How Asset Management Organizations Are Investing in Data Management
Executive Summary
Asset management firms are grappling with a confluence of events that have created a particularly challenging environment in which to thrive. The post-pandemic reality of high interest rates and inflation, as well as global political conflict have contributed to significant market volatility, ending a long streak of strong market gains. As a result, asset management firms can no longer rely on market performance to drive profitability. To compete, all firms, regardless of size and geographic region, must deliver innovative products, differentiated client experiences, and streamlined operations.
Improving the use of data locked in silos across the enterprise offers asset management firms powerful competitive advantages. These include enhanced analytics that provide deeper insight into markets and clients, faster reaction to market fluctuations, more precise risk management, and improved responsiveness to regulators.
However, challenges persist with processing and managing the vast volumes of data spread across in-house and third party applications, data warehouses, data lakes, data marts, external data feeds, and other sources. These challenges result in delays, errors, inefficient workflows, and strained internal resources. Improving data management transforms the speed and accuracy of reporting to inform decisions and meet the increasingly complex demands of regulators. The good news is that investment in data management technology is a priority for asset management firms.
The research results presented in this report confirm that improvements to data management processes are considered critical by asset management firms in order to provide faster responses to the front office, improve risk management, and gain a 360-degree view of clients.
According to the research results, many asset management firms are challenged with data errors and delays, making it difficult to provide accurate and timely responses to their business stakeholders. Remediating errors and handling ongoing data requests requires dedicated support from technology staff. The research shows that both small- and mid-sized firms rely on a number of data sources similar to large firms and spend just as many internal resources to service data requests, despite their smaller overall staff, thus increasing margin pressure.
Faced with these barriers, firms are looking to a variety of solutions to speed and simplify access to accurate and timely data. One new approach that is rapidly gaining momentum is the data fabric architecture, which enables firms to address the challenges of disparate, high volume data in a non-disruptive way. With innovative approaches like data fabrics holding real promise for firms looking to leverage new capabilities, the industry has an opportunity to address age-old data challenges more effectively.
Key Findings
After eliminating errors, the next two biggest data management challenges cited by firms are improving responses to regulators and improving risk management.
The research found that asset management firms typically use between 20 and 29 sources of data. When combined with the resources required to process data requests, this places disproportionately heavier demands on the limited resources of smaller firms when it comes to acquiring, processing, and managing all this information.