Responsibilities

• Analyze historical insurance data (policies, claims, endorsements, cancellations) to identify fraud patterns.
• Develop, review, and optimize fraud prevention rules across the insurance lifecycle (policy issuance, mid‑term changes, and claims).
• Adjust risk weights and parameters based on data‑driven insights.
• Identify suspicious profiles (policyholders, third parties, service providers, repair shops, etc.).
• Monitor fraud‑related KPIs, such as fraud rate in claims, suspicion vs. confirmation ratio, false positives, detection time.
• Investigate anomalies in claims frequency, coverage usage, repeated entities (ID, phone number, address, vehicle, etc.).
• Perform data cross‑referencing using internal and external sources.
• Support the creation and maintenance of blacklists and risk profiles.
• Conduct testing and validation of new fraud rules (including A/B testing).
• Research and p...