Mastercard is one of the world's largest payment networks, processing billions of transactions every year across global merchants, banks, and financial institutions. With fraud becoming increasingly sophisticated, Mastercard required an advanced, high-performance system capable of detecting anomalies in real time, reducing false positives, and strengthening global payment security. BAAS partnered with Mastercard to design, engineer, and support a cutting-edge fraud detection and alerting system, built with enterprise-grade reliability, speed, and intelligence.
Project Overview
Mastercard needed a solution that could analyze massive transaction volumes in real time, detect fraudulent patterns with high accuracy, trigger instant alerts for risk teams, integrate seamlessly with global banking partners, allow continuous testing, tuning, and improvement, and operate with near-zero downtime. BAAS delivered a modern fraud detection platform combining data analytics, machine learning, microservices, real-time alerting, and automated test frameworks-all built to meet Mastercard's strict security and performance requirements.
What We Delivered
1. Real-Time Fraud Detection Engine - Developed algorithms and rule-based logic to detect suspicious transactions instantly. Built pipelines capable of processing high-throughput payment data with ultra-low latency. Integrated machine learning features to improve fraud detection accuracy over time.
2. Intelligent Alerting & Notification System - Implemented real-time alert workflows to notify risk teams of suspicious activity. Designed configurable alerts with priority levels, case creation, and escalation paths. Integrated alerting with email, dashboards, and internal monitoring tools.
3. Transaction Analysis & Behavioral Scoring - Analyzed patterns across cardholder behavior, merchant types, geolocation, device data, and velocity checks. Created scoring models to classify risk levels for each transaction. Enabled more precise fraud identification while reducing false positives.
4. Microservices Architecture & Enterprise Integration - Built modular, scalable microservices to handle ingestion, scoring, alerting, auditing, and reporting. Designed secure APIs for Mastercard internal systems and external banking partners. Ensured high availability and fault tolerance across all service components.
5. Automated Testing Framework & Quality Assurance - Developed robust automated test suites simulating high-volume payment scenarios. Built continuous testing pipelines to validate fraud rules, ML models, and new releases. Ensured accuracy, performance, and security across every deployment cycle.
6. Monitoring, Logging & Support Operations - Implemented real-time monitoring dashboards to track system health, fraud trends, and performance metrics. Built logging and audit trails to meet financial compliance standards. Provided long-term operational support, issue resolution, enhancements, and tuning of fraud rules/models.
Impact
Faster detection of fraudulent activity - Real-time analysis and alerting dramatically reduced the time between suspicious activity and intervention
Higher accuracy with fewer false positives - ML-driven scoring and refined business rules improved outcomes for both customers and financial institutions
Strengthened global payment security - Mastercard's fraud teams gained deeper insights and actionable intelligence at scale
Modern, scalable platform ready for future threats - Microservices and cloud-ready architecture allow continuous improvement and rapid expansion
