— Agents / Fraud Intelligence Agent

Fraud Intelligence Agent

From suspicious signals to investigation-ready intelligence

Detect fraud patterns humans miss.

AI that investigates every claim, document, image, invoice, vendor and historical record — connecting hidden signals to uncover fraud before it becomes a payout.

FOUR DEALERS — REVIEWED INDIVIDUALLY D-118OP 7734WITHIN BAND D-204OP 7734WITHIN BAND D-331OP 7734WITHIN BAND D-407OP 7734WITHIN BAND SAME OPERATION · SAME QUARTER · SHARED SUPPLIER no single claim is anomalous
FIG. 04 — the pattern is not in any claim, it is between them

— What it does

Detect→Connect→Investigate→Prevent
  1. 01 Cross-claim

    Cross-Claim Intelligence

    Detect duplicate claims, reused evidence, recurring entities and suspicious patterns across millions of records.

  2. 02 Vision

    Visual Fraud Detection

    Identify image reuse, manipulation, damage inconsistencies and suspicious visual evidence.

  3. 03 Network

    Entity & Network Intelligence

    Connect claimants, garages, vendors, vehicles, invoices and investigators to reveal hidden relationships.

  4. 04 History

    Historical Pattern Analysis

    Compare every new claim against years of historical data to surface anomalies and known fraud patterns.

  5. 05 Evidence

    Explainable Investigations

    Give investigators the evidence, connections and reasoning behind every fraud signal.

Don’t just flag suspicious claims. Investigate the intelligence behind them.

03 Between the claims

Some of what we do saves effort. Some of it finds what no one could.

Adjudicating faster is a cost story with a headcount answer. Surfacing a collusion ring no reviewer could have seen is a different line on the P&L.

Dealers × repair operations
FIG. 05 — one cluster, four dealers Cluster surfaced

A single inflated labour line is invisible. The same inflation, on the same operation, at four dealers who share a parts supplier, is a finding — and it exists only once every claim is in the same place.

Claims a warranty audit team can reviewA sample
Claims an Actuora agent readsAll of them
Where a collusion pattern livesBetween claims
Who keeps the scoring harnessYou do

— Return

Fraud & Claims
Up to 3% additional fraud detected

In claims already processed — surfaced by cross-claim and historical intelligence that rule-based screening cannot reach.

Baseline: fraud already caught by existing controls. Counted only where the customer’s own investigators confirmed the finding.

Turning millions of records into actionable fraud signals

— Start here

Your closed claims are an answer key. Let us be graded against them.

Send us nothing. We send you one file, your own IT runs it offline against a single export of closed claims, and you keep what it finds either way.