Article
Thought-leadership

Opening up ESG data

Challenges with accessing reliable ESG data continue to hinder the integration of ESG into the investment process. Leveraging an open-architecture approach may offer a solution.
Written by
Amandine Leroy, Manaos & Liam Hammond, BNP Paribas
Published on
August 5, 2022

The integration of ESG into the investment process is accelerating, yet challenges with accessing reliable ESG data continue to hinder progress. Leveraging an open-architecture approach may offer a solution.

Few areas are moving as quickly in the investment landscape as environmental, social and governance (ESG) and responsible investing.

As scientific warnings around climate change grow starker, the critical role that the finance sector has to play in the transition is coming more into focus. As a result, institutional investors are ramping up investments that seek to deliver measurable ESG benefits. Research by Bloomberg Intelligence suggests global ESG assets under management (AUM) will increase by around $9 trillion between 2022-2025, surpassing $50 trillion (which would represent more than a third of projected global AUM).

The kaleidoscope of ESG data

In spite of market growth, familiar challenges continue to hinder progress. In our latest BNP Paribas ESG Global Survey, data remained the top impediment to ESG integration – in particular, issues relating to consistency and quality of ESG data.

Unlike traditional financial metrics, ESG factors can be subject to varying interpretation and are inherently more difficult to quantify. The latter is especially true for the social pillar, which remains the most difficult to analyse and integrate according to 51% of investors[1]. As a result, correlation between ratings from main providers has been shown to be comparatively low. One reason for this is the lens through which ESG is assessed. For instance, rating agencies typically focus on financial risk based on exposure to ESG factors, as opposed to the impact, i.e. the alignment of a company with ESG-aligned outcomes.

Low correlation can also come from the basic methodology used to collect information on the companies. For instance, the use of declarative sources such as the company annual report versus third party sources, or the use of natural language processing technologies to scrape the web and press articles versus human analysis. Moreover, the definition of the categories (what does E, S and G actually entail) are not standardised, nor are the weights and materiality tables used to determine a score.

While a number of regulatory and market efforts are underway to help standardise ESG definitions, disclosure and measurement, the idiosyncratic nature of ESG as a concept means we are unlikely to have a universally agreed framework for defining and measuring ESG any time soon.

Instead, institutional investors looking to screen their investments and monitor progress against objectives are using and comparing multiple sources of data, as well as conducting their own research to achieve a balanced view of their investments, and avoid an over-reliance on external vendors.

"The breadth and diversity of ESG as a concept means there is no one-size-fits-all approach." says Amandine Leroy, Product Manager at Manaos, a data marketplace launched by BNP Paribas Securities Services connecting clients with a wide range of third-party ESG data vendors and fintechs.

“As a result what we have seen is a proliferation of a number of incumbent but also new ESG data vendors specialising in different approaches. In isolation, no one provider can give the full picture across thematics. But when used together, it’s possible to gain a much more holistic view of a portfolio’s sustainability.”

While leveraging multiple sources can help provide a balanced view and mitigate consistency issues, achieving this via traditional ‘build or buy’ data models can be a time and cost intensive exercise. These setups can also be limited in their ability to easily add new datasets to the operating model as and when they become available.

This can lead to a dreaded ‘spaghetti junction’ of data feeds that need to be aggregated and synthesised at a portfolio or even asset level to provide an accurate view.  This is where an open-architecture approach has a growing role to play.

Leveraging open-architecture ESG data models

To ramp up integration of ESG in a practical and credible way, it is clear that investors need access to diverse and reliable ESG data as quickly and as cheaply as possible. As a key part in institutional investors’ ESG value chain, this was one of the key drivers behind BNP Paribas Securities Services’ launch of its Manaos platform.

"A key objective was to remove the point of friction that existed between identifying relevant data and efficiently integrating it into the investment process. For Manaos, we felt the best way to do this was a plug-and-play solution that would give institutional investors access to a growing universe of datasets and providers, as well as the aggregation, analysis and reporting capabilities, all within a single platform. We call this approach open-ESG. " says Amandine

Adopting this approach offers an app store type experience for ESG data. The model can be customised and scaled without the pre-configuration and dependency challenges of traditional ESG infrastructure setups. Institutional investors can access packaged analyses across different themes, which they can use for standalone scoring or as the basis for proprietary analysis. This makes it possible to gain a holistic view of investments in a much more compressed timeframe, ultimately reducing time to integration, but also cost.

“In trying to democratise ESG data, accessibility from a cost standpoint was also very important to us,” says Amandine. “By taking a freemium approach to the pricing model, institutional investors of all size have the ability to sample what is available without purchasing it first. They can then choose to scale their model as required by adding additional services or analyses.”

Manaos currently has more than 30 applications live on its platform, with more on the way. Among current partners are well-established names such as S&P Global Sustainable1, Moody’s ESG Solutions, CDP, and Clarity AI, but also more specialist players such as Util (focusing on the UN Sustainable Development Goals), Greenomy (EU Taxonomy/SFDR reporting), and OWL ESG (consensus scores across different vendors/methodologies). It also has several proprietary apps specifically aimed at simplifying data management across different portfolios and formats. For instance, its Collection and Dissemination apps help investors to exchange, harmonise and enable look-through of fund inventories.

Manaos has also launched a new app focused on helping asset managers with EET (European ESG Template) requirements. The template, designed by Financial Data Exchange (FinDatEx), captures the ESG characteristics of a fund range in a standardised format, which can then be disseminated to distributors. While EET is not a regulatory requirement in itself, the template will facilitate compliance with impending regulatory requirements under SFDR, EU Taxonomy, MiFID and Insurance Distribution Directive (IDD).

Progress over perfection

A lack of standardisation across ESG data and disclosures continues to present a challenge to sustainable investing. However, while far from perfect, asset managers and asset owners must do the best they can with the tools and frameworks available if they are to keep pace with mounting regulatory and investor expectations. To do this, many are taking a holistic view of their portfolios by using multiple data sources and conducting their own analyses. This is where we see a growing place for open-architecture models, that not only help investors easily access reliable ESG information and report on the sustainability of their investments, but also adapt to the market as it evolves.

*Manaos is a BNP Paribas platform in a separate legal entity – 100% owned by BNP Paribas Securities Services

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