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Real-Time AI Fraud Detection Layer for Digital Payment Platform

Real-Time AI Fraud Detection Layer for Digital Payment Platform

A digital payments company headquartered in Singapore experienced recurring transaction anomalies during high-volume payment events. The platform processed millions of transactions per day but lacked intelligent monitoring and real-time fraud interception. To mitigate losses and improve trust, the organization collaborated with our AI engineering team to build a real-time AI fraud detection system integrated directly with their transaction APIs.

Image representing case study

31%

Reduction in fraud-related losses

< 150

ms response time per transaction

92%

Accuracy in fraud detection model

About  

Problem Statement

  • Manual fraud checks happened post-transaction, causing delayed action.
  • Lack of real-time anomaly detection led to recurring chargeback cases.
  • Suspicious activity patterns were missed due to static rule-based filters.
  • No automated alerting mechanism existed for high-risk transactions.
  • Growing user base required a scalable and low-latency fraud monitoring solution.

Industry: FinTech & Payments

Services: AI Integration, AI Security, Fraud Detection

Region: Southeast Asia (Singapore)

Our Tech Stack

Tech stack we used

Solution Approach

  • Analyzed 12 months of historical transaction data to identify behavioral and device-level indicators.
  • Developed ML pipelines in Python using XGBoost for classifying transactions as normal or suspicious.
  • Deployed streaming ingestion with Apache Kafka, feeding real-time events into the inference layer.
  • Implemented Redis Streams for short-term caching of user behavior to detect velocity-based fraud (e.g., multiple payments in seconds).
  • Integrated AWS Lambda functions to process model predictions within 150 ms.
  • Created an Elasticsearch dashboard for risk analysts to search anomalies instantly.
  • Configured AWS SNS + CloudWatch alerts for proactive notification to the fraud-prevention team.
  • Used Terraform for infrastructure consistency and automated encryption of sensitive data fields.

Benefits

  • Reduced financial losses from fraudulent transactions by 31% in the first quarter.
  • Real-time scoring prevented high-value fraud before settlement.
  • Automated alerts improved compliance response speed.
  • Scalable setup handled >10 million daily events without latency overhead.
  • Improved customer confidence in digital payment security.

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