• We worked with the client to design and deploy a cloud-based fraud detection platform powered by AI-driven decisioning services. The system analyzes loan applications in real time, combining behavioral patterns, document validation, and ML-based anomaly detection on network-level signals to identify fraud risks

• Applications are processed through automated pipelines with configurable rules that cross-check identity data, historical activity, and partner bank requirements. Fraudulent or suspicious profiles are blocked before reaching partner systems, significantly reducing the volume of false applications passed downstream

• The platform was deployed on a cloud-native stack with autoscaling, fault isolation, and observability to support growth. For the aggregator’s risk and compliance teams, we introduced real-time monitoring and case management tools, while partner banks consumed structured outputs via APIs and regulatory reports

• This architecture ensured faster approvals for legitimate applications, stronger fraud defenses, and clear audit trails to support compliance requirements