Building a secure foundation for AI-driven insurance analytics
- $500K Annual investment
- 80% Potential maintenance savings
- $1M Potential infrastructure savings
This joint solution combines Teradata’s advanced analytics capabilities—such as complex workload management and Bring Your Own Model (BYOM)—with the elasticity and security of AWS. The result is a cloud-native architecture that enables advanced AI and machine learning use cases while maintaining strict compliance with SOC 2 Type II and PCI-DSS requirements.
Known for its commitment to customer service excellence, the insurer set a strategic goal to enhance its digital offerings and improve customer experiences through advanced analytics, AI, and machine learning. However, achieving this vision required overcoming several challenges:
The organization needed a modern analytics platform that could support enterprise-scale analytics today while enabling next-generation AI capabilities for the future.
The insurer implemented a hybrid cloud analytics architecture built on a joint Teradata and AWS solution, designed to modernize its on-premises corporate network while meeting regulatory requirements.
The solution leverages Teradata’s compliance certifications and AWS’s secure infrastructure to align with state insurance regulations, SOC 2 Type II, and PCI-DSS standards. Key architectural elements include:
The primary dataflow begins in the on-premises environment, where SQL Server and DataStage ETL tools feed data into an AWS Data Lake account via Direct Connect. This account serves as a centralized data hub and includes:
At the core of the solution is the Teradata Vantage® platform deployed on AWS, supporting both production (PRD) and development (DEV) environments. Teradata Vantage® runs natively on AWS, with:
Beyond migration, the platform establishes a foundation for AI-driven innovation. By leveraging Teradata BYOM and open table format, the insurer integrates its data warehouse with Amazon SageMaker AI.
This approach allows data scientists to train models in SageMaker and execute them directly inside Teradata Vantage®—eliminating slow, costly data extraction. One planned use case includes a quote abandonment model that scores prospect behavior in real time and triggers personalized re-engagement campaigns for high-intent users.
The migration to Teradata VantageCloud on AWS delivered measurable business and operational benefits while positioning the insurer for long-term innovation.
The partnership directly supports the insurer’s strategic goals, including
While specific total cost of ownership figures remain confidential, the insurer’s annual investment of approximately $500K delivers enterprise-scale value well beyond its cost. By moving to Teradata VantageCloud on AWS, the company:
Industry benchmarks show cloud migrations can eliminate 70% to 80% of traditional maintenance overhead, with documented savings ranging from $250K per quarter to over $1M annually by retiring legacy infrastructure.
The joint Teradata–AWS solution enables:
The migration was completed on schedule, validating the overall strategy and execution. Key takeaways include:
By migrating to Teradata VantageCloud on AWS, this insurer transformed its analytics environment into a secure, scalable, and future-ready platform. The joint Teradata–AWS solution not only delivers immediate operational and business benefits but also empowers the organization to confidently innovate with AI and machine learning—without compromising compliance or performance.
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