Zarv
For Insurance

Fraud gets paid. Without proof.

Better underwriting. Continuous monitoring. Fraud-proof claims. One platform.

Key Capabilities

1

Behavioral Risk Scoring at Underwriting

87% accuracy. Price risk right from the start — even thin-file profiles. 200+ data sources analyzed in under 150ms.

2

Continuous Risk Monitoring

Monitor $150M in assets in real time. Detect behavioral anomalies, geofencing violations, and high-risk patterns that predict claims before they happen.

3

Dynamic Repricing Signals

Risk shifts. Premiums should too. Zarv Signal triggers repricing based on observed behavior, not renewal cycles.

4

Claims Intelligence & Fraud Detection

Investigate claims 34x faster. Cross-reference 15+ data sources, detect fraud patterns, generate court-ready reports — all AI-powered.

Proven results.

18%

Avg. loss ratio improvement

First 12 months post-implementation

87%

Behavioral scoring accuracy

Compared to bureau-only models

93%

Fraud prevention rate

Claims processed with Zarv Lens

34x

Faster claims investigation

Compared to manual processes

How Insurance Works with Zarv

1

Underwriting

Zarv ID

Behavioral risk scoring at quote generation

Price risk accurately from day one. Reduce adverse selection by up to 31%.

2

Policy Lifecycle

Zarv Signal

Continuous monitoring of insured assets & driver behavior

Detect risk changes in real time. Trigger repricing or cancel high-risk policies mid-term.

3

Claims Processing

Zarv Lens

AI-powered fraud investigation & evidence generation

Deny fraud with hard evidence. Reduce claims leakage by up to 41%.

Who trusts Zarv.

"Zarv helped us reduce loss ratio by 19% in year one. The behavioral scoring caught risks our traditional models completely missed."

Head of Underwriting · Top 10 US Insurer
19% loss ratio reduction in 12 months

Common Questions from Insurance Teams

How does Zarv ID improve on traditional credit bureau scoring?

Credit bureaus provide static, backward-looking data. Zarv ID analyzes 200+ behavioral signals in real time — mobility patterns, network effects, cross-reference verification. Especially powerful for thin-file profiles where credit history is limited.

Can Zarv Signal really trigger mid-term repricing?

Yes. When persistent behavioral anomalies are detected — frequent speeding, late-night driving in high-risk zones, geofencing violations — Signal generates documented, audit-ready alerts that underwriters can use to justify mid-term adjustments.

What happens if Zarv Lens finds evidence of fraud after we've already paid a claim?

Zarv Lens is designed for pre-payment investigation. If fraud is detected post-payment, the evidence — location discrepancies, tampered odometer, collision physics analysis — is court-ready and usable for recovery proceedings.

How fast can we integrate Zarv into our existing underwriting system?

Most insurers integrate Zarv ID into their quote engine within 2 weeks via REST API. Signal requires vehicle ID mapping (3-4 weeks). Lens deploys as a standalone tool or integrates into your claims workflow.

What does 'behavioral risk scoring' actually measure?

Mobility patterns, time-of-day behavior, geographic risk zones, network relationships via graph analysis, device behavior, and cross-verified identity markers. These signals predict claim probability better than static credit data alone.

See risk before it costs you.

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