FINGUARD_AI

Financial fraud in UPI and card payments is becoming increasingly difficult to detect because fraudulent transactions can appear similar to genuine transactions, especially when there is limited historical data for a new user. Traditional rule-based systems may also struggle with rapidly changing fraud patterns.

FinGuard AI addresses this problem by analyzing transaction amount, time, location, device signals, and global fraud patterns in real time. It combines machine learning, anomaly detection, and rule-based analysis to generate a 0–100 fraud-risk score and classify transactions as Low, Medium, or High Risk. This enables faster and more informed Allow, Flag, or Block decisions before the payment clears.