Case study: an insurer reduces claims processing by 12 days with CheckFile

A regional insurer reduced its claims processing time from 18 days to 6 days — an acceleration of 12 days — by deploying CheckFile on its document verification workflow. In parallel, the detected document fraud rate rose from under 1% to 4.7%, revealing systematic falsifications that human checks were not catching. Detection recall reaches 94.8% with a false positive rate of 3.2%.

This article is for informational purposes only and does not constitute legal, financial, or regulatory advice. Regulatory references are accurate as of the publication date. Consult a qualified professional for guidance specific to your situation.

This case study details the deployment of CheckFile at an insurer we shall call Regional Insurance Co. The data presented come from real operational measurements, anonymised in accordance with confidentiality agreements.

Context: an insurer confronting the documentary complexity of claims

Regional Insurance Co is a general insurer (property, motor, liability) based in the Midlands, 500 employees, portfolio of 280,000 active policies. It processes approximately 15,000 claims per year, covering home, motor, professional indemnity, and commercial multi-risk.

As an insurance company, Regional Insurance Co is subject to oversight by the Financial Conduct Authority (FCA) and the Prudential Regulation Authority (PRA). The Insurance Act 2015 governs disclosure duties, while Solvency II imposes governance and internal control requirements on claims management processes.

Each claim generates on average 4 to 7 supporting documents: accident reports, repair invoices, tradesperson quotes, insurance certificates, damage photographs, bank statements in cases of theft. Before deploying CheckFile, the entirety of these documents was manually reviewed by a team of 12 claims handlers.

Starting indicators:

The challenge: detecting invisible fraud without slowing settlement

Document fraud systematically underestimated

The document fraud rate detected by human handlers was under 1%. This figure contrasted with industry data: the Insurance Fraud Bureau (IFB) and the Association of British Insurers (ABI) estimate that insurance fraud costs the UK industry approximately £1.2 billion per year, with a significant proportion relying on falsified documents.

Regional Insurance Co suspected under-detection but had no means of quantifying it. Claims handlers, trained in the technical assessment of claims, had neither the tools nor the time to examine in depth every invoice, every quote, and every certificate. Document checks were limited to quick visual verification: is the document legible? Is the amount consistent with the claim? Does the name match the policy?

A processing time generating dissatisfaction

The average 18-day delay between claim notification and settlement resulted from three bottlenecks:

1. Document collection (7 days on average) — policyholders took an average of one week to gather and submit all supporting documents. Follow-ups for missing or illegible documents extended this delay.
2. Manual verification (6 days) — each handler processed 5 to 7 complete case files per day. Complex case files (multi-party, escape of water with multiple parties) required 2 to 3 hours of verification.
3. Approval and payment (5 days) — internal approval circuit, settlement issuance, policyholder notification.

This 18-day delay placed Regional Insurance Co below the market median (15 days for comparable general insurers, based on FCA data on insurance practices). 23% of claims generated a complaint related to delays, a documented attrition factor: policyholders dissatisfied with their claims handling switch providers in 40% of cases at renewal.

The financial cost of undetected fraud

With an estimated real fraud rate of 4-6% (ABI sector average), undetected fraud was costing Regional Insurance Co between £1.9 and £2.9 million per year in wrongful indemnities. This amount represented the equivalent of the technical result for the home branch. The choice presented itself in simple terms: absorb the loss or invest in detection.

The solution: CheckFile deployed on the claims workflow

Scope of deployment

CheckFile was integrated into Regional Insurance Co's claims management system to automatically analyse six categories of supporting documents:

For each document, CheckFile executes a battery of automated checks:

• OCR extraction with 98.7% accuracy — structured extraction of key fields (amounts, dates, names, addresses, Companies House registration numbers).
• Cross-validation — cross-referencing extracted information with the claim notification, insurance policy, and other documents in the case file.
• Falsification detection — EXIF metadata analysis of photographs, retouching detection on invoices and quotes, font and layout consistency checks.
• Deepfake detection — identification of entirely AI-generated documents, whose prevalence increased by 23% between 2024 and 2025 according to our platform trend data.
• Company verification — checking the existence and active status of the company issuing invoices and quotes via Companies House records.

Technical integration

Deployment took 4 weeks:

• Weeks 1-2: REST API integration into the claims management system, detection rule configuration by claim type, policy reference system connection.
• Week 3: parallel operation period (human verification + CheckFile simultaneously) to calibrate detection thresholds and measure discrepancies.
• Week 4: production switchover, handler training on the alert review interface, fraud routing circuit setup.

The parallel operation period (week 3) was decisive: it revealed that CheckFile detected anomalies on 4.3% of case files — compared with 0.8% for human handlers on the same case files. This gap convinced management of the deployment's relevance.

Results: the data after 18 months of operation

Key figures

Decomposition of the delay reduction

The 12-day reduction breaks down across the three process phases:

The largest gain comes from the verification phase (-5 days). CheckFile analyses each document in an average of 4.2 seconds. A complete case file of 5 documents is processed in under 30 seconds, compared with 45 minutes to 2 hours for a human handler.

Anatomy of detected fraud

The 4.7% document fraud rate detected by our platform in the insurance sector breaks down into five categories:

These figures are consistent with the document fraud trend data recorded by our platform, which identify payslips (31%), proof of address (22%), and bank statements (15%) as the three most frequently falsified document types across all sectors. In the insurance sector, fraud logically concentrates on invoices and quotes, which directly determine settlement amounts.

The seasonal effect confirmed

Regional Insurance Co's operational data confirm the September peak identified on our platform (+35% fraud attempts compared with the annual average). This peak is explained by the convergence of three factors: academic year start (home claims related to relocations), end of summer period (motor claims post-holiday), and case file reconstitution after claims team holidays.

Financial impact

Detecting 4.7% document fraud on an annual volume of 15,000 claims represents approximately 700 fraudulent case files identified per year. With an average claim amount of £3,400 at Regional Insurance Co, avoided fraudulent settlements total approximately £2.4 million per year.

Across all our clients, our platform has prevented an estimated £10.8M in fraud. The CheckFile Document Risk Index assigns a score of 6.8/10 to the insurance sector, reflecting exposure distributed between identity documents (underwriting) and financial documents (claims).

Lessons learned: what this deployment reveals about insurance fraud

Three fraudster profiles

Analysis of the 700+ fraudulent case files identified by CheckFile at Regional Insurance Co reveals three distinct profiles:

The opportunistic fraudster (58%). A legitimate policyholder who inflates the amount of a genuine claim. Original invoice retouched to increase the amount by 15 to 30%, addition of a fictitious service line, or submission of a supplementary quote for work unrelated to the claim. This profile is the most frequent and hardest to detect manually because the underlying claim is real.

The organised fraudster (27%). Networks producing entirely fictitious case files: fake accident reports, false invoices from phantom companies (valid Companies House registration but business activity unrelated to declared work), damage photographs recycled from other claims. This profile represents the highest amounts per case file (£9,600 on average versus £2,300 for the opportunistic fraudster).

The negligent fraudster (15%). Policyholders who submit erroneous documents without fraudulent intent: quote from a tradesperson who has ceased activity (struck-off registration), pro forma invoice presented as final, damage photograph taken before the declared claim date. CheckFile detects these inconsistencies in the same way, and the human handler then distinguishes fraud from error.

Speed of detection changes the game

Under manual verification, fraud was detected — when it was detected — during the investigation process, 10 to 15 days after notification. This delay poses two problems: the fraudulent policyholder may have already commenced the work (creating a fait accompli that complicates indemnity refusal), and the handler hesitates to challenge a case file on which they have already invested several hours of work.

With CheckFile, detection occurs within minutes of document submission. The handler receives a documented alert (suspicious zone, anomaly type, confidence score) before even beginning investigation. This timeliness changes the dynamic: the case file is directed to the fraud circuit from the outset, without prior time investment.

ROI extends beyond prevented fraud alone

Regional Insurance Co's return on investment breaks down into four items:

The annual cost of the CheckFile solution for Regional Insurance Co's volume (95,000+ documents) sits under £120,000, yielding an ROI ratio exceeding 25:1.

The alert signals CheckFile detects that humans miss

For claims teams wondering concretely what automated verification adds beyond visual checks, here are the five anomalies most frequently detected by CheckFile at Regional Insurance Co — and that handlers were not catching:

1. Typographic font inconsistency on an invoice (the amount was modified with a slightly different font from the rest of the document).
2. Photo EXIF metadata dating from before the declared claim date, or geolocated to a different address.
3. Invalid or struck-off company registration on a tradesperson quote — the company appears in online directories but has been struck off at Companies House.
4. Invoice duplication between case files — the same document (same hash, same metadata) submitted on two distinct claims several months apart.
5. Inconsistent amount with market rate guides — a plumbing invoice for £5,500 for work that typically costs £650 to £1,200 in the same geographic area.

Frequently Asked Questions

Can CheckFile integrate with an existing claims management system?

Yes. CheckFile integrates via REST API into any management system (Guidewire, Sapiens, Applied Epic, proprietary solutions). Integration at Regional Insurance Co took 4 weeks, including one week of parallel operation to calibrate thresholds. A free 48-hour pilot allows testing with your actual documents.

Does the 3.2% false positive rate not overload claims handlers?

On 15,000 claims and 95,000+ documents per year, 3.2% false positives represent approximately 3,000 alerts per year, or 12 per working day. Each alert is accompanied by a detailed report (suspicious zone, anomaly type, confidence score), enabling the handler to adjudicate in 2 to 3 minutes. This is significantly less than the time devoted to systematic visual review of all 95,000 documents.

How do policyholders react to automated verification?

Verification is transparent to the policyholder. They submit documents in the same way (portal, email, app). The difference is speed: instead of waiting 7 to 10 days for feedback, they receive confirmation or a completion request within hours of submission. At Regional Insurance Co, the complaint rate related to delays dropped from 23% to 8%.

Is CheckFile compliant with the Insurance Act and FCA oversight?

CheckFile is hosted in Europe, GDPR compliant, SOC 2 and ISO 27001 certified. The complete audit trail for each verification (document analysed, checks executed, result, timestamp) meets the traceability obligations of the Insurance Act 2015 and the internal control requirements of Solvency II. The rules engine is configurable to adapt to the specificities of each branch (property, motor, liability, health).

What results can you expect on a smaller or larger portfolio?

Results are proportional to volume. The 4.7% document fraud rate and 94.8% detection recall are platform constants, observed consistently across all 95,000+ claims documents verified in the insurance sector. Delay reduction depends on initial organisation: insurers starting from a longer delay achieve greater gains.

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