The Industry Landscape
Evolving Trends in Insurance Analytics
Legacy systems and fragmented data continue to hinder fast, intelligent decision-making in insurance. With growing data volumes across underwriting, claims and compliance, insurers must modernize their data foundations to enable agility, personalization and regulatory alignment.
Intelligent data architectures that combine cloud-native platforms with human-led design are re-shaping the landscape, turning real-time, self-service analytics from a competitive advantage into a business imperative.
The Client Challenge
Fragmented Systems, Limited Insights
The client recognized that its legacy business intelligence infrastructure was constraining growth and limiting competitive agility in an increasingly dynamic market.
Critical pain points included:
1. Data Fragmentation and Third-party Dependence
The organization relied heavily on off-the-shelf reporting solutions that provided limited flexibility beyond pre-configured insights, creating bottlenecks for custom analysis and strategic planning.
2. Operational Inefficiency
Lack of policy system integration and limited data availability resulted in lengthy report generation cycles, delaying critical business decisions and reducing responsiveness to market opportunities.
3. Scalability Constraints
With existing Business Intelligence (BI) assets requiring rationalization, the client faced mounting maintenance costs and declining system performance that threatened long-term sustainability.
4. Limited Self-service Analytics
The absence of intuitive self-service analytical tools restricted business users' ability to explore data independently. They were unable to generate ad-hoc reports or derive timely insights on their own. As a result, they became excessively dependent on specialized IT and data analytics teams for routine business intelligence needs.
5. Manual Reporting Dependencies
A substantial portion of the report generation workflow required extensive manual intervention, introducing inherent inefficiencies, elevating the risk of human error and prolonging turnaround times for critical business reports.
6. Fragmented Report Versions
Multiple versions of key reports existed across departments, often without harmonization. This led to the absence of a single source of truth for critical business metrics. As a result, it fostered confusion, contradictory analyses and diminished stakeholder confidence in data integrity.
To maintain competitive leadership and drive sustainable growth, the client needed to transform its data architecture from a collection of disparate systems into a unified, intelligent foundation that empowered business users while maintaining enterprise-grade security and governance.
The Solution
A Secure and Scalable Data Lake Powered by Microsoft Fabric
WNS Analytics designed and deployed a comprehensive enterprise data lake solution built on Microsoft Fabric’s OneLake platform, harmonizing human ingenuity with next-generation technologies.
Our approach blended domain excellence with data management to deliver a context-aware solution, while Microsoft Fabric's unified platform enabled seamless data integration and intuitive self-service capabilities.
Key elements of the solution architecture included:
1. Metadata-driven Dynamic Data Integration
Harmonized sales, distribution, underwriting and claims data streams through automated pipelines and real-time synchronization
2. Centralized Cloud-native Repository
Implemented Microsoft Fabric OneLake as a unified, cloud-native data foundation, integrating domain-specific metadata, end-to-end lineage tracking and advanced data governance
3. Enterprise-grade Security
Implemented a unified data access framework with enterprise-grade Personally Identifiable Information (PII) encryption and role-based controls, ensuring secure, compliant and collaborative data use across departments
4. Integrated Self-service Analytics Ecosystem
Integrated Power BI with Microsoft Fabric and Copilot to deliver intuitive, real-time dashboards and ad-hoc analytics. Rationalized legacy BI platforms to reduce redundancy, accelerate insight generation and empower business users with secure, self-service access to enterprise data
The Outcome
Enterprise Intelligence Delivered at Scale
The deployment of our intelligent data foundation solution delivered immediate and sustained value. Our strategic thinking, integrated with advanced analytics, transformed data from information into actionable intelligence, enabling the client to make faster, more informed decisions.
The tangible outcomes included:
% reduction in report generation time and cost driven by automated workflows, self-service capabilities and a unified reporting framework
% increase in data access efficiency and accuracy enabled by a unified data architecture with embedded metadata that ensured reliability and real-time access for business users
% decrease in maintenance and licensing costs through reduced solutions complexity and infrastructure overhead by rationalizing 40 percent of legacy BI assets and consolidating platforms
Empowered, insight-driven teams as business users were equipped with intuitive tools for self-service analytics, driving faster, decentralized decision-making
Through this partnership, our client solved immediate operational challenges while establishing a foundation for continuous innovation and market leadership.
FAQs
1. How did WNS Analytics help the insurance company improve reporting and analytics?
WNS Analytics implemented a cloud-native enterprise data lake using Microsoft Fabric, integrating data across underwriting, claims, and operations. This unified platform, combined with Power BI and Copilot, enabled self-service analytics, automated workflows, and reduced report generation time by 40%, allowing business teams to access accurate insights faster.
2. What are the key benefits of a self-service analytics ecosystem for insurers?
A self-service analytics ecosystem empowers insurance teams to explore data independently without relying on IT. It ensures real-time access to accurate information, reduces manual reporting errors, increases operational efficiency by 35%, and supports faster, insight-driven decision-making, giving insurers a competitive edge in a data-driven market.
3. Why is a cloud-native enterprise data lake important for insurance operations?
Cloud-native data lakes, like Microsoft Fabric’s OneLake, centralize fragmented data, track metadata and lineage, and provide enterprise-grade security. For insurers, this translates to consistent reporting, lower maintenance costs, scalable infrastructure, and the ability to quickly adapt to market changes—all while supporting future-ready, insight-led operations.
4. What data analytics services does WNS offer to insurance companies?
WNS provides end-to-end analytics solutions for insurers, including enterprise data lake implementation, cloud-native data integration, self-service BI with Power BI and Copilot, advanced reporting automation, and metadata-driven insights. These services help insurers reduce reporting time, improve data accuracy, and enable insight-led decision-making.
5. How does WNS ensure secure and compliant data management for insurers?
WNS implements enterprise-grade security frameworks, including role-based access controls, PII encryption, and centralized data governance. By combining cloud-native platforms like Microsoft Fabric with WNS’s domain expertise, insurers can securely manage sensitive data, maintain regulatory compliance, and support collaborative, self-service analytics across teams.