Volker Lainer, VP, Product Management and Regulatory Affairs at GoldenSource.
The role of data in financial markets is constantly evolving to fit with trading trends and constant advancements in technology. Back in 2022, we saw new requirements come into force under MiFID II for banks and investment firms to integrate sustainability into their suitability assessments and product governance, as well as a new sense of focus on climate and nature-related disclosures with the Taskforce on Climate-related Financial Disclosures (TCFD) and Taskforce on Nature-related Financial Disclosures (TNFD) reporting requirements. In the realm of what is defined under sustainability now, the pressure is certainly on businesses to do more.
The ESG landscape
That said, the ESG landscape is still dominated by uncertainty. A recent report by Clarity AI, has brought Sustainable Finance Disclosure Regulation (SFDR) fund labels back into the limelight after finding nearly a quarter of Article 9 funds were failing the ‘do no significant harm’ test.
While there have been a number of developments in recent years, the one thing that fund managers cannot afford to do is stand still when it comes to gathering and applying ESG-related data to comply with increasingly stringent regulatory standards. As more regulations come to light on a global scale, clearly long-term climate objectives are front of mind for both regulators and investors who are looking to generate sustainable returns across multi-asset portfolios.
To ensure compliance, the answer is simple – data. Having a strategic data management solution that can adapt to the input of more granular ESG data is what gives firms competitive edge.
Applicable for all global ESG regulations, firms require a variety of different data points, and multiple ESG data sources for those data points where available, on top of their own analytical capability to digest the data to prevent greenwashing and accurately map for physical and transition risks and opportunities. For funds, this will demand transparent, documented processes and procedures backed by data and analytics.
The predictable evolution of ESG data sources and requirements means financial firms will face ongoing change in ESG data management and related business processes over the coming years, and this is where the importance of having access to the latest and greatest data is paramount. Pooling information from multiple data sources requires the means to manage all this data in a way that is meaningful, efficient and applicable.
Clearly demands are being placed on data vendors, but this is also where data management solutions come in to approach this in a more packaged way. This can help to handle aggregation for account-level information, allowing firms to automatically check that investments are in line with the account-level suitability preferences of the customer. Previously, this was approached on a more manual level, but the next step is automating the process to maximise efficiency across the organisation, especially as more global ESG regulations come into force.
As with many areas of ESG, the standards are still evolving and industry players must establish the capabilities to acquire and understand the related data, as well as retain the flexibility to apply that data for a variety of different analytics and reporting purposes as requirements continue to change
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