Global Life Insurance Firm

The Challenge

The client is a premier global life insurance provider with large-scale investment portfolios spanning fixed income, derivatives, and alternative assets. Managing risk across these portfolios requires advanced analytics, high data throughput, and robust reporting capabilities.

 

The client was undertaking the build-out of a new Investment Management Risk Analytics platform to support increasingly sophisticated modelling requirements and large-scale data processing.

 

Key challenges included:

 

• Need for advanced scenario analysis and investment modelling capabilities
• Handling and processing massive volumes of market and portfolio data
• Inconsistent data quality and fragmented reporting workflows
• Performance constraints impacting analytics generation and decision-making speed
• Integration complexity across multiple enterprise systems

Our Approach

RocketFin was engaged to support the design, integration, and delivery of the new risk analytics platform. The objectives were to:

 

• Enable robust scenario analysis and investment modelling capabilities
• Improve data quality, processing speed, and reporting consistency
• Integrate and configure the Beacon platform within a complex enterprise environment
• Support large-scale data handling and analytics generation
• Provide ongoing advisory and delivery support across multiple phases

 

Project Management Methodology
A long-term, Agile delivery model was adopted, with continuous iteration across modelling, data, and platform integration workstreams. RocketFin worked closely with internal teams to evolve the platform alongside business needs.

Technologies Used
• Beacon Platform
• C#, TypeScript, AngularJS for application and analytics development
• Informatica for data integration and processing
• Calypso and Aladdin for trade, risk, and portfolio system integration

Solution Design
• Implementation of scenario analysis frameworks and investment models
• Integration of Beacon into the broader enterprise risk architecture
• Data pipeline enhancements to support large-scale analytics processing
• Improvements to reporting workflows and output consistency
• Performance optimisation for faster analytics generation

Risk Management
Key risks included data volume scalability, model complexity, and multi-system integration. These were mitigated through iterative delivery, performance tuning, and close coordination with enterprise architecture teams.

Governance
• Ongoing engagement with risk, investment, and technology stakeholders
• Multi-phase delivery with defined milestones and validation checkpoints
• Alignment with enterprise governance and architecture standards

Service Lifecycle (ITIL-aligned)
• Development: Model, data, and platform integration
• Testing: Validation of analytics outputs and data integrity
• Deployment: Incremental releases across platform components
• Support: Continuous improvement, optimisation, and knowledge transfer 

The Outcome

The engagement delivered a scalable, enterprise-grade risk analytics platform, enabling the client to:

 

• Run complex scenario analysis and investment models at scale
• Improve data quality, reporting consistency, and processing speed
• Handle large volumes of data with greater efficiency and reliability
• Strengthen integration across core investment and risk systems

 

RocketFin’s sustained involvement helped transform the client’s risk analytics capability into a modern, high-performance platform capable of supporting evolving investment strategies and regulatory demands.