What challenges did EXL face before AI implementation?

Manual, time-consuming underwriting processes requiring days to review and assess documents. High costs and risks of inaccuracies in underwriting evaluations. Need for faster customer onboarding and competitive digital transformation.

What was the impact of the AI solution?

Reduced underwriting process time from days to hours. Achieved up to 80% reduction in underwriting costs. Enabled faster customer onboarding and competitive advantage in the insurance market. Launched within 60 days and optimized costs with pay-for-usage model.

Source

ExpandedEvidence: Medium50/100

EXL Transforms Insurance Underwriting with Generative AI Assistant Built on Amazon Bedrock

Use case typeDocument automationUpdated Jun 13, 2026

EXL, a data analytics and digital solutions provider, sought to reduce manual effort, time, and cost in insurance underwriting processes. They developed a generative AI virtual assistant integrated into their Life Digital Suite platform, utilizing multiple foundation models on Amazon Bedrock. The solution incorporated Amazon Textract and Amazon Comprehend for data extraction and PII redaction to maintain data privacy and regulatory compliance.

Organization: EXL
Industry: Insurance
Location: India
Published: August 2024

Reported outcomes

−80%

costCost savings

60 dayscost

Strategic outcomes

New product / capabilityBuilt generative AI underwriting assistantRisk & complianceAdded PII redaction and compliance supportCustomer experience & trustEnabled faster customer onboardingNew business modelAdopted pay-for-usage pricing model

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Cost: 80% decrease

EXL WebsiteAug 1, 2024Case studyInferred claimMedium evidence strength

Achieved up to 80% reduction in underwriting costs.

Normalized claim

Cost: 60 days

EXL WebsiteAug 1, 2024Case studyInferred claimMedium evidence strength

Launched within 60 days and optimized costs with pay-for-usage model.

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: EXL
Provider: AWS
Maturity: Unknown
Linked source: EXL Website

No explicit deployment-stage evidence found.

Customer identity supportedSource describes one deploymentMaturity evidence evaluated

Primary read

Use case focus

Showing 3 of 3

1Document Processing
2Underwriting Automation
3Generative AI Virtual Assistant

Manual, time-consuming underwriting processes requiring days to review and assess documents.
High costs and risks of inaccuracies in underwriting evaluations.
Need for faster customer onboarding and competitive digital transformation.

Built a generative AI-based virtual assistant for underwriting using Amazon Bedrock's large language models.
Integrated document processing automation using Amazon Textract for data extraction and Amazon Comprehend for text analysis and PII redaction.
Developed a retrieval-augmented generation chatbot to streamline assessment and review stages within the LDS platform suite.

Technologies

Amazon Bedrock Amazon Textract Amazon Comprehend

Reduced underwriting process time from days to hours.
Achieved up to 80% reduction in underwriting costs.
Enabled faster customer onboarding and competitive advantage in the insurance market.
Launched within 60 days and optimized costs with pay-for-usage model.

Sources & evidence1

Evidence: Medium50/100Evidence strength