Our client is a Fortune 500 insurance provider operating globally, managing millions of policyholders and complex underwriting risk models. Their legacy infrastructure relied on siloed, on-premise data centers that struggled to keep pace with the massive volume of real-time claims processing, actuarial analysis, and customer engagement data. As the organization expanded its digital footprint, the cost of maintaining aging hardware and the latency inherent in their traditional ETL (Extract, Transform, Load) pipelines became a significant bottleneck, directly impacting their bottom line and agility.
Hours delivered back to the business
SOX compliance in Settlement process automation
Success rate of bot case completion
For functional release of OBT, RTS and OGS
The Challenge
The insurance provider faced an escalating crisis regarding data accessibility and operational expenditure. Their primary legacy system was built on a monolithic architecture that required extensive manual intervention to reconcile data across disparate departments. As the volume of ingested data grew exponentially, the system’s inability to scale horizontally led to frequent processing delays, resulting in delayed claims settlements and hindered the actuarial team’s ability to run complex simulations for risk assessment.
Beyond performance issues, the maintenance of this aging infrastructure incurred prohibitive overhead costs. The IT department was locked into rigid licensing agreements and expensive hardware refresh cycles that did not provide a return on performance. Furthermore, the lack of a unified data lake meant that critical business intelligence was locked away in “data swamps,” making it impossible for the executive team to gain a holistic view of financial health or customer behavior in real-time.
Finally, the organization struggled with data integrity and compliance across various regional jurisdictions. Because the legacy environment lacked modern automated governance, keeping up with shifting international insurance regulations was a manual, error-prone, and labor-intensive process. The leadership team recognized that without a strategic migration to a modern cloud-native big data ecosystem, they would continue to lose competitive advantage and bleed capital on inefficient technical debt.
What did
Tecnologia do
Amrita Infovision Pvt Ltd (AIV) initiated the engagement by conducting a comprehensive audit of the client’s existing data landscape. We identified redundant processes, mapped critical data dependencies, and architected a future-proof roadmap centered on a cloud-native migration strategy. By implementing an automated, serverless data pipeline, we replaced the manual ETL workflows with a robust, scalable framework that could ingest and process structured and unstructured data in real-time, significantly reducing the system’s operational footprint.
To ensure business continuity, AIV executed a phased, “zero-downtime” migration strategy. Our engineers utilized high-speed replication tools to move legacy data into a scalable, cloud-based data lake, ensuring that the transition remained transparent to end-users. During this phase, we also introduced granular data governance protocols and automated cleaning scripts, which immediately sanitized the client’s historical data and ensured all incoming streams met the highest standards of accuracy and regulatory compliance.
Beyond the migration itself, our team empowered the client’s internal staff through a comprehensive knowledge transfer initiative. We implemented modern BI dashboards that enabled the actuarial and management teams to visualize risk models and operational KPIs at the click of a button. By establishing this cloud-native ecosystem, AIV did not just move the data; we fundamentally modernized the client’s decision-making process, replacing guesswork with data-driven precision.
The Results
- Significant Cost Reduction: Achieved a $750,000 monthly saving in operational expenditure by eliminating expensive legacy hardware maintenance and optimizing cloud resource allocation.
- Enhanced Processing Speed: Reduced data ingestion and transformation latency by 85%, allowing for near real-time claims processing and risk analysis.
- Scalability on Demand: Successfully transitioned to a serverless architecture that scales automatically with data volume, eliminating the need for over-provisioning infrastructure.
- Improved Governance & Compliance: Automated the audit trail and data validation processes, ensuring 100% adherence to complex international insurance regulatory requirements.
- Data-Driven Decision Making: Empowered stakeholders with self-service BI dashboards, reducing the time required to generate complex financial reports from days to minutes.
- Operational Resilience: Increased overall system availability to 99.99%, virtually eliminating the costly downtime that previously plagued month-end financial reconciliation.
