CASE STUDY

Life Insurance Reserve
Process Transformation with High-Performance Calculations

Software Development
BFSI

Project Highlights

Scope

  • Modernised life insurance reserve calculation processes covering annual, long-term, premium-refund, and accumulation policy types.
  • Implemented dual execution models supporting both online policy-level calculations and automated daily batch reserve processing.
  • Redesigned the architecture using microservices to improve performance, reduce processing overhead, and optimise resource usage.

Challenges Overcome

Reduced processing complexity while maintaining accuracy across multiple reserve calculation models.

Enabled real-time reserve visibility without impacting daily batch performance.

Integrated reporting outputs across data warehouse and analytics platforms while ensuring consistency of financial results.

Business Impact

The redesigned reserve calculation framework improved processing performance, reporting accuracy, and operational efficiency across life insurance reserve management.

Daily reserve calculation processing time

CPU utilisation during reserve processing

Manual intervention in reserve calculations

Financial reporting preparation time

The Client

The client is a prominent financial institution and a key player in the global banking sector. Renowned for its innovative approach to digital banking and customer-centric services, the client offers a wide range of financial products, including retail, corporate, and investment banking.

  • Operates an extensive network of branches and digital platforms, serving millions of customers worldwide.
  • Recognised as a leader in adopting cutting-edge technologies to enhance operational efficiency and customer experience.
  • Committed to sustainability and innovation, driving positive change in the financial industry.
Business professionals in meeting with charts

The Problem

  • Reserve calculation processes relied on legacy structures that created high processing overhead and limited performance scalability.
  • Daily reserve calculations required optimisation to support growing policy volumes without increasing infrastructure costs.
  • Online reserve visibility was limited, preventing business teams from accessing up-to-date policy reserve information.
  • Reporting processes required better integration with data warehouse and analytics platforms to improve financial transparency.

The Solution

BGTS redesigned the life insurance reserve calculation framework using a microservices-based architecture to improve scalability and processing efficiency. Reserve calculations were optimised across multiple policy types, while dual execution modes enabled both real-time policy processing and automated batch execution.The solution introduced online reserve viewing capabilities, allowing policy-level reserve tracking in real time. Month-end processes were enhanced through automated reserve release and reporting based on policy maturity dates. Integration with the data warehouse and Oracle Business Intelligence enabled consistent reserve reporting and improved financial visibility.

Team & Technology

Tech Stack Utilised

Backend

  • Java
  • Spring Boot

Architecture:

  • Microservices

Database

  • Oracle Database

Integration

  • REST APIs

Reporting & Analytics:

  • Oracle DWH
  • Oracle Business Intelligence (OBI)

Batch Processing

  • Spring Batch

Team Composition

1 Architect

5 Full-Stack Developers

1 Business Analysts

1 Tester

The Outcome

Faster reserve calculations

The modernised architecture significantly reduced processing overhead and improved daily reserve calculation speed.

Real-time reserve transparency

Business users gained the ability to view policy reserves online, improving operational visibility and decision support.

Optimised infrastructure usage

CPU optimisation and microservices design improved resource utilisation without increasing system footprint.

Reliable financial reporting

Integrated DWH and OBI reporting improved consistency and accuracy of reserve-related financial reporting.