International Journal of Recent Trends in Engineering & Research

online ISSN

Implementation Of Neural Network For Cashless Transactions In Credit Card Transactions

Publication Date : 29/01/2018


DOI : 10.23883/IJRTER.CONF.20171225.026.HGEDM


Author(s) :

M SRIRAM REDDY , S INDRAJA , L NIKHIL.


Conference Name :
RECENT ADVANCES IN ELECTRONICS AND COMMUNICATION ENGINEERING-2017



Abstract :

Cashless transactions such as online transactions, credit card transactions, and mobile wallet are becoming more popular in financial transactions nowadays. With increased number of such cashless transaction, number of fraudulent transactions are also increasing. Fraud can be distinguished by analyzing spending behavior of customers (users) from previous transaction data. If any deviation is noticed in spending behavior from available patterns, it is possibly of fraudulent transaction. To detect fraud behavior, bank and credit card companies are using various methods of data mining such as decision tree, rule based mining, neural network, fuzzy clustering approach, hidden markov model or hybrid approach of these methods. Any of these methods is applied to find out normal usage pattern of customers (users) based on their past activities. The objective of this paper is to provide comparative study of different techniques to detect fraud


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