In pursuit of infrastructure modernization and superior financial governance, a nationally recognized insurance conglomerate initiated a pivotal collaboration with Atlantic Computer Systems (ACS). The initiative was designed to architect and implement an end-to-end migration from fragmented, obsolete on-premises data architectures to a unified, cloud-native big data ecosystem. This strategic evolution served as both a technological uplift and a catalyst for enterprise-wide digital transformation. The outcomes were nothing short of transformative: operational workflows were streamlined and automated, advanced analytics enabled real-time insight generation, and a recurring monthly cost savings of approximately $750,000 was realized—representing one of the most substantial financial optimizations in the company’s history.
Hours delivered back to the business
SOX compliance in Settlement process automation
Success rate of bot case completion
For functional release of OBT, RTS and OGS
Contextual Challenge
Prior to engagement with ACS, the insurance provider’s IT environment was dominated by legacy systems—monolithic data warehouses and siloed operational databases—that could not accommodate the scalability, speed, and agility required for today’s hyper-competitive, data-intensive insurance landscape. The infrastructure was burdened by excessive capital expenditures for hardware refreshes, inflated software licensing fees, and a chronic reliance on manual data processes. Furthermore, disparate data repositories inhibited enterprise-wide visibility, constrained actuarial modeling precision, and undermined customer satisfaction metrics due to lagging response times in claims and support channels.
Real-time data access was virtually nonexistent, and the inability to unify structured and unstructured datasets in a single framework precluded the use of modern analytics, machine learning, or predictive modeling. This lack of insight hindered fraud detection capabilities and introduced delays in underwriting and compliance reporting. The organization recognized that without a holistic, elastic, and secure big data framework, its long-term competitiveness was at significant risk.
ACS Strategic
Intervention
Upon conducting a rigorous diagnostic assessment and systems audit, ACS formulated a comprehensive, phased migration strategy anchored in a Microsoft Azure-native data architecture. The strategic roadmap integrated a suite of enterprise-class technologies including Azure Data Lake Storage Gen2 for scalable and secure data consolidation, Azure Synapse Analytics for distributed query processing, and Databricks for advanced machine learning workflows and real-time data engineering.
Additionally, ACS implemented Apache Kafka for streaming data pipelines and utilized Power BI for democratizing analytics access across the enterprise. An internal governance model was established to ensure data quality, provenance, and lifecycle management, aligning with industry compliance mandates.
Key deliverables included:
Migration and transformation of over 12 years of historical policy, claims, billing, and customer interaction data into a highly available cloud data lake
Decommissioning of six high-maintenance legacy systems, reducing IT overhead and simplifying architectural complexity
Development of AI-driven analytical models for fraud detection, risk scoring, and predictive lapse modeling
Deployment of real-time data pipelines between front-end applications and the analytics environment to support dynamic underwriting and live claims tracking
Empowerment of line-of-business stakeholders with self-service BI dashboards and event-driven alerts
The Results
- Enterprise Agility: Business units gained the ability to generate analytic insights independently, leveraging curated data marts and no-code interfaces, accelerating time-to-insight by 70%.
- Robust Security and Compliance: Data was encrypted end-to-end, access control was enforced via Azure Active Directory and RBAC (Role-Based Access Control), and audit trails were implemented to support HIPAA, PCI-DSS, and NAIC data regulations.
- Elastic Scalability: The cloud infrastructure was designed with autoscaling capabilities to accommodate seasonal volume spikes, such as during natural disaster-related claim surges, without performance degradation.
- 3x acceleration in claims processing due to enhanced real-time data ingestion and decisioning
- SDK delivered for native platforms, enabling Virtual & Live agent communications across multiple mobile platforms
- 40% increase in SLA compliance for customer service metrics, directly linked to rapid access to unified customer records
