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  1. LTIMindtree is now LTM | It’s time to Outcreate
  2. Insights
  3. Enhancing the customer experience by modernizing a leading North American bank's contact center

Elevated Customer Experience: Frictionless Claim Processing Through Data Platform Modernization

Jun 01, 2025

  • Client
  • Market Trends
  • Need for Change
  • Solution
  • Business Benefits
  • Conclusion
  • Client
  • Market Trends
  • Need for Change
  • Solution
  • Business Benefits
  • Conclusion

Client

The client is an American insurance company and the second-largest commercial property casualty insurance writer in the U.S. It operates in the business and personal insurance and surety bond segment through independent agents, ensuring comprehensive risk coverage for customers.

Market Trends

The insurance industry is under pressure to move beyond traditional processing models and deliver hyper-efficient, customer-centric experiences. With increasing claims volume, complex regulatory needs, and rising fraud risks, insurers are turning to modern data platform modernization, real-time analytics, and intelligent automation to stay ahead. Cloud-native architecture and FinOps-driven efficiency have become critical enablers of this shift.

Yet for many insurers, especially those managing extensive portfolios and operations, legacy systems remain a major roadblock. Outdated infrastructure limits agility, drives up costs, and hampers access to timely insights. These systemic challenges make it difficult to accelerate claims processing, deploy fraud detection using AI, or personalize services—ultimately affecting customer satisfaction and business outcomes.

Need For Change

Like many large insurers navigating today’s evolving market, the client recognized the need for data platform modernization to stay competitive and meet rising customer expectations. Legacy systems were no longer sufficient to support fast, data-driven decisions or cost-effective operations. Key challenges included:

  • Scalability and latency issues: The existing platform struggled to handle peak load volumes, leading to claim processing delays and inconsistent user experiences.
  • Technical debt and high costs: Maintaining legacy systems incurred high operational expenses and slowed the rollout of new features and process improvements.
  • Limited analytics and insights: The lack of real-time analytics restricted the company’s ability to optimize claim settlements and fraud detection.

Solution

LTM partnered with the client to reimagine their claims data ecosystem with future-ready architecture. The engagement involved a strategic shifting of data gravity to a centralized Snowflake-based platform, tailored for scalability, performance, and cost optimization.

  • Scalable, High-performance Data Architecture - Designed and implemented a centralized Snowflake platform to overcome performance bottlenecks and support high-volume data ingestion.
  • Business Value-led Delivery - Delivered the project in three waves, each designed to drive incremental business value.
  • Advanced Security and Compliance - Integrated enterprise-grade encryption and role-based access to align with regulatory mandates and safeguard sensitive claims data.
  • Accelerated Migration with LTM PolarSled - Leveraged LTM’s Snowflake modernization accelerator, PolarSled, to automate discovery, code conversion, and data validation—minimizing manual effort.
  • Seamless Adoption with Touch-based Transition Framework - Rolled out a buddy-assisted transition model, making it easier for users to adopt the new system with minimal disruption.

Business Benefits

  • Manual effort for code conversion and data validation was cut nearly 50%, thanks to automation, improving speed and accuracy.
  • Migration-related expenditures were reduced by 25%, through strategic modernization and cost-control measures.
  • Claims processing efficiency increased by 20%, as the centralized platform enabled fast, analytics-powered decisions.
  • Reduced technical debt significantly improved time-to-market for new features and platform enhancements.
  • Enhanced data protection and regulatory compliance through enterprise-grade security measures.

Conclusion

By embracing data platform modernization, the client transformed its claims operation into a high-performing, insight-driven function. The touch-based adoption framework and advanced automation provide a future-ready foundation for AI-driven claims assessment, predictive analytics, and fraud detection using AI, reinforcing the client’s commitment to customer-centric, frictionless insurance services.

Ready to modernize your data platform?

Let’s build scalable, cloud-native solutions that power real-time insights and fraud detection using AI.

Explore more or contact us at data.analytics@ltm.com.

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Case Study
calendar June 3, 2024
Modernize Your Workloads on Snowflake with PolarSled
David Althoff
Chief Business Officer, Insurance

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