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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 Outdated infrastructure limits agility, drives up costs, and hampers access to timely insights.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
LTIMindtree 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.
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Scalable, High-performance Data Architecture
Designed and implemented a centralized Snowflake platform to overcome performance bottlenecks and support high-volume data ingestion.
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Business Value-led Delivery
Delivered the project in three waves, each designed to drive incremental business value.
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Advanced Security and Compliance
Integrated enterprise-grade encryption and role-based access to align with regulatory mandates and safeguard sensitive claims data.
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Accelerated Migration with LTIMindtree PolarSled
Leveraged LTIMindtree’s Snowflake modernization accelerator, PolarSled, to automate discovery, code conversion, and data validation—minimizing manual effort.
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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.
“Our partnership with one of the largest commercial property and casualty insurers in the U.S. reflects our shared vision for a data-driven, customer-first future. By modernizing their claims data platform, we’ve laid the groundwork for faster, smarter, and more seamless claim experiences for their policyholders. Together, we’ve built a foundation that drives operational excellence and elevates every customer interaction.”
— Prashanth Pulgal, Associate Vice President, Data & Analytics, LTIMindtree
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.
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