Insurance Fraud Detection

Catching Fraud at a Scale No Team Could Match

A leading Thai insurer struggled with post-payment losses from high-volume fraudulent accident claims that overwhelmed human reviewers. AIGEN developed a fraud prediction model trained on years of historical data to identify suspicious patterns. The model now scores every claim before adjudication, triaging high-risk cases for specialist review while enabling straight-through processing for clean claims.

Claim Triage & Straight-Through Processing

Screening Claims So Humans Focus on What Matters

Facing days of backlog from thousands of weekly submissions that will only keep growing with business, a leading insurer implemented AIGEN’s claim decision support system. The solution automates classification by risk and complexity, selects policy eligibility, and predicts outcomes, all with explanation. This achieved a dramatic reduction in handling time and a significant uplift in adjuster productivity, focusing human expertise on the most complex cases.

Audit Enablement

Auditing What Was Previously Impossible to Audit

Compliance teams of a motor insurance company previously sampled only 5–10% of transactions due to human limits. AIGEN’s automated audit model now screens 100% of transactions against policy rules and anomalies, turning sampling into a comprehensive control.

In another case, an insurer using third-party administrators (TPAs) as claim processor can now move beyond merely random reviews of high-value claims. AIGEN’s aiClaim streamlines checks, allowing more cases to be audited to catch leakages and mistakes, maximizing savings.

Medical Cost Intelligence

From Invoice Chaos to Category-Level Cost Insight

A health insurer was paying out billions of baht in medical claims annually with almost no visibility into what they were actually paying for at a granular level. AIGEN encoded and categorised all medical line items from thousands of hospital invoices — standardising drug names, medical procedures, and consumables into a clean taxonomy. For the first time, the insurer could see exactly how much each brand of paracetamol cost at each hospital across their network — benchmarking prices, identifying outliers, and entering provider negotiations with data-backed confidence.

Medical Anomaly Detection

Detecting Irrelevant Medicines That Drain Millions

Medicines prescribed for conditions unrelated to a patient’s primary diagnosis are a significant sourceof claim leakage — whether from fraud, clinical waste, or billing abuse. AIGEN’s anomaly detection model cross-references every medicine line item against the diagnosis and treatment context, automatically flagging items that cannot be clinically justified. Cases that would take a medical reviewer hours to detect — across thousands of claims per week — are surfaced in seconds, protecting insurers from losses that human teams simply don’t have the bandwidth to catch.