Litcius/Paper detail

Credit Card Fraud Detection Techniques – A Survey

Nikita Shirodkar, Pratikesh Mandrekar, Rohit Shet Mandrekar, Rahul Sakhalkar, K. M. Chaman Kumar, Shailendra Aswale

20202020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE)49 citationsDOI

Abstract

The rapid growth of e-commerce and internet lead to a wide increase in the credit card use. Due to increase in the usage of credit cards there is vast increase in the credit card frauds in the recent years. Artificial neural network considers effectiveness of neural networks in the detecting credit card frauds. This system trains the neural network based on the data of the customer from the past. Training artificial neural network is difficult because every time the activity is different in each of the transaction. So, we can conFigure an artificial neural network with a genetic algorithm for this task. We create a combination of simulated annealing and genetic algorithm to get better results. Genetic algorithm uses a biological way to find the fittest solution from various solutions. Simulated annealing has effective algorithm which on combining with Genetic algorithm proves efficient in the detecting credit card frauds. Simulated annealing after processing credit card details of owner passes through ANN network for detection.

Topics & Concepts

Credit cardComputer scienceArtificial neural networkCredit card fraudGenetic algorithmSimulated annealingArtificial intelligenceDatabase transactionMachine learningThe InternetData miningDatabaseOperating systemWorld Wide WebPaymentImbalanced Data Classification TechniquesFinancial Distress and Bankruptcy PredictionArtificial Intelligence in Healthcare