‍Marion Aubert, co-founder & Chief International Officer, shared her vision and expertise during the panel discussion: "Best practice ESG data management for compliance and investment insight." In an ever-evolving financial world, ESG data management represents a major challenge for asset managers. Marion presented the best approaches to address these challenges alongside Sarah Boden, Chief Sustainability Officer at Deutsche Bank, Maria Christodoulou, Assistant to the Vice President at SMBC, and Rupert Davies, Founder & Managing Partner at ESG Sum.

A fragmented market facing complex regulations

Asset managers today operate in an increasingly complex regulatory environment. There is a concerning gap between the ambitions displayed by financial institutions and their concrete actions. They must navigate an environment with multiplying regulatory requirements such as SFDR, the European Taxonomy, CSRD, SDR, and TCFD.

This situation is even more complex as these regulatory frameworks are constantly evolving, with the upcoming arrival of SFDR 2.0 planned for the end of 2025. The quality and reliability of ESG data remain major issues that can hinder the adoption of ESG strategies.

Numerous challenges related to ESG data regarding their governance and quality

The quantity of data to analyze is a major challenge. Indeed, 62% of industry players use and compare multiple sources, relying on an average of 5 to 8 different providers. This approach allows them to compare providers and leverage both private and public sources.

However, this multiplication of sources also creates new challenges. Notable issues include data quality and frequent changes in the data provided by different suppliers.

The main challenge therefore consists of centralizing all this information in one place to ensure organizational coherence and facilitate calculations.

Best practices to implement

To ensure the accuracy and completeness of ESG data, rigorous practices are essential. Best practices include:

• Implementing automated technical and functional verifications
• Cross-referencing information from various sources
• Specific controls to compare sustainability indicators with each other
• Automated data matching
• Judicious use of proxies

Cloud infrastructure: the key to scalability

The current state of legacy systems poses numerous challenges, with 92% of British financial services (source: FCA) still relying on obsolete technologies, managing an average of 130 different software systems. This further highlights the complexity of processing different data formats.

These complex and siloed systems hinder sharing and communication between different departments and place operational teams in a position of dependence on IT teams. It is important to note that adding a new data source can take several months.

A cloud-based solution offers the necessary scalability, although sustainability data requires specific processing while maintaining interoperability with other systems.

Characteristics of an effective solution

An effective ESG data management solution must present two fundamental characteristics:

1.Interoperability: allowing it to function with different providers, integrate with existing tools such as Portfolio Management Services (PMS), and exchange data via APIs.

2.Flexibility: regarding data integration, methodology application, and the ability to respond to various client needs.

Automation helps optimize resources by reducing manual tasks, providing a reliable source for advanced analytics. It facilitates the creation of test environments for new methodologies and ensures the auditability required by regulators while preserving data history.

In conclusion, adopting a strategic approach to ESG data management is essential to address all the challenges we have discussed.

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