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Authors
Affiliations
1 Department of Banking Technology, Pondicherry University, Puducherry, IN
2 Department of Computer Science, St. Joseph's College, Cuddalore, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 3, No 9 (2011), Pagination: 601-607
Abstract
In the globalized stiff business environment for the survival of any organization an effective technology is required to take right decisions at right time by right people. One such a prime technology is business intelligence. Bankruptcy prediction is one of the business intelligence techniques. Among so many challenges bankruptcy is very important for a financial institution or any business. Prediction of bankruptcy is crucial for the smooth running of business. Many bankruptcy models are available. Each bankruptcy model is described by quantity equation, which is based on the non linear relationship between various financial ratios used in that model. The Genetic process is applied to find the non linear relationship between financial ratios which are having more impact on bankruptcy model. In this research three bankruptcy models Altman, Edmister and Deakin model were chosen. Genetic algorithm is applied in these three bankruptcy models to find most impacted ratios. Altman model is has more impact on its financial ratios compare to other bankruptcy models. The impacted threshold value is 98% matches with the original threshold value of Altman.
Keywords
Genetic Algorithm, Bankruptcy Models, Deakin Model, Altman Model, Edmister Model, Financial Ratios, Business Intelligence.
