Abstract:

Credit card fraud has become a significant threat to financial institutions and customers, causing substantial monetary losses annually. FraudShield proposes an efficient credit card scam detection system using Logistic Regression, leveraging historical transaction data to identify fraudulent patterns. The model uses features such as transaction amount, location, and time to predict the likelihood of fraud, achieving high accuracy and low false positive rates. Experimental results demonstrate that FraudShield significantly reduces undetected fraudulent transactions, thereby improving transaction security and trust in digital payment systems.

Description:

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