A brief review of recent research trends on applications of computational and statistical techniques in financial & business intelligence

Kuldeep Kumar, Sukanto Bhattacharya

Research output: Contribution to journalArticleResearchpeer-review

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 languageEnglish
Pages (from-to)30-37
Number of pages8
JournalInternational Conference on Business Intelligence & Data Warehousing
DOIs
Publication statusPublished - 1 Jul 2010

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Business Intelligence
Credit Rating
Fraud Detection
Bankruptcy
Survival Analysis
Prediction
Historical Data
Logistic Regression
Discriminant Analysis
Scoring
Regression Analysis
Decision tree
Artificial Neural Network
Trends
Review

Cite this

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