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Industry: Insurance

Software development for insurance

Engineering for carriers, MGAs, brokers, and insurtech startups. AI claims pipelines that auto triage 85% of volume. Underwriting platforms with rate engines that finance can audit. Policy administration that replaces a fragile mainframe instead of layering on top of it. Broker portals that handle quote and bind, MTAs, and FNOL without a phone call. IRDAI aware in India, FCA aware in the UK, NAIC aware in the US.

Industry challenges we solve

Insurance is process heavy and document heavy. Most of the engineering pain comes from systems built before the web, paperwork that still arrives as a PDF, and regulatory frameworks that punish ambiguous data more than slow data.

Claims handlers retyping the same fields. A loss notification arrives as a PDF, the handler types the policy number, the date of loss, and the claim value into the policy admin system by hand. Three thousand claims a month, a five day backlog, and accuracy that drifts at the end of every shift.
Underwriting on spreadsheets. A pricing model lives in an Excel workbook on one underwriter's laptop. The version control is the file name. A regulatory inspector asks how the rate was derived and the answer is a screenshot.
Brokers waiting on email quotes. A commercial enquiry sits in an inbox for two days because it needs three carrier quotes and nobody remembered to email the third. The deal goes to a competitor that quoted in 20 minutes.
Policy admin systems built in 1998. Green screen terminals, COBOL on the back end, batch jobs that run overnight. Adding a new product takes nine months, and every front end change waits on the same release window.
Fraud detection by gut feel. A senior handler "knows" when a claim looks wrong. The rules engine is six unmaintained Drools files. False positives are 40%, the operations team is buried in investigations, and actual fraud rings ship through under the radar.
Regulatory evidence that lives in tickets. The FCA, IRDAI, or state insurance commissioner asks for the audit trail of a control. The team finds it eventually, in three Confluence pages, two ZIP files, and one Slack thread. Audit fatigue grows and confidence in compliance shrinks.
Capabilities

Our insurance capabilities

📄

AI claims processing

AWS Textract or Azure Document Intelligence for OCR, GPT-4 or Claude for structured extraction, validation against policy and customer systems of record, and confidence based routing into auto pay, fast review, or escalation lanes. 85% auto triage achievable on standardised loss types.

📊

Underwriting platforms

Rate engines with versioned product definitions, scenario testing against historical books, embedded data enrichment (motor vehicle history, property risk, business credit), and a workflow that an actuary can audit without asking engineering for an explanation.

🗂️

Policy administration systems

New PAS builds and integrations with Guidewire, Duck Creek, Sapiens, INSIS, INSTANDA, Acturis, and Open GI. Event sourced cores where the audit story justifies it, configurable workflow engines for endorsements and renewals, and document generation aligned to your jurisdiction.

🤝

Broker & agent portals

Quote and bind, MTAs, renewals, claims FNOL, commission statements, and document downloads. Panel comparison flows for MGAs, SDK style embeds for partners, and Lloyd's market PPL patterns for London Market product lines.

🛡️

Fraud detection ML

Gradient boosted models on engineered features (claim velocity, network analysis, anomalies against the policyholder's history), shadow scoring before production, holdout precision and recall measurement, and an explainability layer so handlers can defend the decision in court.

📈

Customer & partner reporting

Self serve dashboards for policyholders, brokers, and carrier partners. Bordereaux generation for MGAs, regulatory return preparation, IFRS 17 contract grouping, and tax exports aligned to HMRC, IRS, or IRDAI formats.

Compliance & regulatory considerations

Insurance is one of the most regulated industries we work in. The frameworks differ by jurisdiction, but the engineering controls (audit trails, role based access, data residency, retention, incident response) overlap heavily.

IRDAI awareness (India) FCA Handbook (UK) NAIC awareness (US) Solvency II awareness GDPR & UK GDPR PCI DSS for premiums Lloyd's market readiness UAE Insurance Authority awareness

India is increasingly the most prescriptive market on the technology side. The IRDAI Information and Cyber Security Guidelines mandate specific controls including periodic VAPT, board reporting on cyber incidents, and data residency for policyholder data within India. We design AWS, Azure, or GCP deployments in Mumbai or Hyderabad regions, with role based access, MFA on every console, and the immutable audit logs IRDAI inspections expect. The Bima Sugam digital insurance distribution framework opens new integration paths; we are tracking the protocol as it stabilises.

UK insurance technology sits inside the FCA's product oversight and operational resilience expectations. We are not a regulatory consultancy and we will not pretend to be one. We are engineering aware of ICOBS for general insurance conduct, the Consumer Duty for retail products, SYSC operational resilience, SUP 15 incident reporting, and the operational resilience policy statement (PS21/3) on impact tolerances. For appointed representatives we coordinate with the principal firm's compliance team rather than replacing them. Solvency II reporting touches the data architecture for European carriers; we model contracts and exposures so the QRT extracts come out clean.

US carriers face state by state regulation under the NAIC framework. We design rate filings, policy form versioning, and consumer disclosures with the patchwork of state insurance commissioner requirements in mind. Where you operate in California, the CCPA / CPRA layers consumer privacy obligations on top, and the New York DFS Cybersecurity Regulation (23 NYCRR 500) drives technology controls similar to the IRDAI guidelines. We deliver the technology evidence base; your compliance team owns the regulatory relationship.

Tech stack we use for insurance

Strongly typed, auditable, and predictable. Event sourced cores where the audit story justifies it. Document AI where humans were retyping. Gradient boosted models for fraud and risk where the data supports them.

Node.js 20 + TypeScript Java 21 + Spring Boot React 18 + Next.js React Native + Expo PostgreSQL 16 + event sourcing Kafka + Temporal workflows AWS Textract + Azure Document Intelligence OpenAI GPT-4 + Anthropic Claude Python + XGBoost / LightGBM Guidewire / Duck Creek / Sapiens DocuSign / HelloSign Datadog + immutable audit logs
Insurance / AI Document Processing UK insurance broker · 12 weeks · 4 engineers

AI document processing for an insurance broker handling 3,000 monthly claims

A UK insurance broker received three thousand monthly claims as a mix of PDFs, scans, and email attachments. Handlers retyped policy numbers, claim values, and clinical or repair codes by hand, with a five day average processing time and accuracy that drifted at the end of every shift. We paired AWS Textract for OCR with GPT-4 structured outputs for field extraction, validated each field against the policy API and customer record, and added a rules plus ML triage lane that routed claims by confidence: high confidence auto progressed, medium went to a fast review queue, low escalated to senior handlers with the original document highlighted. Eighty five percent of claims now clear in under four hours, extraction accuracy holds at 96%, and the operations team has reclaimed three FTEs of capacity for the work that actually needs human judgement.

85%Claims auto triaged
4 hrsAvg processing (was 5 days)
96%Extraction accuracy
12 wksConcept to production

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FAQ

Common questions

Yes. Our standard architecture pairs AWS Textract or Azure Document Intelligence for OCR with GPT-4 or Claude for structured extraction, validates each field against your policy and customer system of record, and routes by confidence score: high confidence claims auto progress, medium confidence go to a fast review lane, low confidence escalate to a senior handler with the original document highlighted. We have shipped this for a UK insurance broker handling 3,000 monthly claims, taking average processing from 5 days to under 4 hours and auto triaging 85% of volume.
Yes. We are engineering aware of the IRDAI (Insurance Regulatory and Development Authority of India) framework: the IRDAI (Maintenance of Insurance Records) Regulations 2015 for record retention, the IRDAI Information and Cyber Security Guidelines for technology controls, the Bima Sugam framework for digital insurance distribution, and the e-insurance account requirements. We are not a regulatory consultancy and we will not pretend to be one. We deliver the immutable audit logs, role based access, and data residency in India that IRDAI inspections expect, and we coordinate with your compliance officer during build.
We design around the FCA Handbook clauses that drive software: ICOBS for general insurance conduct, the Consumer Duty for retail products, SYSC operational resilience, SUP 15 incident reporting, and the FCA's product oversight and governance requirements. For appointed representatives we coordinate with the principal firm's compliance team rather than replacing them. We deliver the audit trails, immutable logs, and incident playbooks your compliance team will be asked to produce, plus the technology evidence base that increasingly drives FCA technology and operational resilience reviews.
Both. We have integrated with Guidewire PolicyCenter, Duck Creek, Sapiens, INSIS, INSTANDA, Acturis, Open GI, and bespoke legacy mainframes via flat file, MQ, or REST. Where the existing PAS is the bottleneck, we build new policy administration on a modern stack (Node.js or Java with PostgreSQL, event sourced where the audit story justifies it) with versioned product definitions, rate engines, document generation, and a configurable workflow engine for endorsements, renewals, and cancellations.
Yes. Broker portals on web and React Native cover quote and bind, MTAs (mid term adjustments), renewals, claims FNOL, commission statements, and document downloads. Quote engines integrate with rate APIs from carriers, panel comparison flows for MGAs, and SDK style embeds for partners. We design for the Lloyd's market where applicable, including PPL (Placing Platform Limited) integration patterns and the bespoke broker workflows that London Market product lines require.
A focused claims AI pipeline (document ingestion, structured extraction, validation, confidence based routing, handler review console) typically ships in 10 to 12 weeks with a 4 person team. A broker portal with quote and bind, MTAs, and claims FNOL takes 12 to 16 weeks. Policy administration replacements are 6 to 12 month programmes depending on product complexity. AI agents handle scaffolding and tests; senior engineers own the rate engines, the integration boundaries with carriers, and the regulatory evidence base.
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