Insurance fraud specialist analyzing claims evidence and reconstructing loss events for Gramian Consultancy’s AI training and evaluation projects. Producing evidence-based assessments of staged and fraudulent claims.
Responsibilities
Analyze digital claim evidence, including CCTV footage, dashcam recordings, scene photographs, witness statements, and engineering reports
Identify inconsistencies, anomalies, and indicators that may suggest staged incidents or fraudulent claims
Reconstruct accident and loss events using visual, technical, and documented evidence
Assess the authenticity of reported incidents and evaluate potential causes of loss
Prepare detailed, structured written assessments suitable for Special Investigation Unit (SIU) investigators, forensic engineers, and insurance professionals
Explain investigative findings and support conclusions with clear, objective evidence
Identify patterns associated with staged-loss incidents, suspicious claims, and potentially organized fraud schemes
Review technical reports, visual evidence, and claim documentation for accuracy and consistency
Contribute investigative insights and industry best practices to AI training and evaluation datasets
Collaborate remotely with project stakeholders and provide professional feedback and clarifications
Requirements
Minimum 7 years of relevant professional experience in Special Investigations / Special Investigation Units (SIU), Insurance Fraud Detection, Claims Investigation, Forensic Engineering, or Fleet Safety Investigation or Review
Demonstrated experience analyzing insurance claim evidence and evaluating incident authenticity and causation
Strong ability to interpret visual evidence, technical reports, statements, and supporting documentation
Experience identifying inconsistencies and potential indicators of staged-loss incidents or fraudulent activity
Excellent analytical and critical-thinking skills
Strong written communication skills, with the ability to produce detailed, evidence-based investigative reports
Ability to work independently and communicate findings clearly in a remote environment
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