The insurance industry's digital transformation has delivered genuine benefits — faster underwriting, instant policy issuance, streamlined claims processing, and mobile-first customer experiences that have expanded market reach. It has also created new attack surfaces that fraudsters are exploiting with increasing sophistication.

The traditional insurance fraud model required physical interaction. Filing a false claim meant visiting an agent, producing documentation, and subjecting yourself to potential in-person scrutiny. The friction was not intentional security — it was just how insurance worked — but it served a deterrent function. A fraudster had to be willing to look someone in the eye and lie.

Digital-first insurance has removed this friction for legitimate customers and fraudsters alike. A fraudulent claim can now be filed from a phone in minutes, supported by AI-generated documentation that is increasingly difficult to distinguish from genuine evidence. Fake medical reports, fabricated repair estimates, and doctored photographs of damage are all within reach of generative AI tools that cost nothing to use.

The identity layer is where the problem begins. Insurance fraud frequently involves identity manipulation — using a stolen identity to take out a policy and then stage a claim, creating a synthetic identity that exists solely to file fraudulent claims, or impersonating the policyholder to redirect a legitimate claim payout. Without robust identity verification at both the policy issuance and claims filing stages, insurers have limited ability to detect these manipulations.

The cost to the industry is enormous. Insurance fraud adds an estimated ten percent to premium costs in most markets, a cost ultimately borne by honest policyholders. For individual insurers, fraud losses can represent a significant share of claims expenditure, particularly in lines like auto insurance, health insurance, and property insurance where the frequency and potential payout of fraudulent claims are highest.

The most effective defence is identity verification at every touchpoint in the policy lifecycle. At onboarding, identity verification and biometric matching confirm that the person taking out the policy is who they claim to be, establishing a verified identity anchor for the policy. At the claims stage, re-verification confirms that the person filing the claim is the policyholder — not someone who has acquired their policy details through a data breach or social engineering.

For insurers processing claims remotely — which is now the majority — this re-verification must include deepfake detection. A video call with a claims adjuster is only useful for confirming identity if the person on the call is real. Without deepfake screening, a fraudster can impersonate the policyholder convincingly enough to authorise a payout redirect.

Document forensics adds another layer. Claims supported by AI-generated documentation — fake medical reports, fabricated repair invoices, doctored damage photographs — require verification systems that can detect the telltale signs of generative AI output. This is an arms race, but one where defensive technology is keeping pace with offensive capability.

Insurers looking to reduce fraud losses while maintaining the digital-first customer experience can implement deepidv's identity verification at both policy issuance and claims filing, providing biometric confirmation, document authentication, and deepfake detection in a workflow that adds seconds, not minutes, to the customer interaction.