Problem 01
No model-risk evidence
The POC produces no CP24/2-aligned model card and no traceability matrix for second-line risk. Without that evidence, the system never clears review and never reaches production.
Solutions · Insurance
Auto-route 60–70% of claims, FCA-cleared.
An agentic pipeline that classifies, scores, and routes inbound claims, with the per-decision audit trail FCA CP24/2 expects.
Solutions we provide
Six claims workloads, made decisionable.
Every workload ships the same citation-bound audit trail and inline fraud signal. Start with the line of business costing you most.
Why claims automation fails
Four reasons claims-AI POCs stall before production.
Most insurers have run claims-AI POCs; most stalled. The pattern is consistent: the POC clears engineering but fails at second-line risk review.
Compliance is not a model feature. It's the end-to-end claims system.
- 12 min
- Loss-adjuster review per claim under manual triage
- 9/10
- Claims-AI POCs that stall at second-line risk review
- T+1
- Fraud surfaced a day late when scoring sits in a separate tool
The POC cleared engineering and died at second-line risk review.
- Problem 02
Loss-adjusters work in parallel anyway
Even when the model auto-routes, adjusters re-review every decision 'just in case', eroding the entire business case. The AI becomes overhead instead of the leverage it promised.
- Problem 03
Fraud-scoring lives in a different system
Triage classifies the claim while fraud-scoring sits in a separate vendor tool. Suspicious claims slip through the gap because neither system ever sees the other's signal.
- Problem 04
No audit replay capability
When the FCA asks why a claim was routed the way it was, the team can't reconstruct the agent's full reasoning trajectory, and confidence in the whole pipeline collapses.
What changes once it ships
Four things a regulated insurer can take to the board.
Not features: outcomes a head of claims, an SIU lead, or a second-line risk function can defend in the room.
Every routing decision is defensible.
Each classification, score, and routing decision is bound to its inputs and reasoning, and replayable on demand. “Why was this claim routed this way?” has a sub-minute answer, not a forensic project.
- Per-decision audit log + trajectory replay
- CP24/2 model cards generated per release
- FCA-format traceability matrix
- Low-confidence decisions auto-route to a human
Loss-adjusters decide, the pipeline does the lifting.
Adjusters stop re-keying and triaging the obvious. 60–70% of claims auto-route; only complex, fraud-flagged, and material-injury claims reach a specialist, and every override sharpens the next quarter's model.
- 60–70% of claims auto-routed end-to-end
- Co-pilot first, full-automation once override rate < 5%
- Specialists judge exceptions, not data entry
- Overrides feed the quarterly retrain
It holds on the real claims stream.
Motor, home, and SME commercial claims as they actually arrive (paper FNOLs, broker submissions, messy free text), not a cleaned demo subset. The agent matches loss-adjuster decisions on 96–98% of the standard tier against hold-out sets.
- Motor, home & SME commercial coverage
- OCR + document parsing on paper claims
- 96–98% agreement with adjusters on the standard tier
- Integrates with Guidewire, Duck Creek, Sapiens IDIT
It clears the FCA, not just builds.
Regulator evidence is engineering output, not a final-stage scramble. Every build ships CP24/2-aligned model cards, a SAR-bearing decision pathway, and an on-prem sovereign fallback for data that can't leave the estate.
- CP24/2 model cards + traceability matrix per release
- Consumer Duty + vulnerable-customer routing built in
- Separate SAR-bearing evidence pipeline
- On-prem sovereign model fallback
Why BritonOne Technology
Why regulated insurers choose BritonOne Technology
Not features: four reasons a head of claims or second-line risk lead can defend in the room.
FCA-fluent by design
CP24/2 model-risk evidence ships as engineering output, not a late scramble.
Evidence-bound, never a black box
Every routing decision is audit-logged and replayable in under a minute.
FCA-cleared in eleven weeks
A phased path from demo to 2LoD-approved production.
Adjusters judge exceptions, AI does the rest
60–70% of claims auto-route; specialists handle only the complex and suspicious.
How we build
From FNOL to FCA-cleared production.
Five stages, each with a bounded output you can hold us to. The CP24/2 evidence runs in parallel with engineering, never as a final-stage scramble.
- Week 1–3
Discovery & evidence design
We audit the current triage flow, design the CP24/2 evidence harness, lock the agent specification, and get the model-card template signed off by second-line risk, before any code ships.
- Week 4–8
Build the agent
Classify, complexity-score, fraud-score, route, plus the retrieval layer and evaluation harness, with daily hold-out evaluation and prompt-regression detection from day one.
- Continuous
Evidence & hardening
CP24/2 model cards, the FCA-format traceability matrix, per-decision trajectory replay, and pen-test, produced as engineering output alongside the build, not after it.
- Week 9–11
Shadow & clear
Run in shadow against the live FNOL stream for two weeks, clear final 2LoD review, then submit the FCA notification with the parity report attached.
- Week 12+
Production & extend
Phased rollout (10% → 50% → 100%), then extend to commercial claims and SIU fraud triage under quarterly retrain governance.
Success stories
Programmes we have shipped
47%
Insurance
Motor damage assessment from photos for an insurer
Settled 47% of motor claims from images alone, with fraud flags surfaced inline.
PythonPyTorchDetectron2AWS
Country · UK
3x
Insurance
Claims platform rebuild for a general insurer
Replaced a 15-year-old claims system, tripling throughput per handler.
C#.NETAzureSQL ServerReact
Country · UK
38%
Healthcare
Claims and billing analytics for a hospital group
Unified claims and billing data, cutting rejected-claim rework 38% for a hospital group.
SnowflakedbtFHIRPower BI
Country · UK
3.1x
Insurance
Underwriting copilot for a speciality insurer
Drafted first-pass quotes from submission packs 3.1x faster, every clause cited back to the wording it came from.
PythonAzure OpenAILangChainPostgrespgvector
Country · UK
61%
Legal
Clause-level contract drafting for a commercial law firm
Cut first-draft time on regulated commercial contracts by 61%, each clause traceable to firm precedent.
TypeScriptAWS BedrockAnthropicOpenSearchReact
Country · UK
18%
Foodtech
Churn prediction for a foodtech subscription platform
Cut voluntary churn 18% in two quarters with next-best-action scoring for a meal-subscription platform.
PythonXGBoostSnowflakedbtMLflow
Country · UK
22%
Retail
Demand forecasting for a grocery retailer
Cut waste 22% across 900 stores with SKU-level probabilistic forecasts.
PythonPyTorchDatabricksDelta Lake
Country · FR
£14M
Insurance
GenAI opportunity assessment for an insurance group
Mapped a £14M annual benefit pipeline across 40 use cases, sequenced by risk.
StrategyValue modellingRisk assessment
Country · DE
4.8★
Retail
Loyalty and shopping app for a retailer
Launched a retail loyalty app to a 4.8-star rating and 200k users in 90 days.
SwiftKotlinReact NativeAWS
Country · UK
60%
Retail
Lakehouse build for a grocery retailer
Unified 40 sources into a governed lakehouse, cutting report build time 60% for a grocery retailer.
DatabricksDelta LakeSparkTerraform
Country · UK
45%
Automotive
Cloud warehouse migration for a carmaker
Migrated a legacy warehouse to the cloud, cutting query cost 45% for a carmaker.
SnowflakedbtFivetranTerraform
Country · DE
60→1
Insurance
Underwriting analytics dashboards for an insurer
Replaced 60 spreadsheets with one governed underwriting board pack for an insurer.
Power BITabularAzuredbt
Country · UK
3x
Foodtech
Self-service analytics for a foodtech platform
Self-service models tripled analyst throughput at a food-delivery platform.
LookerdbtBigQuery
Country · FR
100%
Insurance
Test automation for an insurance quote platform
Automated quote, coverage, and claims journeys for a US insurer, holding 100% of critical paths green across a fast release train.
SeleniumJavaTestNGJenkins
Country · US
30+ edge cases caught
Fintech
Exploratory and regression testing for a customer-management platform
Exploratory and regression testing across pipelines, analytics, and customer records surfaced more than thirty edge-case defects that scripted suites had missed, hardening a German fintech's CRM before a major rollout.
WebTestRailJiraPostman
Country · DE
p95 latency flat
Fintech
Scalability and endurance testing for an analytics platform
Kept p95 latency flat as audience data and concurrency scaled, proving the analytics dashboards would not slow as customers grew.
k6LocustGrafanaDatadog
Country · US
Who we are
About usBritonOne Technology is a full-cycle engineering company that builds and operates production software for regulated estates. Since 2017, we have shipped programmes that clear audit on the first pass across banking, insurance, wealth, healthcare, and biotech. Our teams pair deep domain knowledge with disciplined engineering, treating compliance, security, and resilience as first-class deliverables. From architecture through to live operations, we stay accountable for the systems we build, measuring success by uptime, audit outcomes, and defensible business results.
60+Senior engineers across UK and EU
Why choose us
Engineer experience, average9+ yrs
Specialist replacement window48h
Code and IP ownership, day one100%
Surprise invoicesZero
What claims-automation clients say
Words from the regulated teams we shipped with.
Anonymised under MNDA, verifiable on reference call. Each quote is from a senior owner who carried the engagement through second-line review.
The FCA meeting was almost boring
“Three previous internal AI projects had failed at second-line risk review. BritonOne Technology shipped the FCA-cleared agentic pipeline in eleven weeks. Twelve months later, 68% of motor claims auto-route end-to-end and we have taken £4.2M of loss-adjuster cost out of the run-rate. The most surprising thing: the FCA supervisory meeting was almost boring.”
Director of ClaimsTop-5 UK motor insurer
Common questions about claims automation
What heads of claims and 2LoD ask before approving a build.
