Global specialty insurer
IDP + AI underwriting copilots cut commercial property submission turnaround from 9 days to 2.8 days.
What was getting in the way.
A global specialty insurer writing USD 4.2 billion in GWP across commercial property, marine, and professional lines was losing submissions to faster competitors. A 9-day average turnaround on complex accounts was becoming untenable as brokers gravitated to markets that could quote in 48 hours.
Underwriters were spending 60% of their day extracting data from broker submissions — PDFs, spreadsheets, CAD surveys — rather than pricing risk. Eleven systems of record created rekeying risk; placement slip errors ran 4.1%. Broker satisfaction NPS had fallen to 41.
What we deployed.
Gennexa implemented an IDP pipeline that ingested broker submissions in any format — PDF, ACORD XML, or email attachments — and structured them into the insurer's risk data model within minutes of receipt.
An AI underwriting copilot pre-populated the risk assessment template, flagged any line items that deviated from the current appetite, and suggested the five most comparable reference accounts from the live portfolio — reducing each submission to a review-and-price interaction rather than a data-extraction exercise.
A workflow orchestration layer routed each submission to the appropriate underwriting team based on line of business, aggregate value, and a complexity score, with SLA counters visible to both underwriters and broker relationship managers in a shared dashboard.
What we measured.
Average submission turnaround fell from 9 days to 2.8 days — a 3.2× improvement. Underwriter time spent on data extraction dropped from 60% to 14% of the working day.
Placement slip errors fell from 4.1% to 0.6%. Broker NPS recovered from 41 to 67 within two renewal cycles as teams noticed the speed difference. The insurer processed 38% more new business submissions in the same quarter without any increase in headcount. Loss ratio impact analysis showed a 2.4-point improvement attributed to more consistent risk selection.
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