Insurance claims automation for insurers and TPAs
At a UK general insurer, handlers spent most of their day chasing, reading and keying documents, and little of it on judgement. Reading every document automatically, checking cover against the policy and screening for fraud lets routine claims settle in hours rather than days. Handlers take the exceptions, and the insurers below now catch fraud their old rules missed.
What is insurance claims automation?
Insurance claims automation reads every document that comes in with a claim, checks the claim against the policy wording and benefit rules, screens it for fraud, then settles it, declines it with the reason or passes it to a handler. Clear-cut claims settle with no human step after the claim is reported. The rest reach a handler with the documents parsed, a coverage opinion and a fraud assessment already assembled, so the handler reviews rather than starts from scratch.
- A UK general insurer settles 80% of low-complexity motor claims straight through, with a median time to pay of 24 hours.
- An APAC health insurer auto-adjudicates 74% of its claims, up from 22%, on about 320,000 claims a month.
- At the APAC insurer, hospital claims took 9 days to settle and pharmacy claims 3; the median is now 6 hours.
- An Indian health TPA decides routine cashless pre-authorisations inside the 1-hour window set by the regulator, IRDAI.
Insurance claims, step by step
Sort claims at first notification
When a claim is reported, it is checked against the segment claims leadership agreed to automate. At the UK insurer that means motor claims under a set loss value, with no third-party injury, no coverage ambiguity, no prior-claim flag and no fraud flag: about 58% of motor claims.
Read every claim document
Repair estimates, damage photos, police reports, hospital invoices and correspondence are read on arrival. Standard forms go through a template-aware extractor; free text, letters and photos go through a language model tied to the claims data model. At the UK insurer, DocuMage learned from about 1.4 million past estimates and 240,000 police reports.
Check cover against the policy
Each claim is checked against the policy wording and the endorsements that apply to it. The result is a coverage opinion: what is covered, what is excluded, which excess applies and what happens to the no-claims discount. Where the wording is genuinely ambiguous, the claim goes to a handler with the ambiguity flagged.
Screen for fraud and leakage
Rules catch the known patterns, such as recently started policies or several claims in a short window. An anomaly model looks for subtler ones, including staged collisions and coordinated activity across providers and patients. Suspicious claims go to the fraud team with the reasoning attached, rather than being declined by the system.
Settle, decline or hand over
Claims that clearly meet the policy are settled; at the APAC insurer, claims that clearly fail are declined with the deficiency cited. The rest go to a handler. Outcomes go back to the existing claims system, and each decision is logged with the wording cited, the documents reviewed and the model versions used.
Ambiguous cover, suspected fraud, complex claims and third-party negotiation stay with people. Claims that fall out reach a handler with the documents read, the cover checked and the fraud assessed. At the APAC insurer, handler productivity on those claims improved about 3x. The UK insurer moved the handler time it freed into complex claims and third-party liability negotiation.
Results from 3 deployments
Every figure below comes from the case study it links to.
UK General Insurer
Motor Claims Automation
- 24 hrs median time to pay
APAC Health Insurer
APAC Health Claims
- 74% claims auto-adjudicated
- 320K monthly claim volume
Health TPA, India
AI CoE for a Health TPA
- 12 use cases in the governed pipeline
- 3 in production in the first quarter
The accelerators behind it
Pre-built accelerators do the work, configured to your documents, rules and systems. Delivery took 12 to 28 weeks in the case studies above.
Claims Router →
Routes claims by payer, plan and likelihood-to-pay.
DocuMage →
Flagship IDP — OCR + ICR + LLM for any document type, replaces legacy OCR.
Anomaly Detector →
Detects spend, journal and vendor anomalies in real time.
Multi-Agent Orchestrator →
Coordinates agent teams with planner + critic patterns.
Medical Records Parser →
Extracts structured clinical data from PDFs, faxes and scans.
Document processing ROI calculator
Enter your document volumes, handling times and current straight-through rate to see the three-year return, then email yourself the PDF.
Insurance claims: the questions buyers ask
How fast are claims settled once they're automated?
At a UK general insurer, low-complexity motor claims averaged 18 days from first notification to settlement. The 80% that now go straight through are paid in a median 24 hours, and the 95th percentile is 36 hours. At an APAC health insurer, the median time to a settlement decision is 6 hours, against 9 days for hospital claims before.
Which claims can be automated?
Claims that clearly meet the policy. The UK insurer automated low-complexity motor claims: under a set loss value, with no third-party injury, coverage ambiguity, prior-claim flag or fraud flag, about 58% of its motor volume. The APAC insurer runs hospital, ambulatory and pharmacy claims through one platform, and 74% are now decided automatically, up from 22%.
Does automating claims let more fraud through?
No. At the UK insurer, suspicious claims go to the fraud investigation team with the reasoning attached, rather than being declined by the system. The UK and APAC insurers now catch fraud their old rules missed, such as staged collisions spread across unrelated-looking claims and coordinated patterns across providers, and both fraud teams accept more of the referrals they receive.
Do we have to replace our claims system?
No. The APAC insurer's claims platform could not be replaced, so the automation sits upstream of it, connects through its standard APIs and writes each outcome back for payment release and member and provider notification. At the Indian TPA, the AI layer never writes a decision directly. The UK pipeline ran alongside the existing claims tools for 8 weeks before traffic was switched.
Where does our claims data stay?
Inside each client's own environment. The UK platform runs in the insurer's private cloud in London, inside its UK data-residency boundary. The APAC platform runs on the insurer's local private cloud, and no medical data leaves that infrastructure. The Indian TPA runs everything in its own data centre: no claim document, prompt or model output leaves its network.
How long does a deployment take?
Delivery took 22 weeks at the UK insurer and 28 weeks at the APAC health insurer. The Indian TPA took 12 weeks, with its first 3 use cases in production in the first quarter.
Can every decision be explained to an auditor?
Yes. At the UK insurer, each automated decision is logged with the policy wording cited, the documents reviewed, the model versions used and the decision path. Its compliance team uses that trail for FCA Treating Customers Fairly oversight, and internal audit can query it directly. At the Indian TPA, the model inventory and audit logs passed an insurer client's audit without a finding.
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See it running on your own process
A 20-minute walkthrough with the engineers who build these deployments: your documents, your systems, the accelerators running.