Abstract
Artificial neural networks and statistical techniques like decision trees, discriminant analysis, logistic regression and survival analysis play a crucial role in Business Intelligence. These predictive analytical tools exploit patterns found in historical data to make predictions about future events. In this paper we have shown some recent developments of a few of these techniques in financial and business intelligence applications like fraud detection, bankruptcy prediction and credit rating scoring.
| Original language | English |
|---|---|
| Pages (from-to) | 30-37 |
| Number of pages | 8 |
| Journal | International Conference on Business Intelligence & Data Warehousing |
| DOIs | |
| Publication status | Published - 1 Jul 2010 |
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