Fraud, waste, and abuse continue to cost the global insurance industry billions each year. In Asia-Pacific alone, 30–40% of health insurance claims costs can be linked to FWA. Yet most insurers still rely on siloed data and manual reviews that struggle to detect complex fraud patterns.

As a result, insurers face:

• Escalating claims leakage and financial losses
• Inefficient fraud investigations and long triage times
• Difficulty identifying collusion networks hidden within claims data

To stay ahead, insurers must evolve using AI-driven insurance analytics to reveal hidden risks and automate fraud detection at scale.