Tackling growing pains: ESG Data Management is coming of age
Until recently, investing according to ESG criteria was the remit of specialist companies known as green or impact investors. These investors would have their own in-house data collection processes and their proprietary screening or selection criteria to assess potential investments. Although there were different reporting frameworks in places such as the PRI and GRI standards, the absence of standard data collection, integration, and reporting solutions required them to create their own “ESG data hub” to provision their own analysts, front office, and client reporting teams. As ESG investing has become mainstream due to both a regulatory push as well as an investor pull, ESG information management is fast becoming mainstream for research, asset allocation, performance measurement, operations, client reporting, and regulatory reporting.
With the deadline for key ESG regulations like SFDR fast approaching, asset managers and asset owners must do more to anchor ESG data into their end to end workflow processes. Simply having a source of ESG data to feed to the front office is not sufficient as businesses need this data from across the organisation to integrate into the whole investment management process – from research to client and regulatory reporting.
ESG integration is needed across buy-side and sell-side business processes
Any firm that sells or distributes investment products into the European Union will have to follow the SFDR regulation. SFDR requires firms to report on 18 mandatory Principal Adverse Impact (PAI) Indicators as well as some optional ones. Paradoxically, the reporting requirements for publicly listed companies that asset managers invest in lag behind the SFDR timetable. This causes an information gap and the need to supplement corporate disclosures with third party ESG scores, expert opinion as well as internal models to come to an overall assessment of ESG criteria.
There is also a need for ESG-data on the sell-side of financial services. For instance, in corporate banking, ESG data is increasingly crucial to support customer onboarding and, in particular, Know Your Client (KYC) processes. Banks will have to report their ‘green asset ratio’ – in essence, the make-up of their loan book in terms of business activities of the companies they lend to according to the EU Taxonomy.
In the future, if a company signs up to get a loan from a bank as part of the screening criteria, it will be asked to disclose what kinds of business activities it is involved in and what kinds of sustainability benchmarks it has in place.
Banks and other sell-side financial services firms will also frequently screen their suppliers, as part of a process called Know Your Third Party (KY3P). They will want to know who they are doing business with, so they can then report this in their own Annual Report. Banks will also want to climate stress test the products they hold in their trading book for their own investment against certain climate scenarios. The ECB, MAS as well as the Bank of England have all incorporated climate stress test scenarios in their overall stress testing programmes to gauge the solvency and resilience of banks.
ESG data also has a role to play in the way banks manage their mortgage book as they are increasingly looking for geospatial data, for example to work out the flood risk of the properties they finance.
Both sell-side and buy-side financial services companies will also need to integrate ESG data with data from the more traditional pricing and reference providers to give a composite view, incorporating not just the prices of instruments and the terms and conditions but also the ESG characteristics.
ESG data now needs to spread across the whole of the organisation, integrating with all the different data sets to provide a composite picture, becoming a key source of intelligence, not just for the front office but also for multiple business functions.
ESG data challenges
Common ESG data challenges firms encounter as they develop their ESG capabilities include data availability, usability, comparability and workflow integration. Many corporates do not report the information investment managers require for their decision making or indeed their regulatory reporting. This leads to the need to combine corporate disclosures with third-party estimates and scores, as well as internal assessments.
Usability issues include the disparity in methodologies third-party firms use to estimate or score firms on ESG criteria. Rating firms have their own input sets, models and weights and often come to different conclusions. Compared to credit ratings, the correlation between the scores given to a firm by different rating agencies is lower. However, credit analysis is as old as the banking industry and the metric gauged (probability of default) is clear. It could be that, with increased global disclosure standards under IFRS, ESG scores will converge.
Comparability issues in ESG are exacerbated by different standards, different reporting frequencies or calendars and also the lack of historical data to track progress and benchmark performance over a longer time period.
The biggest issue however is how to anchor the ESG data in a range of different business processes to put users on a common footing – which requires the capability to quickly onboard users, reports and business applications onto a common set of quality-vetted ESG data.
Accessing ESG data and ensuring it is of good quality, comparable with other ESG data sets and well-integrated within existing workflows can be difficult.
Organisations will need to cross-reference, match and combine the data, as well as assimilate it with traditional data on companies and their financial products. Traditional prices and security terms and conditions of financial services providers will help build a composite picture from those different sources.
However, data management solutions and Data-as-a-Service offerings are now available to help firms get the ESG information they need, the capabilities to quality-check, supplement and enrich it with their own proprietary data or methods and the integration functionality to put users and applications on a common footing. This will enable firms to have an ESG data foundation for their end-to-end investment management processes on which they can build – for asset allocation, operations, client reporting and regulatory reporting alike.
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