Case Study

Modernizing Insurance Data Platforms with a Data Vault-Driven Cloud Architecture

Industry

Insurance (Specialty Insurance)

Location

United Kingdom

Our Contributions

Data Modernization, Data Vault 2.0 Modeling, Cloud Data Platform Engineering, Data Governance, ETL Automation, DevSecOps Enablement

Specialty insurers rely on robust, transparent, and governed data platforms to support underwriting decisions, operational processes, and rapidly evolving business rules. However, legacy on-premises data warehouses often struggle to scale with modern digital systems, resulting in fragmented data, slow insight generation, and limited visibility into critical business changes.

To accelerate digital transformation and support real-time decision-making, insurers are modernizing their data foundations using cloud-native architectures and standardized modeling approaches that improve flexibility, auditability, and governance.

The Challenge

The insurer’s legacy data warehouse environment lacked scalability, transparency, and consistent governance, making it difficult to support digital channels and real-time business rule changes. Data was fragmented across multiple systems, including SQL Server, Pega, Sitecore, Salesforce, and file-based sources, leading to inconsistencies and delayed insights.

Manual and slow ETL processes limited reusability, while the lack of standardized data modeling made it difficult to enforce consistent business rules. Limited reconciliation controls and a lack of real-time visibility further increased operational risk, highlighting the need for a secure, auditable, and cloud-native data platform.

Our Approach

Coforge designed and implemented a modern, cloud-native data platform leveraging AWS, Snowflake, and Data Vault modeling to deliver scalability, governance, and real-time transparency.

Cloud-Native Data Platform Foundation

Built an enterprise data lake on AWS and a Snowflake EDW using a future-ready, scalable architecture designed to support digital and operational use cases.

Data Vault 2.0 Modeling

Implemented Data Vault 2.0 as the core EDW modeling approach to ensure flexibility, lineage, auditability, and controlled evolution of business rules.

Unified Ingestion & Orchestration

Enabled ingestion from system databases using Attunity and message-based sources via the Intelligent Scriptless Ingestion accelerator. Built Airflow-based orchestration to manage end-to-end pipelines reliably.

Transparency, Governance & Automation

Introduced centralized reconciliation and monitoring for trusted data flows. Delivered a UI-based business rule engine to allow real-time updates by business users, supported by a meta-model service for ETL reuse and DevSecOps-based continuous deployment.

Impact to Date

The Data Vault–driven modernization delivered measurable gains in speed, governance, transparency, and operational efficiency.

~30% Faster

Business Rule Deployment

~25% Reduction

ETL Maintenance Effort