Use of new technologies to facilitate data collection, particularly ESG on Private Markets
Why collect non-financial data?
The need to collect data, which used to be primarily financial in nature, now extends to non-financial data.
To meet the expectations of investors who wish to give meaning to their investment with investments that are more sustainable and responsible, asset managers are, for strategic reasons, beginning to integrate ESG criteria1 into their investment strategies, offering funds that promote ESG characteristics (Article 8 funds under the SFDR2), and even funds that have a sustainable development objective (Article 9 funds under the SFDR).
By way of illustration, 52.9% and 3.5%3 of assets under management in Europe are currently invested in funds that fall under Articles 8 and 9, respectively. Asset managers prefer not to be seen to be overly ambitious and therefore limit themselves to Article 8 funds under the SFDR, rather than Article 9 funds, even going so far as to downgrade Article 9 funds at their own initiative. There is a balance to be struck between ESG objectives, profitability and portfolio diversification. How can this third goal be met when the share of the Taxonomy-aligned revenue of CAC40 companies is estimated to be just 2%?4
The inclusion of ESG criteria in investment strategies means that there is a real need to collect ESG data to measure performance. This need is reinforced both by the desire of asset managers to avoid any risk of greenwashing and by the ever-increasing number of ESG-related regulatory obligations (Taxonomy Regulation, SFDR, etc.), thereby gradually increasing the range of data that has to be covered: climate, social, biodiversity, etc.
Collecting this data requires both IT systems and human intervention.
The systems used up until now to manage financial data are not suitable for, or easily adaptable to, non-financial data; consequently, asset managers do not have the systems required to meet this new need.
In the world of listed companies, access to data is undoubtedly facilitated by the presence of financial and - now - non-financial data providers, but it should be borne in mind that the collection of such data remains cumbersome, as several ESG data providers generally need to be consulted to cover the various areas of investment and the different criteria applied.
In the inherently illiquid world of non-listed companies, data collection has always been a real challenge - historically in the case of financial data (e.g. to value assets) and now in the case of non-financial data. ESG data collection in the financial year 2023 has therefore been relatively complicated for asset managers: many have no other choice but to use Excel and are now looking for a tool that will make it easier to collect investee company data. To do this, they have to send out relevant questionnaires to investee companies, aggregate the data at fund level and thereby meet their non-financial reporting obligations: SFDR regulatory reports, EET report5 provided to their distributors, etc.
To implement a virtuous ESG approach between asset managers and their investee companies, it is essential to go beyond the needs of pure data collection by offering:
Calculators (e.g. carbon) to help investee companies with their reports
ESG reports made available to investee companies to help them to define their own strategies in these areas
Modules that will enable asset managers to define and monitor action plans with their investee companies
What can such systems achieve without an expert trained to support asset managers?
In the age of generative artificial intelligence, even if initiatives that use new technologies to facilitate data processing are emerging (for example, the use of character recognition tools and artificial intelligence by data providers to extract data from company reports), the need for human intervention remains very real and the expectations of asset managers go far beyond mere technological systems.
Asset managers, particularly those embarking on ESG, need significant support in terms of training, and day-to-day assistance from experts familiar with these metrics. Experts will offer them support with data collection, by administering and monitoring the collection of necessary data from their investee companies, then by checking the data collected and ultimately producing reports.
What about the future? Time for quality…
The foundations laid by the regulations (Taxonomy, SFDR, etc.) have given rise to a common language between players, but there is still a long way to go to ensure that asset managers receive data that is comparable and of satisfactory quality: raw data is hardly checked and all too often comes from proxies (sector data). The implementation of theCSRD6 in Europe is a key step that will pave the way for improved data quality, at least for listed companies, by gradually introducing, between now and 2029, stricter requirements regarding the provision of audited non-financial raw data by European companies. The approach is intended to be virtuous and progressive, and it will certainly take many years for the structure to become more robust, but let's not forget that Rome was not built in a day!
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Product Engineer, Societe Generale Securities Services - Private Markets
1 ESG: Environmental, Social and Governance criteria.
2 SFDR: Sustainable Finance Disclosure Regulation
3 Morningstar Direct. Assets as of June 2023. Based on SFDR data collected from prospectuses on 97.6% of funds available for sale in the EU, excluding money market funds, funds of funds, and feeder funds.
4 ISS ESG & Adelphi - European Sustainable Finance Survey 2020
5 EET: European ESG Template
6 CSRD: Corporate Sustainability Reporting Directive