AI-powered claims assessment for a specialist insurer

The business

A specialist insurance operation handling high-value claims — fine art, antiques, jewellery, and collectibles. Each claim involves detailed assessment of authenticity, condition, provenance, and current market value. Claims range from a few thousand pounds to six figures.

The team was experienced but stretched. Three handlers processed all incoming claims, each carrying a caseload that left little time for thorough research. The business relied on their expertise, but that expertise wasn't documented, wasn't consistent, and walked out the door every evening.

The challenge

Two problems were compounding each other.

Assessment quality was inconsistent. Each handler had their own approach. One might spend an hour on provenance research. Another might skip it if the declared value was under a threshold. Market valuations were based on whichever comparables the handler found first, not a systematic search. Two handlers assessing the same claim could reach different settlement figures — sometimes significantly different.

Fraud detection was experience-dependent. The senior handler had twenty years of pattern recognition. The junior handler had two. There was no systematic way to flag suspicious claims beyond individual gut feel. Known fraud patterns weren't codified anywhere. When the senior handler was on leave, the fraud catch rate dropped visibly.

The business needed the quality and consistency of its best handler, applied to every claim, every time — without tripling the headcount.

What we built

A claims intelligence platform with a six-stage AI pipeline that processes each claim through a structured assessment workflow.

Document processing. Claim submissions arrive in various formats — PDFs, photos, handwritten valuations, auction certificates. The system extracts and structures all relevant information automatically. No manual data entry from claim forms.

Item identification. AI image and text analysis identifies the specific item being claimed — maker, period, materials, distinguishing features. For art and antiques, this includes style attribution and period consistency checks.

Market research. Automated valuation against current market data. The system searches auction house records, dealer networks, and comparable sales databases to establish a fair market range. Each comparable is sourced and timestamped.

Fraud analysis. Cross-referencing against industry fraud databases with pattern matching. The system checks for duplicate claims, inflated valuations, provenance gaps, and known fraud indicators. Flags are raised with specific evidence, not just a score.

Confidence scoring. Signals from all previous stages are aggregated into a risk-weighted confidence score. High-confidence claims move quickly. Low-confidence claims are escalated with a clear explanation of what triggered the flag.

Settlement calculation. A recommended settlement is generated based on verified market values, policy terms, coverage limits, and any applicable excess. The full calculation is broken down step by step — nothing is a black box.

The claims dashboard provides operational oversight across the network: total claims, active caseload, declared values, settlement savings, and handler workload distribution. Individual claim views show item-level detail with provenance research, market comparables, and the AI-generated assessment report. Every decision in the pipeline is auditable.

What the platform does

Handlers spend their time on judgement, not data gathering. The pipeline runs the document extraction, market research, and cross-referencing in the background, leaving human reviewers to make the calls that actually need expertise.

Fraud checks become systematic. Every claim passes through the same database lookups, pattern matches, and thresholds — so catch rates stop depending on which handler happens to pick the file up.

Settlement methodology becomes consistent. Two handlers working the same claim draw on the same market data and the same calculation steps, so valuations converge and every settlement comes with a documented rationale.

Audit trails are built in by default. Every stage of every assessment is logged with timestamps, sources, and confidence scores, ready for regulatory review or policyholder dispute without reconstruction.

Concept build. Fictional brand. All data illustrative.