Navigating data management challenges In today's competitive financial landscape, asset managers face the significant challenge of attracting new institutional clients, in part due to outdated data management practices. Many firms still rely on an Excel-driven approach, which often leads to inconsistencies and inefficiencies. To meet the sophisticated information needs of institutional clients, a shift to a database-driven approach is essential. Data is everything in asset management Hilton emphasises the critical role of data in asset management, explaining that firms must regularly update data on their securities, maintain pricing across multiple vendors and currencies, and track various characteristics like region, sector, and market cap. Effective data management is essential for accurate analysis and reporting. He further distinguishes between Excel-driven and database-driven systems. In an Excel-driven model, data is spread across multiple workbooks, which often lose consistency over time. In contrast, a database-driven approach uses a single source of truth, ensuring data is current and analyses are consistent. Embracing a database-driven approach isn’t just for quantitative or large asset management firms. Accenture’s 2020 report revealed that 83% of asset management firms lacked enterprise-wide Master Data Management, a statistic that likely hasn’t improved much. Yet the ability to manage data well is becoming increasingly essential, even for medium-sized firms.

Navigating data management challenges

Navigating data management challenges

Navigating data management challenges