Fraud Intelligence Platform
A real-time fraud intelligence layer for a regional fintech operating across mobile money and card payment rails, surfacing anomalies fast enough to act before settlement. The client's identity is withheld under a confidentiality agreement.
Client
East African fintech, name withheld
Role
AI architecture, platform engineering, and analyst workflow design
Duration
Multi-phase engagement under NDA
Thesis
Deployment
Sector
Finance
Outcomes
What changed.
Lower
Detection-to-action latency materially reduced
Fewer
Reduction in noisy false-positive review load
Auditable
Full investigation trail per case
Context
The setting
The client operates at the intersection of mobile money and card rails, where fraud patterns evolve continuously and the cost of late detection is settled losses. Existing rule-based controls were too slow and too noisy.
Challenge
What we had to solve
- Fragmented signals across mobile money, card, and merchant rails
- Rule-based system generating high false-positive volumes
- Latency between signal and intervention measured in minutes
- Strict data residency and confidentiality requirements
Approach
How we delivered.
Unified signal layer
Consolidated transaction telemetry from multiple rails into a single feature store.
Real-time scoring
Combined behavioural baselines with anomaly detection to score events as they happen.
Analyst workspace
Investigation UI for fraud analysts with case management and audit trails.
Highlights
What was shipped
- Cross-rail signal consolidation
- Real-time anomaly scoring
- Analyst case management workspace
- Tighter feedback loops between models and reviewers
Stack
Technology
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