The client captures voluminous data from multiple internal and external sources. The absence of quick, on-demand capabilities for business users was inefficient in generating customized portfolio analytics on attributes such as average quality, yield to maturity, average coupon, etc.
The client teams were spending enormous amounts of manual effort and elapsed time (approximately 12-15 hours) to respond to requests for proposals from their respective clients.
Iris implemented a data acquisition and analytics system with pre-processing capabilities for grouping, classifying, and handling historical data.
A data dictionary was established for key concepts, such as asset classes and industry classifications, enabling end users to access data for analytical computation. The analytics engine was refactored, optimized, and integrated into the streamlined investment performance data infrastructure.
The team developed an interactive self-service capability, allowing business users to track data availability, perform advanced searches, generate custom analytics, visualize information, and utilize the insights for decision-making.
The solution brought several benefits to the client, including:
- Simplified data access to generate custom analytics for end users
- Eliminated manual processing and the need for complex queries
- Enhanced the stakeholder experience
- Reduced response time to client RFPs by over 50%