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Composable Enterprise

CASE STUDY

Streamlining Insurance Submissions with an AI‑Led Cognitive Underwriter Workbench

Industry

Insurance (Property & Casualty / Reinsurance)

Our Contributions

AI Consulting, Document AI, NLP & Machine Learning, Intelligent Automation (RPA), Decision Intelligence, Office 365 Integration

Location

Europe

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In recent years, the global insurance industry has seen a sharp rise in submission volumes, driven by market volatility, evolving risk profiles, and increasing demand for faster underwriting decisions. For leading insurers, this surge has introduced significant operational challenges, particularly as submissions arrive in highly unstructured formats across emails and multiple document types, complicating review and processing.

To stay competitive, insurers are turning to advanced AI-driven capabilities that leverage real-time data, intelligent document processing, and decision analytics. These technologies enable underwriting teams to streamline submission intake, reduce manual effort, improve decision accuracy, and balance risk effectively, while accelerating turnaround times in an increasingly dynamic insurance landscape.
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The Challenge

The insurer was managing a high volume of policy submission and negotiation emails, nearly 80,000 annually, originating from more than 400 sources. These submissions arrived largely as unstructured content, embedded in email bodies or attached as PDFs, Word, and Excel documents, making it difficult for underwriting teams to review and prioritize requests efficiently.

As a result, underwriters spent significant manual effort interpreting submissions, slowing processing and limiting their ability to respond to all incoming requests quickly and accurately. The lack of automation and structured data extraction limited scalability, delayed decision-making, and constrained the insurer’s ability to handle growing submission volumes effectively.

Our Approach


To address the insurer’s growing submission processing challenges, Coforge began the engagement with focused AI consulting to assess each stage of the policy pre-bind lifecycle and identify where AI and automation could deliver the greatest impact. The approach centered on combining intelligent document processing, decision intelligence, and seamless system integration to accelerate underwriting workflows while maintaining accuracy and control.

AI Consulting & Cognitive Underwriter Workbench

Designed and implemented a Cognitive Underwriter Workbench to streamline submission intake and decision-making. The solution was accelerated using Document AI to efficiently handle high volumes of unstructured submission data.

Document AI & Intelligent Classification

Implemented a classification engine to automatically categorize incoming emails and submissions for further action. Document AI enabled automated extraction and text analytics from emails, PDFs, Word files, Excel documents, and scanned images

NLP & Machine Learning

Applied NLP and machine learning models to interpret unstructured content, contextualize data, and extract relevant underwriting information from third-party sources with high accuracy.

Intelligent Automation & Core System Integration

Integrated the solution with Guidewire using RPA to automatically create and manage submissions. Decision-making for policy submissions enabled us to use rules and machine learning models to support faster, more consistent underwriting outcomes.

Seamless Underwriter Experience

Integrated the workbench with Office 365 to provide underwriters with a familiar, seamless user experience, accelerating adoption and reducing manual effort across submission processing.

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Impact to Date

 

The AI-led Cognitive Underwriter solution significantly improved submission processing efficiency, underwriting accuracy, and scalability, enabling the insurer to handle higher volumes while accelerating decision-making and enterprise adoption.

↑ 3×

Ability to Handle Submissions

↓ 66%

Submission Intake Time

↑ Accuracy Improvement

85% Extraction Accuracy Achieved

Key Outcomes

 

  • Accelerated Submission Processing Automated classification, extraction, and decision support significantly reduced underwriting effort, cutting submission intake time from 3 days to 1 day and enabling faster policy decisions.

  • Improved Accuracy and Decision Quality Achieved up to 85% extraction accuracy through Document AI and NLP models, improving the consistency and reliability of underwriting evaluations.

  • Enhanced Scalability and Throughput Expanded the insurer’s ability to handle 3× higher submission volumes without increasing manual workload, supporting growth in high-volume underwriting scenarios.

  • Enterprise-Wide Adoption Successfully scaled the solution across multiple regions, the UK, Spain, and Singapore, driving broader enterprise adoption and standardization of underwriting workflows.

 

By leveraging AI-driven document intelligence, machine learning, and intelligent automation, Coforge enabled the insurer to transform submission intake into a faster, more accurate, and highly scalable underwriting process, strengthening operational efficiency and supporting enterprise growth.