At Vidal Health Insurance TPA, artificial intelligence is scanning medical bills, prescriptions and supporting documents line by line, flagging duplicate claims, inflated charges, unnecessary procedures and even signs of document tampering in real time, according to Sonali Kulkarni, Country Head, BFSI, Microsoft India and South Asia.
What earlier took manual scrutiny now happens the moment a claim is filed.
At ICICI Lombard, the shift is just as stark. AI, once used mainly for motor inspections, now tracks health claims and fraud patterns helping cut processing time by around 50% while tightening checks that leave less room for inconsistencies to slip through.
At Bajaj General Insurance, multiple AI “agents” work simultaneously—cross-checking documents, validating treatment costs, and scanning for medical abuse—turning every claim into a multi-layered verification process, especially in cashless cases.
AI in insurance is no longer experimentation.
Insurers are detecting up to five times more fraudulent claims and reducing processing time by about 40%, as AI moves from a back-end tool to a real-time watchdog embedded across the claims lifecycle, according to Kulkarni.
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The traditional process of claims management has been significantly accelerated with AI in the picture.
Santosh Bhat, Head of Advanced Technology at Policybazaar, explained, “Document verification, fraud detection, and damage assessment processes have all been automated, and claims can now be evaluated within minutes. Natural language processing (NLP) enables AI to understand and process customer communications, while image recognition technology helps assess damages from photos, which is especially useful in motor insurance claims. Over the last few years, this automation has not only reduced human error but also ensured that legitimate claims are processed more quickly, resulting in a smoother customer experience and faster payouts.
Scrutiny is beginning at the start not the end. And the outcome is a system that is both faster and far less forgiving.
For genuine policyholders, that means quicker payouts and more predictable outcomes. For those attempting to game the system, the window is rapidly narrowing.
With document intelligence, image analysis and policy validation working together, claims are being checked against policy terms, pricing benchmarks and treatment protocols as they are filed.
Small mismatches that might earlier have gone unnoticed are now flagged immediately.
Kulkarni said the real power of AI in insurance lies in being explainable, auditable and backed by human oversight, ensuring that while fraud detection sharpens, genuine claims are not caught in the crossfire.
Under the hood, insurers are treating AI as shared infrastructure—building common data layers and control frameworks that allow them to apply the same level of scrutiny across motor, health and other segments, while maintaining clear audit trails.
The rise of “agentic” AI—where specialised systems handle anomaly detection, compliance checks and document verification in parallel—is pushing this even further, enabling real-time, claim-level policing without slowing the system down.
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