AI-Powered Fraud Detection for FinTech Transactions
Client Profile
A rapidly growing FinTech company offering digital wallets, online payment processing and lending services, managing millions of daily transactions across global markets.
Sophisticated fraud tactics evaded traditional rule-based systems.
Solution
Deployed a machine learning model trained on historical fraud data to identify anomalies in transaction behavior.
Utilized deep learning techniques to detect hidden patterns in high-dimensional data, such as geolocation, device fingerprints and transaction histories.
Leveraged AI agents to analyze user behavior, flagging unusual patterns like multiple logins, inconsistent spending or location mismatches.
Implemented real-time scoring for transactions, instantly blocking high-risk payments or triggering additional verifications.
Seamlessly embedded into the payment processing pipeline, ensuring uninterrupted user experience.
Business Outcome
40% Fraud Reduction
Identified and blocked fraudulent transactions in real time.
10x Scalability
Handled millions of daily transactions without performance degradation.
Improved Accuracy
Reduced false positives by 25% improving user trust.
Regulatory Compliance
Strengthened adherence to AML and PSD2 requirements.
Seamless UX
Maintained fast transaction speeds while ensuring security.
Technology Used
TensorFlowPyTorchDeep Neural NetworksIsolation ForestApache SparkStripePayPalPower BI
