Build an Insurance Fraud Detection System for Nigerian Insurers

Insurance fraud in Nigeria is pervasive across motor, health, and property lines. Ghost claimants, staged accidents, inflated vehicle values, and duplicate claims across multiple insurers are common. Large insurers have invested in internal fraud teams but small and mid-size insurers — which collectively hold the majority of retail policies — have no fraud detection infrastructure and lose a disproportionate share of their premiums to fraud. Your challenge is to design a shared insurance fraud intelligence platform for the Nigerian market that enables multiple insurers — including small ones — to contribute and access fraud signals without exposing proprietary claims data to competitors. It must flag suspicious claims within one hour of submission, cover at least three insurance lines, and comply with the Nigerian Data Protection Act. Submit a platform design document (max 12 pages) including: the data sharing model that protects competitive information, the fraud signal detection methodology, regulatory compliance approach, how small insurers access the platform at affordable cost, a governance model for the shared database, and a plan to onboard 20 insurers within 18 months. Judging criteria: 40% fraud detection methodology, 30% data sharing model balancing intelligence with confidentiality, 20% NDPA compliance design, 10% insurer onboarding plan.