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Josh Gazes, Senior Vice President – Operations

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Jess Johnson, Head of Operational Excellence

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Mitch Blaser, Co-CEO

Mosaic Insurance

Krishnan Ethirajan, COO

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Jason Hendrey, Senior Director, Global Customer Services

WS Audiology (WSA)

Christof Steube, Director of Finance Excellence

Kiwi.com

Leonard McCullie, Director, Vendor Management

Kiwi.com

Petra Reiter, Vice President, Customer Services

Flight Centre

Aaron Fadelli, Business Leader

Healius Pathology

Alex Cook, Head of Finance Operations

Varo Bank

Breanna Rivers, Partner Performance Manager

Yorkshire Building Society Group (YBS)

Jessica Lockwood, Process Automation Manager

WS Audiology (WSA)

Sharang Patil, Director of Group Finance Excellence

Priya Madan Mohan, VP for Group Accounting & Controlling

United Airlines

Chris Kenny, VP and Controller

GFG Alliance

Phillip Irish, General Manager, Shared Services Delivery, Quality & Governance

Energy Australia

Steve Corden, Outsource Operations Leader

Delaware North

Christopher Lozipone, Senior Vice President and Global Business Services Head

Moneycorp

Nick Haslehurst, Chief Financial & Operating Officer

Prodigy Finance

Nico Barnard, Head of Operations

M&T Bank

Chris Tolomeo, Senior VP & Head of Banking Services

Minerals Technologies Inc. (MTI)

Khem Balkaran, CIO

Church's Chicken

Louis J. Profumo, CFO & EVP

From Documents to Decisions: AI & Automation Accelerate Commercial Underwriting

Read | Jun 08, 2026

AUTHOR(s)

A WNS Perspective

Key Points

  • Faced with mounting volumes of document-heavy New Business submissions, a global insurer’s commercial underwriting teams were spending valuable time navigating fragmented intake processes, manual data capture and workflow bottlenecks, making it difficult to consistently meet turnaround and SLA expectations.
  • WNS combined process re-design with AI-led document processing and intelligent automation to transform unstructured submission data into underwriting-ready information, simplifying intake, improving data quality and helping underwriters focus on higher-value decision-making.
  • The result was a faster, more scalable underwriting operation that significantly accelerated submission-to-quote turnaround, enabled greater straight-through processing and established a strong data foundation for future underwriting automation and AI-driven decision support.

The Industry Landscape
Unlocking Speed and Scale in Commercial Underwriting

Property and Casualty (P&C) insurers face persistent friction in commercial underwriting. Manual document intake, disconnected tools and data silos slow down the submission process and quote generation, increasing lead time and underwriting expenses. These issues are especially prominent in carriers created through acquisitions, where federated entities operate on distinct systems and workflows.

As insurers seek to accelerate submission-to-quote turnaround and improve broker satisfaction, the strategic focus shifts away from replacing legacy systems to enabling data-first automation layers that streamline intake, triage and routing.

The Client Challenge
Document-heavy New Business Submissions | Fragmented Workflows

The client operated a complex, multi-entity underwriting environment spanning commercial and specialty lines. As New Business submission volumes surged, underwriters struggled to process document-intensive applications while consistently meeting speed, accuracy and Service-level Agreement (SLA) requirements.

Key challenges included:

Why Debt Behaves Differently Infographic
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With increasing underwriting workload and the growing demand for digital-first service, the client prioritized a scalable automation layer to standardize and accelerate submission intake, minimize manual document processing and re-keying, and relieve workflow bottlenecks, without a disruptive overhaul of core systems of record.

The Solution
Business Process Re-engineering | AI-led Intake Orchestration | SLA-driven Automation

WNS delivered a consultative, digital transformation program, combining strategic advisory, intelligent automation and AI-led intake. The engagement was anchored on two core pillars:

Consulting

1. Consulting-led Process Re-design and Transformation

Utilizing our proprietary ADAPT framework, WNS systematically mapped the end-to-end New Business process and developed a comprehensive transformation roadmap that:

  • Evaluated New Business submission intake effectiveness across entry channels by assessing data completeness, document variability and upfront triage, identifying first‑touch breakdowns slowing underwriting decisions.
  • Identified high‑impact digitization, automation and orchestration opportunities to remove manual submission handling, improve underwriting decision quality at intake and enable a scalable New Business underwriting model.

The strategic assessment helped re‑imagine the end‑to‑end New Business underwriting model by positioning data digitization as the core enabler, complemented by targeted business process re-engineering and AI‑led intake.

AI

2. AI-powered Document Intake with Hyperscience

To modernize New Business workflows, WNS deployed Hyperscience, an AI / ML-led document processing platform, as the document-to-data platform:

  • Reviewed 150 products, including their application forms and supporting documents, to assess template variations.
  • Assessed various fields within application forms, such as handwritten entries, checkboxes, signature spaces, multiline and free-form text, SSN, dates and alphanumeric data, to evaluate the complexity involved in extracting information.
  • Completed a Proof of Concept (POC) for high-volume, top-tier products to validate data extraction accuracy and performance with Hyperscience.
  • Developed ~1,605 variants of application forms, including structured, semi-structured and handwritten formats, as well as e-mail-based submissions.
  • Ingested, classified And auto-split submission packets, including ACORD forms, supplemental forms, loss runs and schedules.
  • Enabled human-in-the-loop exception handling for low-confidence fields, ensuring control and auditability.
  • Applied SLA-targeted automation, dynamically balancing speed and accuracy based on field-level thresholds.
  • Integrated structured, validated data via application programming interfaces directly into Salesforce and downstream operational systems, preserving existing systems of record.

This enabled STP for clean submissions and exception routing for low-confidence fields.

Why Debt Behaves Differently Infographic
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The Outcome
Useable Data | Faster Quotes | | Future-ready Commercial Underwriting

The transformation delivered measurable impact across underwriting operations and positioned the client for long-term digital success.

Key outcomes included:

Why Debt Behaves Differently Infographic
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FAQs

1. Why are commercial insurers modernizing underwriting operations?

Commercial insurers are facing rising submission volumes, manual workflows, fragmented systems, and increasing pressure to improve underwriting speed and broker responsiveness

2. What is intelligent document processing in underwriting?

Intelligent document processing uses AI, OCR, and ML technologies to extract, classify, validate, and process underwriting submission data automatically.

3. How does AI improve commercial underwriting operations?

AI helps automate submission intake, document classification, data extraction, workflow routing, exception handling, and underwriting decision support.

4. What is straight-through processing (STP) in underwriting?

STP enables underwriting submissions to move automatically through intake and processing workflows with minimal manual intervention.

5. How does AI-led intake orchestration improve underwriting speed?

AI-led intake orchestration automates submission triage, contextual classification, data extraction, and workflow routing, reducing handling time and improving SLA adherence.

6. What business outcomes can insurers expect from underwriting automation?

  • Faster submission turnaround
  • Improved SLA performance
  • Higher underwriting efficiency
  • Better broker experience
  • Improved data accuracy

7. Why is Human-in-the-Loop validation important in underwriting automation?

Human validation helps manage low-confidence extraction fields and exception handling while maintaining auditability and underwriting control.

8. Who should prioritize AI-led underwriting transformation?

  • Commercial underwriting leaders
  • Insurance COOs
  • CIOs and transformation leaders
  • Operations executives
  • Digital underwriting teams