Know the risk before you price it.
Behavioral scoring at onboarding — even with no history.
Static data answers who the client was. Zarv ID answers who they are right now — even with no history.
What Zarv ID does.
KYC & Identity Verification
Document verification (ID, driver's license, passport), facial biometry with liveness detection, deepfake and tampered document detection. Synthetic identities blocked. PEP screening and Zarv Restricted Profiles check.
Fraud at contracting costs more than preventing it. Zarv ID blocks before any contractual bond is established.
Graph Intelligence — Relational Score
Every individual is analyzed in the context of their network. Detects fraud clusters: if someone is linked to 3+ flagged identities, their score rises. Identifies straw buyers and fraudsters invisible to bureaus.
Sophisticated fraudsters pass individual KYC. What gives them away is the network around them. The graph detects what documents don't show.
Behavioral Score (No Prior History)
Score calibrated for insurance and vehicle credit. Works for people with no prior policy or credit history. Detects geolocation shifts, atypical patterns, and incoherent history. Output: numeric score + risk band + flags.
Profiles without history get rejected or overcharged. With Zarv ID, you can price what was previously unknown risk — more volume, same loss ratio.
Pricing Recommendation
Coming SoonNot just a score — a premium band recommendation. Segmentation calibrated to your portfolio. API integration with your pricing engine. Compatible with existing actuarial models.
Underwriters don't need another score to interpret. They need a decision. Zarv ID delivers the decision — with data to back it.
Graph Intelligence — data sources
Zarv ID builds a relationship graph integrating these data sources:
In practice.
New client underwriting — zero-km vehicle
Low bureau score due to lack of history → rejection or excessive premium → client leaves for competitor.
→Behavioral graph reveals the driver lives in a low-risk area, works regularly, and has no links to suspicious profiles → competitive premium band → client accepts → policy issued with accurate pricing.
Identity fraud detection at renewal
Automatic renewal — no flags raised.
→Relational risk flag: the holder's SSN is linked to 4 claims at other insurers in 18 months → underwriter reviews → fraud pattern identified → renewal denied.
Lending to a client with no vehicle credit history
Rejected due to unknown risk.
→Graph shows consistent income patterns, stable employment location, active business links → positive risk scoring → financing approved with adequate guarantees → client stays current.
Dealership fraud detection (suspicious EIN)
Multiple applications processed without red flags.
→Dealership EIN appears in the graph linked to other flagged EINs — fraud cluster pattern → automatic alert before credit release.
Per-driver scoring for personalized fleet insurance
Flat premium for entire fleet, regardless of individual driver risk.
→Each driver scored individually → fleet segmented into risk bands → insurer issues differentiated policy → company reduces total premium.
Proven results.
Client performance (TagPro, B2C)
Validated in client operations
B2C — TagPro
B2B — Arval / BNP Paribas
TagPro — year over year after implementation
Proven at scale.
TagPro
Insurer · Auto Insurance (B2C)
New clients onboarded via Zarv ID (KYC + scoring)
Portfolio monitored in real time via Zarv Signal
Losses investigated via Zarv Lens with evidence generation
Arval / BNP Paribas
Leasing + Self-Insurance · Corporate Fleet (B2B)
Fleet monitored continuously via Zarv Signal
Claims reconstructed automatically via Zarv Lens
Zarv ID integration underway for new lessee onboarding
Ready to integrate.
Per API request (pay-per-use). No minimums during pilot. Volume discounts available.
API DocumentationYour data, protected by design.
See risk before it costs you.
GDPR & CCPA Compliant · No commitment · Integration in days