FinTrack: AI Analytics
FinTrack needed to scale data ingestion and analytics to support real-time fraud detection and reporting for enterprise clients. We built an AI-driven pipeline and dashboard that improved throughput and reduced analytic latency.
The Challenge
FinTrack was processing growing volumes of transaction data with legacy batch pipelines. The team needed near real-time insights and more accurate anomaly detection to reduce fraud losses and improve customer trust.
Our Approach
We implemented a streaming data architecture, combining serverless ingestion on AWS Lambda with an online feature store and streaming ML models for anomaly detection. We also designed a dashboard for business analysts with real-time reporting.
Impact
Throughput increased by 5x, detection accuracy improved by 18%, and time-to-insight dropped from hours to seconds. FinTrack was able to onboard two enterprise customers within 6 months of launch.