Deploying GenAI Across the Claims Lifecycle: How a Specialty Insurer Cut Settlement Time in Half

Overview

A specialty insurer operating in the Lloyd's of London market handled complex, high-value claims across marine, aviation, and property lines. Unlike personal lines insurance where claims are relatively standardized, specialty claims are inherently complex - each one unique, each one requiring significant expert judgment, and each one generating substantial documentation.

The insurer's claims team - 140 experienced adjusters and specialists - was spending an estimated 35% of their working time on tasks that required their expertise to initiate but not to complete: drafting coverage position letters, generating reserve justification memos, producing settlement summaries, and populating bordereaux reports for reinsurance partners.

This wasn't a process efficiency problem in the traditional sense. The people were working hard and the process was well-designed. The problem was that 35% of the capacity of 140 specialist claims professionals was being consumed by document generation - work that GenAI could do in seconds.

Codeless IQ was engaged to embed GenAI capabilities into the insurer's existing Pega BPM platform, targeting the document generation and knowledge retrieval tasks that were consuming the most specialist time without adding the most specialist value.

Our Solution

Codeless IQ deployed Pega GenAI capabilities across four targeted use cases within the existing Pega claims platform, each chosen for maximum impact on specialist time recovery and each designed with human review as a core workflow step rather than an afterthought.

Use Case 1 - GenAI Coverage Position Letters: When a claim reached the coverage assessment stage, Pega GenAI automatically drafted a coverage position letter by combining the claim facts from the case file, the relevant policy wording sections, and the adjuster's coverage notes. The draft was presented to the adjuster in a side-by-side view showing the generated letter alongside the source material used to generate it - enabling fast, confident review. Average drafting time reduced from 45 minutes to 4 minutes.

Use Case 2 - AI-Powered Reserve Justification Memos: Reserve setting is one of the most judgment-intensive tasks in specialty claims. Pega GenAI was configured to generate a structured reserve justification memo drawing on comparable settled claims from the insurer's historical data, current claim facts, and relevant market intelligence. The memo gave adjusters a data-grounded starting point for their reserve recommendation, reducing the time spent on memo preparation from an average of 90 minutes to 12 minutes while improving the consistency of reserve documentation across the team.

Use Case 3 - Pega Knowledge Buddy for Claims Protocols: The insurer's claims handling protocols, coverage guidelines, and escalation procedures existed in a library of over 400 documents. Finding the right guidance for an unusual claim scenario could take an experienced adjuster 20-30 minutes of searching. Pega's Knowledge Buddy - a GenAI-powered conversational search tool - was integrated into the claims workspace, allowing adjusters to ask natural language questions and receive instant, source-cited answers from the protocol library. Average knowledge retrieval time reduced from 24 minutes to under 2 minutes.

Use Case 4 - Automated Bordereaux Generation: Bordereaux - the detailed claims reports submitted to reinsurance partners - were previously generated manually by a dedicated team of two analysts spending approximately 60% of their time on data compilation and formatting. Pega GenAI automated the extraction, formatting, and narrative generation for monthly bordereaux across all reinsurance treaties, reducing production time from 3 days to 4 hours and eliminating a category of error that had previously required periodic restatements.