An Overview of Credit Card Fraud Detection Techniques
DOI:
https://doi.org/10.61506/01.00519Keywords:
Fraud detection, Data Mining, Neural Networks, Machine Learning, Clustering approaches, Electronic commerce, Credit card fraud, spending patterns, Credit card, fraud detection techniques, and online banking.Abstract
Credit card fraud is the first thing that comes to mind when the word fraud is uttered. The volume of credit card transactions has increased significantly in recent years, along with a corresponding spike in credit card fraud. Monitoring users' and customers' spending patterns helps detect fraud and stop bad behavior. There is a rising rate of credit card fraud as they become the most widely used payment mechanism for both online and offline transactions. The goal of fraud detection is to identify fraudulent conduct as soon as it is possible and to document it. The utilization of charge cards is normal in present day culture. The multimillion-dollar industry of extortion is growing each. Extortion influences the world economy fundamentally. Different contemporary strategies, for example, information mining, AI, fluffy rationale, hereditary programming, and man-made consciousness, have been produced for identifying charge card extortion. This study tells the best way to successfully consolidate information mining methods to keep a low or high misleading problem rate while accomplishing high extortion inclusion.
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