Insurance Software Development

Risk rules engine that encodes your underwriting appetite in configurable business rules, not hardcoded logic that requires a developer to change when appetite shifts. Bureau data integration: ISO, LexisNexis, Verisk, CoreLogic, and credit data sources pulled automatically at quote and written to the risk record with source and timestamp. Decisioning with full audit trail: for every automated bind, decline, or referral, the system records which rules fired, which data inputs triggered them, and what the output was, readable by your compliance team and regulable by an examiner. Referral workflow for submissions outside automated appetite: structured referral queue with the risk data pre-organised so the underwriter reviews a complete risk picture, not a raw submission. Real-time rate calculation from your filed rates and bureau data, with rate change history tracked for regulatory rate filing reconciliation. Output: faster decisions on in-appetite submissions, consistent referral handling on edge cases, and a defensible audit record for every automated decision.

First notice of loss intake across all channels: web forms, phone transcripts via speech-to-text, emailed loss notices, and mobile FNOL apps, normalised into a single structured claim record regardless of intake channel. Coverage validation at intake: reported loss date checked against policy effective and expiration, reported peril checked against covered causes of loss, reported location checked against insured property, with coverage questions flagged before the claim opens. Reserve calculation logic from your reserve guidelines, triggered at FNOL with automatic reserve setting for straightforward loss types and structured referral for complex losses requiring adjuster review. Adjuster assignment routing by line of business, geographic territory, workload, and complexity tier. Settlement automation for fast-track claims meeting defined eligibility criteria: payment authorisation generated and issued without adjuster intervention for low-value, clear-liability claims. Fraud detection scoring from historical claim patterns, routing high-risk claims to SIU with contributing factors surfaced. Compliance deadline tracking per jurisdiction: acknowledgement deadlines, investigation deadlines, and payment deadlines monitored automatically with escalation before breach. See also: AI for insurance and insurance automation.

Product configurator: define coverage structures, rating factors, endorsements, and exclusions in a configuration layer, not in application code, so your product team can launch new products and modify existing ones without a development cycle. Quote-bind-issue workflow: from applicant data entry through rating, eligibility checking, payment processing, and policy issuance, with each step logged and the issued policy document generated automatically from your template library. Endorsements: mid-term coverage changes processed against the existing policy record, with pro-rata premium adjustment calculated and recorded. Renewals: automated renewal quote generation at configured advance notice intervals, with renewal offers sent to policyholders and renewal processing triggered on acceptance. Mid-term adjustments (MTA): address changes, vehicle swaps, driver additions, and coverage changes processed with premium recalculation and updated policy documents generated. Cancellation and reinstatement: reason-coded cancellations, non-pay lapse handling, and reinstatement processing with back-to-date coverage reinstatement calculation. The platform is designed for configurability over custom code: your operations team changes product rules, your development team builds integrations.

Extraction and validation pipelines for the document types insurance operations generate at scale. Policy documents: coverage terms, exclusions, and endorsement data extracted from issued policies and compared against the policy administration record for consistency, flagging discrepancies before they become coverage disputes. Claims evidence: loss notices, repair estimates, medical records, police reports, and adjuster photographs processed through vision models (GPT-4o with vision, Azure Document Intelligence) with structured data extracted and written to the claims record. Medical reports and Explanation of Benefits: ICD codes, procedure codes, provider information, treatment dates, and billed amounts extracted from medical billing documents and EOBs for workers' compensation and health lines. Extraction confidence scoring on every field: high-confidence extractions populate your system directly, low-confidence extractions route to a review queue showing the source text alongside the extracted value so reviewers correct in seconds rather than re-reading the document. Volume: the pipeline processes thousands of documents per day without manual triage. See also: intelligent document processing.

Compliance built into the software architecture rather than added as an audit layer after the fact. Solvency II (EU): SCR calculation data feeds structured for Pillar 1 quantitative reporting, Pillar 2 governance documentation framework, and Pillar 3 public and supervisory disclosure templates. FCA Consumer Duty (UK): consumer outcome monitoring dashboards tracking price and value, products and services, consumer understanding, and consumer support metrics with the evidence trail required for annual Board attestation. NAIC model laws (US): prompt payment compliance tracking by state and line of business, denial letter content validation against state requirements before sending, and documentation requirements per line tracked against claim records. Automated underwriting and claims decisions: every automated decision generates a plain-language explanation of the factors that drove the outcome, stored in the decision record for regulatory examination. Audit trail export: for regulatory examinations, the compliance audit trail compresses to a regulator-ready report from the claims and policy handling records without manual compilation. See also: AI governance and compliance automation.

Integration layer between custom-built AI and automation components and your existing Guidewire ClaimCenter, PolicyCenter, or BillingCenter, or Duck Creek Claims, Policy, or Billing platforms. Use case: you've invested in a core platform but need AI-powered document extraction, fraud scoring, or compliance monitoring that the platform doesn't provide out of the box. The integration approach: API-first connections to your platform's REST or SOAP endpoints for reading policy and claim data, writing extracted fields, and triggering platform workflows from external events. Event-driven architecture where the AI component subscribes to platform events (new claim filed, FNOL received, document uploaded) and pushes results back to the platform record. Field mapping documented and tested against your platform configuration rather than against a generic schema, because every Guidewire or Duck Creek implementation is customised. Data synchronisation for high-volume batch scenarios where real-time API calls are impractical. We've built both Guidewire and Duck Creek integrations for clients who needed AI capabilities their platform couldn't deliver natively, without replacing the platform investment they'd already made.