Real-time fraud detection using ensemble ML models with anomaly scoring, transaction pattern analysis, and 99.2% detection accuracy.
Manual data processing in FinTech Security could not scale with the organization\'s growth. They needed an intelligent automation layer to extract insights and predict trends accurately.
We deployed advanced machine learning models to automate feature engineering, provide real-time inference, and boost overall accuracy.
Real-time fraud detection system processing transaction streams with ML risk scoring, rule-based decisioning, and case management workflow.
Transaction ingestion through feature computation, ML risk scoring, rule-based blocking, case investigation, and model feedback loop.
Every payment transaction published to Kafka topic; Flink consumer processes the stream in real time.
Flink computes 100+ features (velocity, geo-distance, device fingerprint) from transaction + historical context in under 50ms.
XGBoost model assigns fraud probability score (0–1); scores above threshold trigger block or review rules.
Flagged transactions open cases in the investigator dashboard; analyst decision feeds back to model retraining loop.
A battle-tested methodology that turns complex challenges into elegant, high-performance solutions.
Deep-dive into business requirements, user personas, market analysis, and technical landscape assessment.
System architecture blueprints, UI/UX wireframes, interactive prototypes, and design system creation.
Iterative sprints with CI/CD pipelines, code reviews, automated testing, and continuous stakeholder feedback.
Production deployment, performance monitoring, A/B testing, and post-launch growth optimization.
Every solution we build comes packed with enterprise-grade features that ensure reliability, performance, and scalability.
SOC 2 compliant infrastructure with end-to-end encryption and zero-trust architecture.
Auto-scaling cloud infrastructure designed to handle 10x traffic spikes seamlessly.
WebSocket-powered live updates ensuring data consistency across all touchpoints.
Pixel-perfect experiences across all devices, from mobile to 4K displays.
Custom dashboards with real-time KPIs, funnel analysis, and predictive insights.
RESTful & GraphQL APIs enabling seamless third-party integrations and extensibility.
Key architectural decisions, data flow optimizations, and security patterns implemented for enterprise performance.
Kafka → Flink → Redis feature cache → XGBoost inference pipeline delivers fraud decisions in under 100ms at 50K TPS.
Browser/device fingerprint combined with behavioral biometrics (typing cadence, mouse movement) detects account takeover.
Analyst-labelled cases feed a daily retraining pipeline using MLflow, with automatic champion-challenger comparison before promotion.
We carefully selected a cutting-edge technology stack to ensure maximum performance, maintainability, and future-proof scalability for this project.
"The AI models Techphin deployed reduced our processing time by 60% and improved prediction accuracy to levels we didn\'t think were possible."
Let's transform your idea into a world-class digital product. Our team is ready to bring your vision to life.
Get Free Consultation