Liability and bodily injury claims automation
General liability fraud relies on manufactured incidents, professional claimants, and pre-existing condition exploitation. Mapping networks and validating scenes is slow manually. Hesper AI runs a full investigation on every flagged claim in minutes.
In short
Hesper AI's agents digest the demand package, read the policy for coverage and limits, reconstruct the incident timeline from records and statements, benchmark the valuation, and flag litigation risk early. Straightforward liability claims resolve straight through, and claims showing medical-mill or attorney-driven inflation patterns get a full investigation-grade workup first.
Last updated
Common liability fraud schemes
Liability fraud spans individual exaggeration to organized professional claimants operating across multiple venues. Hesper investigates every flagged claim across all four schemes simultaneously.
Slip-and-fall staging
Manufactured incidents in retail locations, restaurants, and commercial properties. Hesper AI analyzes scene photos for staging indicators, cross-references the claimant's history for prior similar claims, and verifies witness identities against known fraud ring databases.
Professional claimants
Serial fraudsters filing repeated liability claims across different businesses and locations. Hesper AI maps claimant identities across ISO ClaimSearch and NICB, detects patterns of similar claims filed within geographic clusters, and identifies shared attorneys across cases.
Exaggerated damages
Legitimate incidents with inflated medical bills, fabricated lost wages, or overstated property damage. Hesper AI detects altered amounts in medical billing documents, validates treatment timelines against injury severity, and cross-references wage claims with employment records.
Pre-existing condition exploitation
Attributing pre-existing injuries or conditions to a covered incident. Hesper AI analyzes medical record timelines to detect treatment patterns that predate the incident, identifies inconsistencies between current and historical medical documentation, and flags providers with unusual billing patterns.
Manual workflow vs. Hesper
Every phase compresses. The cumulative effect is the difference between a multi-week cycle and a decision in minutes.
How Hesper AI investigates a liability claim
Every liability claim runs through a structured investigation pipeline. Phases run in parallel where dependencies allow.
Incident scene and document ingest
Incident photos, accident reports, witness statements, medical records, and wage claim documentation are ingested simultaneously. Hesper analyzes each file across 200+ fraud signals at the pixel and text level.
Claimant history and identity check
Claimant identities are verified against ISO ClaimSearch, NICB, and public records. Prior claims history, professional-claimant patterns, and connections across multiple incidents are flagged with citations.
Witness and geographic analysis
Named witnesses are verified against public records and prior claim databases. Incident locations are mapped against known fraud clusters - repeat venues, shared addresses, and geographic ring indicators.
Medical and wage claim validation
Medical bills are analyzed for altered amounts, pre-existing conditions, and treatment patterns inconsistent with the reported incident. Wage claims are cross-referenced against employment records and published salary data.
Investigation report and recommendation
A complete investigation report is generated with scene findings, identity graph, medical analysis, and a denial or settlement recommendation. Output is SIU-ready and defensible in litigation.
Costs and compensation paid into the US tort system in 2022
Over $4,200 per US household
Source: US Chamber Institute for Legal ReformAverage annual growth in US tort costs, 2016 to 2022
Faster than inflation over the same period
Source: US Chamber Institute for Legal ReformHesper AI investigation time per claim
Hesper internal benchmark. Vs. 14+ days manually
Fraud signals analyzed per document
Hesper internal benchmark. Pixel-level plus text-level
Liability claims automation, answered
How does AI claims automation handle a liability demand package?
The agents read the whole demand - medical bills, records, wage loss, the letter itself - extract every line item, check the treatment against the documented injury, benchmark the valuation against comparable claims, and draft a response. Time-limited demands are flagged the moment they land, so the response deadline does not slip.
Can AI spot a medical mill or attorney-driven claim inflation?
Network analysis is built into the platform. The agents map which providers, clinics, imaging centers, and attorneys keep appearing together across unrelated claims, then compare treatment patterns and billing against the documented injury. A provider whose claims all follow the same treatment script shows up as a pattern, not as one adjuster's hunch.
How does Hesper flag litigation risk before a claim becomes a lawsuit?
Litigation scoring runs at triage alongside severity and fraud scoring, and it keeps updating as the file develops - representation appearing early, treatment escalating without a matching injury, a demand arriving faster than the medical record supports. Each flag carries its reasoning, so claims legal can act on it rather than re-derive it.
Can Hesper verify witnesses and reconstruct a premises liability incident?
Yes. The agents verify claimant and witness identities against public records, cross-reference statements for inconsistencies, run scene photos through pixel and metadata forensics, and rebuild the incident timeline from the documents on file. Every inconsistency is cited back to the source it came from.
Does Hesper replace our defense counsel or our adjusters?
No. The agents do the legwork - collecting, verifying, reconstructing, and citing. Settlement authority, negotiation, and the decision to litigate stay with your adjusters and your counsel. What changes is that they open a file that is already evidence-backed instead of building the record themselves.
How does Hesper fit with our existing claims system?
It integrates with the claims system of record through the API - Guidewire, Duck Creek, Majesco, or another - and writes evidence, valuations, and recommended actions back to the file. No rip and replace. Hesper can pick up a liability claim at first notice, or mid-stream for demand review or recovery screening.
Go deeper on liability claims fraud
Research, technical deep-dives, and playbooks from the Hesper AI team.
See Hesper investigate your liability claims
We'll run a sample investigation on your real flagged claims and show you the evidence package and report it produces.