Transforming Insurance: Unveiling Big Data & BDAP for Global Transformation

Client profile

Our client, a multinational insurance company, operates across the entire insurance value chain—from reinsurance to primary insurance and risk solutions. With a presence in over 160 countries and serving over 4,000 corporate clients, their reinsurance group boasts €48.1 billion in gross premiums.

Business challenges

• Disparate systems across client sites lacked operational control and monitoring capabilities, resulting in data silos, inconsistencies, and high costs.
• The absence of a single source of truth resulted in data quality issues and reporting inconsistencies, hindering decision-making.
• Limited reporting capabilities and inadequate support for legacy systems hindered complex data analytics and business intelligence needs.
• Scaling up existing infrastructure and lacking central data governance for legacy data warehouses compounded operational inefficiencies.

LTM solution

• LTM helped map solutions to the big data and analytics platform (BDAP), automated infrastructure provisioning, and designed reference architectures for solution architects.
• Key advantages of the data platform include:
  • Developed metadata ingestion frameworks, logging frameworks, and transformation logic using Azure and Databricks for improved data processing.
  • Implemented data quality checks and processes for batch and stream data using Delta live tables, ensuring consistent and reliable data.
  • Addressed technical queries related to Azure and Databricks and actively participated in Unity Catalog migration and validation activities.

Business benefits

• Delivered curated data for business users, establishing a single source of truth for critical business operations such as financial reporting and policy management.
• Implemented a scalable, agile, and simplified architecture aligned with data governance practices, fostering a data-driven culture and ensuring data security and auditability.
• Addressed out-of-support hardware and software components associated with legacy systems such as Exadata.
• Ensured integrity through quality measures and lineage tracking across the data environment.
• Reduced redundancies with modern reporting platforms, streamlining operations and enhancing decision-making capabilities.