Outcreating Database Resilience in Insurance with 30% Lower TCO with AWS

About the Client

The client is a leading multinational insurer with operations across diverse markets and a complex application landscape. Its data estate included multiple Oracle and MongoDB databases that supported mission-critical business functions across the enterprise. As costs rose and application architecture evolved, the organization needed a database foundation that could support greater agility without compromising reliability. 

This was not a routine infrastructure upgrade. The client had already set a strategic direction to move away from its on-premises Oracle Exadata environment and build a more scalable, cloud-ready platform on AWS. That shift had to support future modernization, improve resilience, and prepare the business for faster change across core systems.

Business Challenges

The client was not dealing with a single migration event. It was trying to modernize a mission-critical database estate while core applications, ownership structures, and modernization priorities were all moving simultaneously.

That made the challenge less about shifting workloads to AWS and more about reducing costs and complexity without introducing instability into the systems the business relied on every day. 

• The organization needed to exit Oracle Exadata on a fixed timeline: The planned move away from Oracle Exadata by the end of 2025 created urgency around reducing licensing and infrastructure costs without disrupting core business systems.  

• The MongoDB estate had to align with a broader modernization strategy: Migration decisions could not happen in isolation because the target architecture also had to support changing application patterns and long-term maintainability.

• Future cloud readiness had to be built in from the start: The client needed a scalable, resilient foundation that could support future workloads and evolving business requirements. 

• Ownership across teams was fragmented: Cross-functional dependencies slowed decision-making and increased the risk of gaps in accountability during planning and execution. 

• Database migration had to stay in sync with parallel application changes: The program had to account for ongoing application modernization, which raised coordination risk and made sequencing far more complex.  

• Schema conversion and compatibility needed careful validation: Complex database objects, conversion feasibility, data integrity, and post-migration performance all had to be assessed before the organization could move with confidence. 

To move forward, the client needed a migration strategy that could lower the total cost of ownership, improve availability through multi-zone deployments, validate performance and integrity, and strengthen stakeholder alignment across the program.

LTM’s Solution

As the Business Creativity partner, we began with detailed due diligence across the Oracle and MongoDB estates to understand database sizes, memory usage, object complexity, and record volumes.

Using Automatic Workload Repository (AWR) data and AWS Schema Conversion Tool (AWS SCT) reports, the team assessed schema compatibility, shaped the migration path, and defined the target architecture, capacity plan, and execution roadmap before moving into delivery.

• Migration strategy grounded in technical feasibility: LTM used AWS SCT for schema transformation and AWS Database Migration Service (AWS DMS) for secure data movement. For MongoDB, the team ran a pilot migration of five workloads from on-premises environments to MongoDB Atlas to validate the approach before scaling further. 

• Testing built into the program from the start: The migration plan included data validation, performance testing, regression testing, and functional testing to verify readiness across the new environment.

• Program governance to align moving parts: To address fragmented ownership, LTM established regular stakeholder interactions, weekly reviews, and a Responsibility, Accountability, Consultation, and Information (RACI) matrix with defined service-level agreements (SLAs). Additional resources and a dedicated program manager helped coordinate database migration activities with parallel application changes. 

• AWS architecture designed for resilience and operational control: The target setup included multi-zone deployments, dynamic storage auto-scaling, and advanced backup capabilities to support a more modern database foundation on AWS. 

Business Benefits

The value of this program showed up where it mattered most: lower run costs, stronger resilience, cleaner execution, and a migration model the client could use again.

Instead of treating modernization as a one-off move, the organization now has a more reliable path to future database and application transformation on AWS. 

• 30% lower database total cost of ownership (TCO): The client reduced costs by exiting Oracle licensing and on-premises infrastructure. 

• 15% to 25% higher operational efficiency: Improved scalability and performance created a more efficient database environment for mission-critical systems. 

• Multi-AZ resilience for core platforms: AWS-based multi-zone deployments strengthened availability and recovery readiness across the modernized estate. 

• 60% less migration effort for MongoDB workloads: The pilot-based migration approach reduced effort and improved execution speed for targeted MongoDB workloads. 

• A repeatable migration foundation for future waves: The program created a stronger framework for upcoming modernization efforts across the broader data estate. 

• Simpler operations with built-in scaling and backup controls: Automated scaling and advanced backup capabilities improved day-to-day manageability of the platform. 

Conclusion

This program changed the economics and the operating posture of the client’s database estate. What had been a costly, tightly bound on-premises environment became a more resilient AWS-based foundation built for scale, performance, and future migration waves.

LTM brought structure where the program needed it most: feasibility analysis, stakeholder alignment, testing discipline, and execution rigor across parallel moving parts. The result was a cleaner way for the insurer to modernize its core systems with greater confidence, lower TCO, and a stronger foundation for what comes next.

Ready to Outcreate modernization in insurance with a database foundation built for resilience, efficiency, and scale?

Contact us at aws.communications@ltm.com to see how LTM can help you lower costs, simplify migration, and own outcomes on AWS.