Our client, the world’s leading provider of news and information services to financial institutions, was grappling with their outdated financial data analytics platform. Integrating real-time financial news, SEC information, and market forecasting capabilities, this platform was essential for managing asset portfolios for their customers that included top financial institutions like the Royal Bank of Canada and US Trust. However, it was plagued with issues: 1. Fragmented Development History: The platform was a patchwork of different teams' efforts, each using their own set of database rules and technological frameworks. This disjointed development history led to significant data inconsistency and prohibitively expensive support. 2. Compromised Analytics: The data inconsistency became a major hurdle in performing comprehensive analytics. Retrieving data for accurate market forecasting was also a challenging process, along with an assessment of consultant performance and the accuracy of forecasts. 3. Scalability Roadblocks: Its architecture was not built for growth. As market demands evolved, scaling up the system required integrating new, intricate components into an already complex architecture. Faced with these challenges, the client sought a partner who could not only conduct a thorough audit of their existing data ecosystem but also guide them in establishing a modern data architecture. The goal was to revamp their data warehouse and create a new, robust data analytics platform, informed by insights from the in-depth audit.
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