Advancing financial security : A hybrid fusion of neural network and rule-based system for credit card fraud detection

Credit card fraud presents a serious threat to financial institutions, causing substantial financial and reputational damage. To address this, the proposed method combines a neural network with a rule-based system to enhance fraud detection. This hybrid model effectively examines credit card transactions by capturing complex patterns and integrating expert insights, improving accuracy and minimizing false positives. By leveraging human-understandable rules and domain knowledge, the approach enhances transparency in decision-making processes. This innovative solution represents a significant advancement in fraud detection, helping financial institutions mitigate losses while ensuring greater trust and security in financial transactions.