Genetic algorithms for credit card fraud detection
نویسندگان
چکیده
Due to the rise and rapid growth of E-Commerce, use of credit cards for online purchases has dramatically increased and it caused an explosion in the credit card fraud. Fraud is one of the major ethical issues in the credit card industry. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In real life, fraudulent transactions are scattered with genuine transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. Implementation of efficient fraud detection systems has thus become imperative for all credit card issuing banks to minimize their losses. Many modern techniques based on Artificial Intelligence, Data mining, Fuzzy logic, Machine learning, Sequence Alignment, Genetic Programming etc., has evolved in detecting various credit card fraudulent transactions. A genetic algorithm is an evolutionary search and optimisation technique that Mimics natural evolution to find the best solution to a problem. Here the characteristics of credit card transactions undergo evolution to allow a modelled credit card fraud detection system to be tested. KeyWords:Electronic commerce, fraud, credit card, genetic algorithms, detection
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