Stewart Jones, David A. Hensher
Web resources: Bankruptcy Prediction for Credit Risk Using Neural Networks: A Survey and New Results
Hybrid and ensemble-based soft computing techniques in bankruptcy
Power Point Presentation (PPT): Bankruptcy, Reorganization, and Liquidation
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