Data Engineering Services on AWS Cloud for A Large Insurance Enterprise

Problem Statement

The client was struggling with many challenges and approached Aegis to overcome them with efficient data engineering solutions. The client had highlighted their pain points saying,

“We have our data spread across multiple legacy systems and we are finding it hard to access and analyze. On-premise infrastructure is not kept up with the growing data volumes leading to system slowdown.”

"We are also dealing with delays in claims processing, and the need for manual intervention is increasing our costs. Regulatory compliance is another concern, as our old systems are not up to current security standards. And, without real-time analytics, it is becoming challenging to make informed decisions."

Objectives

• Transfer data from on-premise to the cloud infrastructure.
• Automate data processing and ensure compliance with industry regulations.
• Improve scalability to handle large volumes of claims data in real-time.

Outcomes

• 30% faster data access with a centralized data lake on AWS S3.
• 40% reduction in processing time for claims, policy updates, and risk assessments.
• 25% savings in operational cost and 50% scalability improvement.
• Data quality and compliance increased by 35%.
• 15% boost in customer satisfaction due to faster claim processing and real-time policy updates.

Future Implications

Implement predictive analytics to improve claims forecasting and customer experience.

The solution integrates AI-driven automation for all processes including underwriting, claims processing, and customer support with increased scalability.

Conclusion

The insurance enterprise has leveled up its data infrastructure by partnering with the Aegis team. We have implemented AWS Cloud-based Data Engineering services and successfully delivered a project that helped the company remove all the bottlenecks by centralizing data, automating processes, and enhancing compliance.