Machine LearningFinTech

Real-Time Fraud Detection System

Built an ML-powered fraud detection system using ensemble models and real-time feature engineering, processing transactions in under 50ms with adaptive learning.

Digital Payments Provider
7 months

Key Results

99.2%
Fraud Detection
True positive rate
-60%
False Positives
Reduction in false alerts
-$12M
Fraud Losses
Annual savings
<50ms
Latency
Transaction scoring time

The Challenge

Rising fraud attempts were costing millions annually, and existing rule-based systems couldn't adapt to evolving fraud patterns quickly enough.

Our Solution

Built an ML-powered fraud detection system using ensemble models and real-time feature engineering, processing transactions in under 50ms with adaptive learning.

Measurable Impact

Quantifiable results that demonstrate the value delivered to the client.

99.2%
Fraud Detection
True positive rate
-60%
False Positives
Reduction in false alerts
-$12M
Fraud Losses
Annual savings
<50ms
Latency
Transaction scoring time

Technologies Used

The modern tech stack powering this solution.

XGBoost
Apache Flink
Redis
Kubernetes
MLflow
The ML models caught fraud patterns our rules never would have detected. The ROI was evident within the first quarter.
DK
David Kim
Head of Risk Management

Ready to Achieve Similar Results?

Let's discuss how we can help transform your data operations and drive measurable business impact.