P&C Insurance · live proof

VIN-repeat, geo-cluster, and fatal-rate outliers from real NHTSA crash data.

pc-engine ingests the NHTSA FARS public crash register, indexes by VIN, lat/lon, and make/model/year cohort, and runs three deterministic checks per engagement. Same kernel that ships every other JIL vertical: customer-profile gated on lob = 'pc_insurance_carrier', sealed CREB on every finding, FRE 902(14) self-authentication.

3
Production checks live
FARS
NHTSA national crash dataset
8955
Engine port (internal)
CREB
Sealed receipt per finding
Section 01 · Three production checks

What pc-engine fires on.

pc_vin_repeat

Same VIN appearing in 2+ distinct crash records. Cross-state span and presence of fatalities escalate severity. Leading indicator of staged-accident rings, VIN cloning, salvage-title fraud. Regulatory basis: NAIC Anti-Fraud Plan model, NHTSA defects investigation, TREAD Act 49 USC 30166.

pc_geo_cluster

Crashes clustered within a configurable radius (default 500m) above a configurable threshold (default 5+ crashes). Material indicator of staged-accident rings operating from a single location. Regulatory basis: NAIC Anti-Fraud Plan model, NAIC P&C Annual Statement.

pc_fatal_rate_outlier

Make/model/year cohort with fatal-crash rate at least 2.0x the peer mean for the same body-style and model-year cohort. Precursor signal NHTSA uses to open defects investigations. Regulatory basis: TREAD Act 49 USC 30166, SAE J2980.

Section 02 · Sample CREB

What the carrier takes to NAIC or NHTSA.

finding_id : cf3b9210-...-pc-vin-repeat-001
check_id : pc_vin_repeat
subject_type : vin
subject_id : 1HGBH41JXMN000001
severity : critical
occurrences : 5 distinct crash records
state_count : 3 states
fatal_count : 2 fatalities
regulatory_basis: NAIC Anti-Fraud Plan, NHTSA defects investigation, TREAD Act 49 USC 30166
code_version : pc-engine@2026.05.01-pc-1
Section 03 · Methodology

Deterministic, replayable, court-defensible.

Same kernel as the other 7 verticals. The VIN-repeat check is a SQL aggregate; geo-cluster bins crashes into a regular grid sized to the configured radius; fatal-rate outlier joins each cohort against the peer-mean for body-style + model-year. No stochastic LLM in the verdict path. Ava (the in-house agentic AI) groups, narrates, and routes findings; it never produces the underlying flag.

Customer engagement adds depth. Tier 2 brings carrier-supplied claim records, repair estimates, telematics, photos, named-actor cross-reference. Optional ATTOM API for premise classification. The public-data POC above is the Tier 1 baseline, included in every engagement.
Reality check. Statistical outliers are not adjudicated fraud. The value of pc-engine is not "list of bad actors" - it is "list of cohort outliers, sorted, with each finding's reconciliation pathway and cost pre-computed." Ava layers on top, separating expected variance from genuine staged-accident or VIN-cloning signal.