Why the C-Suite Needs to Care About Data: A Capital Markets Buy-Side Impact Assessment Survey, commissioned by InterSystems and produced by Aite Group, highlights the impact of poor data support on business processes, including financial, regulatory, and risk management. This white paper is based on conversations with executives with knowledge of their firm’s data architecture and data management strategy at 19 global capital markets firms. It examines why firms need to invest in data architecture to improve their competitive and operational capabilities in the era of digital transformation. Key takeaways from the study include:
- Three of the top four data architecture challenges are around integrating, cleansing, normalizing, and transforming data for use by the business. These challenges will only increase as the volume and number of data sources needed increase.
- Many buy-side respondents currently have a problem with operational and technology data silos, but many have plans to tackle silos via technology investments and strategic governance programs. A major challenge for these firms is getting clean data to specific business units from portfolio management to client reporting teams.
- For the buy-side, areas such as trading have put significant demands on data teams and technology, with the growing focus on best execution requirements and accurate regulatory reporting. Nevertheless, for these firms, portfolio management is as it should be, the function that has placed the most pressure on internal data architecture. No matter how well supporting business units perform, delivering on investment returns and attracting assets remain the overarching goals that define success for these firms.
- An effective data management team is focused on demonstrating the “value” in data and emerging business cases—the priority is gaining business buy-in and support across the enterprise for improvement of data architecture and data delivery.
- The majority of buy-side respondents view improved reliability as the most important goal and benefit of data architecture investment. Confidence in data quality and stability of internal data architectures to meet ongoing business demands is vital for firms.
- Half of asset manager respondents are focused on developing an internal API strategy to better connect siloed data sets that often live in best-of-breed applications. The goal of APIs is mainly to support straight-through processing efforts.
- Aite Group estimates that the majority of Tier-1 sell-side and buy-side firms have less than 10% of their total technology stack hosted in a public cloud environment. Multiple asset management firms are considering migrating key applications from on-premises installations to cloud hosted. However, many still have reservations largely due to security and lack internal expertise to provide oversight over cloud outsourcing.
- A sizable portion of buy-side respondents are either actively considering machine learning’s (ML) application to deliver insights for the investment process or are already piloting in this area. However, many other institutions have noy yet considered how ML can support their businesses.