Identity Verification for insurance – stop fraud at all points of risk

Prevent ghost broking, fronting and inflated or staged claims from the moment a user engages—quote to payout.

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What the Industry Says

In France, detected fraud reached €695 million in 2023, an increase of more than 18% compared to the previous year. But this figure represents only the tip of the iceberg; actual fraud could account for 3 to 10% of benefits paid.”

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Insurance Fraud Prevention Agency

Why Identity Risk is critical in insurance

Digital distribution has made it easy to spin up throwaway identities and attack multiple touchpoints from quote engines to self-service portals and claims. Synthetic profiles and impersonation now bypass basic checks; organised rings coordinate quotes, Mid Term Adjustments (MTAs) and payouts.

Top Threats

  • Application & policy fraud: ghost broking, fronting, synthetic identities, mis-stated risk data.
  • Account takeover & policy misuse: portal hijacks leading to fraudulent MTAs and bank-detail changes.
  • Claims fraud (opportunistic & organised): inflated damage/injury, staged accidents, fabricated losses.
  • Speed vs control: automation without identity trust exposes quote/First Notification of Loss (FNOL) to abuse.

How Oneytrust protects insurance journeys from day one

Oneytrust’s D-Risk ID takes an identity-first approach to secure quote, onboarding, policy changes and claims. It analyses identity signals, device/network fingerprints and behaviour to compute a real-time identity trust score, so you can approve good users instantly and stop bad ones at the door.  


Key Features

Synthetic identity detection Flags profiles with no footprint or mismatched data that slip past standard KYC checks.
Identity trust scoring in <2 seconds Real-time score you can tune to risk tolerance and product line—keep good users moving while you stop bad actors.
Device & network fingerprinting Correlates devices, IPs and sessions across an identity graph to reveal ghost-broker clusters, repeat abusers and Account Takeover (ATO) patterns.
Behavioural analysis Detects bots, industrial-scale quote stuffing, and suspicious navigation during FNOL or bank-detail changes.
Built on 15M+ verified real identities Improves precision on synthetic and impersonation attempts while keeping approval rates high
Fast API integration & configurable thresholds Drop into your quote engine, policy admin and claims workflows; adjust score cut-offs by product and exposure.
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Where it applies

  • At quote & onboarding: block ghost brokers/fronting without friction for all users
  • Account & MTAs: step-up only on risky sessions (new device/geo, anomalous behaviour, suspicious detail changes).
  • FNOL & claims: auto-route low-risk claims; pre-package high-risk cases for human review
  • Payouts: verify destination accounts and check link to known fraud networks before release. 

Identity verification in insurance—what you need to know

Use risk-based step-up. Combine identity, device and behaviour signals; only challenge when the trust score crosses your threshold (<2s decisions keep good users flowing).

Yes. Network analysis across identities, contact points, devices, addresses and IBANs exposes clusters that siloed tools miss.

No—D-Risk ID scores in under two seconds and flags only high-risk profiles; low-risk claims stay automated.

It’s API-based; you control thresholds and decisioning in your existing workflows.

See how Oneytrust stops identity fraud for insurers

Talk to our experts about how we can prevent identity fraud, protect quote-to-claim journeys and improve loss ratios—without adding friction.

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