Data is essential for financial institutions seeking to demonstrate to investors, customers and regulators that they are behaving sustainably. But that can’t happen until the data is properly managed and governed, a panel of experts told an A-Team ESG Insight webinar.While there are challenges to getting that right, it’s essential that firms pay special attention to these processes in order to keep data available to individuals within an enterprise, useable by analysts and other operations, and trusted. Without those ingredients financial institutions will run into a lot of reporting and operational difficulties that will be troublesome and costly to address later.
The comments, which came in this week’s Managing Data Governance for ESG webinar, established that at stake is not only the market value of companies, but also their reputations, credibility and viability.
Panellist Philip Miller, Co-CEO and Co-Founder of Solidatus, said a solid governance and management framework would enable data to be more effectively analysed and would make operations automation easier to achieve. He characterised his favoured strategy for doing this as “federated and empowered”, a setup in which individuals are given responsibility and trusted to perform tasks on their own initiative.
By establishing these solid foundations, firms will be able to better understand their data and that will support their broader ESG strategy, said Paul Jones, Director, Data Analytics and AI Practice at Baringa Partners. With proper data governance, firms can get the most value out of their data and meet regulatory demands more fully, he added.
Getting those structures in place won’t be easy, said Hany Choueiri, Board Member, Sustainability and Vice Chair at Global Legal Entity Identifier Foundation (GLEIF), a point each member agreed.
The very nature of ESG data means it can’t be readily slotted into the same processes as the rest of a firm’s enterprise data.
Much of the data is unstructured and difficult to integrate with other datasets. For instance, social data – on such factors as race and gender – are “nebulous”, said Miller.
For other consumers, the lack of sustainability data – especially that linked to smaller companies, of which the majority of supply value chains are comprised – will present problems when it comes to creating a strong governance framework. That can be partly resolved by ensuring corporates are educated in identifying the information their investors need for their own reporting and disclosure obligations. To illustrate the importance of this, Miller used the example of a factory visit in which it was discovered the facilities manager hadn’t realised the installation of LED lights would have contributed to – and improved – the company’s overall sustainability performance.
Unstructured data has to be structured, but the act of reshaping it to fit into established systems poses challenges of its own.
Jones, for instance, argued that two companies may interpret the same dataset in different ways and, therefore, incorporate it into their systems differently. This, continued, Choueri presents potential regulatory hurdles and makes investor discrimination problematic: how can the assets of one of those two companies be chosen over those of the the other if their sustainability credentials differed only in the way they had interpreted identical datasets?
The wide variety of datasets – and the constant introduction of new formats – is also placing handicaps on firms as they seek to put cogent governance strategies together.
Once these are overcome, however, the data governance challenge is the same as that presented by an enterprise’s other data.
Chouerie said firms should leverage their existing technology to ensure ownership, data quality, dictionaries, glossaries and other vital factors are in place.
His co-panellists agreed, adding that systems should be designed to provide room for expansion and to accommodate changes as the ESG ecosystems, and the data that provides transparency into it, evolve and advance.
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