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The Client

The client is a full-service life insurance company with operations in 22 countries across the Caribbean, United States, and Latin America. With over 4,000 carrier producers and agents, the organization manages extensive data across claims, policies, sales, and customer portfolios.

The Challenge

The client faced siloed data across business units and geographies, which limited reporting capabilities and on-time decisions. They required an enterprise-wide data warehouse to unify transactions into a single source of truth for accurate and timely insights.

  • Data Fragmentation Across Functions:
    Policies, claims, and sales data were spread across multiple systems, making it difficult to consolidate and analyze.
  • Inconsistent & Inaccurate Reporting:
    Conflicting formats and definitions led to errors and inaccuracies in dashboards.
  • Manual, Time-Consuming Processes:
    Heavy reliance on spreadsheets and manual data entry increased the risk of mistakes and delayed reporting.
  • Delay in Generating Insights:
    Decision-making was slowed by the time taken to reconcile and validate data from different business units.
  • Limited Visibility Across Geographies & Products:
    The absence of a unified view restricted leaders from entity-based and portfolio-wide analysis.

challenges

Fragmented data across claims, policies, and sales

Inconsistent data formats leading to inaccurate reporting

Delayed insights due to manual data reconciliation

Poor decision-making due to lack of a unified dashboard

The Solution

Damco partnered with the client to design and implement end-to-end data warehouse solution. The solution integrated data across all functions, streamlined reporting, and strengthened decision-making.

Data Model Standardization

  • Damco established a standardized enterprise-wide data model across claims, products, and sales, ensuring uniform data definitions and comparability across all geographies and entities.
  • The team collaborated closely with business users to validate rules and mappings, aligning data formats and resolving conflicts across systems.

Centralized Data Warehouse Migration

  • Legacy transactional data was migrated to a centralized SQL Server 2014 warehouse with automated validation steps.
  • Version-controlled ETL processes were implemented to cleanse, transform, and load data, ensuring reliability and long-term scalability.

Data Integration & Transformation

  • Damco’s team leveraged ETL pipelines to consolidate fragmented data sources into a unified model, applying transformation rules to reconcile conflicting structures and improve data integrity.
  • The phased delivery approach ensured early value by prioritizing critical business functions before scaling across the enterprise.

Comprehensive Reports & Dashboards Development

  • The team developed IBM Cognos Analytics-powered dashboards to track policy cohorts by SGI, SLI, and SLC categories, covering accident, motor, living benefits, universal, and traditional life policies.
  • Business unit views now displayed assigned portfolio counts across CAPSIL-BAR categories such as Living Benefits, Endowment, and Traditional Life (Par and Non-Par).
  • Audit-ready reports, geographic entity-level views, and product assignment summaries were also integrated, improving compliance and strategic decision-making.

The Benefits

The new enterprise-wide data warehouse provided the client with a centralized, BI-ready data ecosystem promising smart business insights and faster, reliable decision-making.

  • 100% of legacy transactional data integrated into a single enterprise-wide reporting system
  • 99.9% data accuracy achieved through automated validation and cleansing processes
  • 22 countries consolidated under one unified reporting platform, enabling consistent performance insights
  • Accelerated reporting with standardized data available in real time
  • Improved audit readiness through reliable, transparent, and traceable reporting processes
  • Smart decision-making grounded by trusted data across claims, products, and geographies
  • Scalable and future-ready data architecture to support advanced reporting and analytics needs
Data Warehouse Solution - case study

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