by Mahra Alfalasi, Intern, SmartStream
Data is the new currency in finance and last week – as part of my internship at SmartStream – I had the chance to be a part of and witness the SmartStream Connect 2024 Customer Conference in London. On the agenda was a panel discussion on Data Processing, hosted by Linda Coffman of SmartStream (EVP Reference Data Services), which featured insights from Pallavi Dongre (SVP, SmartStream) and Ross Lancaster (Head of Research, Acuiti), shedding light on the transformative power of data in the financial sector. The conversation examined how financial institutions are progressing from foundational data management toward strategies that generate revenue and alpha.
Key Takeaways
Investment in Data Management: A recent survey conducted by Acuiti, discussed during the panel, revealed that over 70% of respondents had invested in data management in the last five years, with half doing so in the past 12 months. This steady investment demonstrates the growing recognition of data’s role in business transformation. Firms are now moving from building foundational platforms to exploring ways to leverage data for growth, operational efficiency, and revenue generation.
However, the survey also revealed the stark reality that only 21% of firms rely on a single vendor for data—most firms are managing multiple data sources. This complexity increases the need for integration and harmonisation, directly impacting operational efficiency and revenue potential.
Navigating the Data Maze: Data integration remains a major challenge for firms, particularly with the lack of standardisation across different data platforms. Pallavi Dongre highlighted the issue, stating that firms juggling multiple vendors often face inefficiencies, which can lead to revenue loss. As discussed in the panel, integrating data from various vendors is cited as the most significant challenge by many financial institutions.
The panel also touched on the challenges firms face when trying to standardise external data from exchanges and counterparties, making corporate actions and reconciliations especially difficult to manage. According to the statistics from the Acuiti survey, these two aspects are marked as particularly challenging for both hedge funds and sell-side firms alike.
Sector-Specific Strategies: Ross Lancaster emphasised intriguing differences in technology investment strategies across the financial sector:
- Hedge funds and proprietary trading firms prioritise external data harmonisation
- Sell side firms focus on improving internal systems, particularly for enhancing straight-through processing (STP)
These differing priorities reflect the unique operational challenges each sector faces, with hedge funds contending with contract changes and corporate actions, while sell-side firms are more focused on trade settlements and reconciliations.
The Importance of Data Accuracy: Pallavi Dongre warned that treating data as static can lead to complacency. Even “static” data, such as corporate actions and contract updates, are subject to regular changes due to market and regulatory shifts. Failing to update data in real time can result in operational errors and added costs. The Acuiti survey found that over 50% of sell-side firms view corporate actions as particularly challenging to manage; further underscoring the importance of maintaining up-to-date and thus accurate data.
Regulatory Compliance: Regulatory compliance was another key theme, with the panel noting the increased complexity brought about by new identifiers and expanding regulatory requirements. Survey respondents, particularly sell-side firms consistently cited regulatory reporting as one of their top operational challenges. This is exacerbated by the need to manage data from multiple jurisdictions and maintain compliance amid evolving regulations.
From Data Efficiency to Alpha
Looking to the future, AI and machine learning (ML) emerge as potential game-changers in data management. These technologies promise to:
- Improve data accuracy
- Automate decision-making processes
- Enhance overall productivity
For hedge funds and proprietary trading firms heavily reliant on external data, the automation of data harmonisation and reconciliations could dramatically improve efficiency and reduce regulatory burdens.
The journey from efficient data processing to achieving alpha is complex, with challenges in integration, standardisation, and compliance. By continuing to invest in technology, reducing manual processes, and enhancing transparency, firms can not only meet their current data needs but also position themselves for future success.
With over 70% of firms already investing in data management and over 50% viewing corporate actions as a major hurdle, financial institutions are making significant progress. By adopting AI and ML, firms can turn these challenges into opportunities, transforming data management into a key driver of profitability and growth.
