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Use of Data Mining in Banking



In today‟s globalization and cut throat competition the banks are struggling to gain a competitive edge over each other. Apart from execution of business processes, the creation of knowledge base and its utilization for the benefit of the bank is becoming a strategy tool to compete. In recent years the ability to generate, capture and store data has increased enormously. The information contained in this data can be very important. The wide availability of huge amounts of data and the need for transforming such data into knowledge encourage IT industry to use data mining. The banking industry around the world has undergone a tremendous change in the way business is conducted. The banking industry has started realizing the need of the techniques like data mining which can help them to compete in the market. Leading banks are using Data Mining (DM) tools for customer segmentation and profitability, credit scoring and approval, predicting payment default, marketing, detecting fraudulent transactions, etc. This paper provides an overview of the concept of DM and highlights the applications of data mining to enhance the performance of some of the core business processes in banking industry

Topics: Data Mining, Fraud Detection, MIS, TBC
Year: 2014
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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