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Research Paper | Computer Science & Engineering | India | Volume 5 Issue 11, November 2016

Customer Retention and Fraud Detection for Credit Card

Ajinkya Pathak | Rohan Aney | Soham Baheti

Abstract: In todays digital world banking sector has reached every business, every small business and households in multiple forms from loans to credit cards to Fixed Deposits. It is very crucial for a bank to analyses its customer purchases and to interpret the trends to enhance the customer base and retain existing customers. There are various strategies for customer retention, the modern day banks use latest IT tools to capture and interpret the data for customer attributes. The present project deals with developing a decision tree program to gain a rough estimate on whether a customer with particular attribute would be profitable for the bank in the long term. For a manager Visualization tools are also provided to help facilitate a much better understanding of its customers. The project also addresses a very vital aspect of fraud detection and offers a suitable program for the same. Fraud detection is not only essential for the bank but lowest level of fraud will enhance customers confidence in the transactions with the bank. The program is based on genetic algorithms for Fraud detection. This program can be incorporated dynamically (i. e. Real time) on any system thus making it more agile and effective.

Keywords: Banking tools, Data Classification, Genetic algorithms, Visualization tools

Edition: Volume 5 Issue 11, November 2016,

Pages: 1284 - 1286

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