Needing access to better environmental, social and governance (ESG) data is crucial to helping the businesses of today achieve their ESG goals and ambitions. ESG factors are increasingly informing the decisions that financial services leaders make – from day-to-day operational choices to long-term strategic planning. In addition to the investment returns they generate; businesses are now also being judged on a broad range of ESG criteria.
As organizations work to deliver these broader goals, they must be transparent and account for their ESG performance to a wide range of stakeholders.
KPMG and Google Cloud investigate the ESG data challenges and opportunities facing the financial services industry and how with access to more detailed ESG data, financial institutions have an opportunity to secure competitive advantage while simultaneously improving their chances of delivering positive societal outcomes.This is the first report in our three-part series on how to close the ESG data disconnect in financial services.
The ESG Imperative
Many factors are putting ESG considerations at the center of financial services institutions activities, including customer demand in ESG products, the increasing need to embed the ESG agenda within their people strategies to attract talent, as well as the demand from their own investors and shareholders. To date, many organizations still lack the means with which to truly seize the agenda because of difficulties with the collection and curation of ESG data.
Responses from more than 100 banks, insurers and wealth management companies found they regarded the lack of available relevant data as the single greatest challenge preventing them from adequately addressing climate risk1. Each sector of the industry is facing its own data imperative and challenges.
The ESG data landscape
Before financial institutions can begin to think about defining and fulfilling their data needs, they run into a significant roadblock – there is no globally agreed definition of the term “ESG” and there are no standardized definitions of ESG reporting – either what it means or what is required.
The term “ESG” is often loosely and interchangeably used with descriptions such as sustainability and even in legislature, standardized terminology is sorely missing.
Currently, the single most important primary source of ESG data is businesses and other organizations making disclosures of sustainability-related information. These are self-collected and assessed. However, in the absence of any global agreement on harmonized disclosures, a broad range of standards and frameworks have been developed that financial institutions may be obliged by regulation to work with or not, depending on their jurisdiction. These include: The Global Reporting Initiative (GRI), The Sustainability Accounting Standards Board’s (SASB) standards, The Task Force on Climate-related Financial Disclosures (TCFD).
Common ESG data challenges
As a result of the lack of standardization in the data landscape and lack of consistency on the definitions of ESG itself, many financial services organizations face a broad range of challenges. These include:
In the absence of globalized and standardized ESG disclosure obligations, corporates are often free to decide whether to report non-financial information. Where they do disclose — voluntarily or otherwise — they have a choice of standards to take account of, making reporting difficult to compare with other organizations.
The weaknesses of primary ESG data feeds through the value chain and are magnified in the process. Data collectors and providers depend on self-assessed disclosures and interpret this data according to their own varying practices.
While aggregators of ESG data serve some useful purpose, they are often unable to independently verify data and their analytics engines are structured in different ways. The result is that their outputs may be at odds with each other. With the lack of standardization, agencies may award corporates very different ESG ratings and financial institutions are not always equipped to assess the accuracy of these ratings.
The quality and quantity of ESG reporting varies enormously by jurisdiction, by asset class, and by size of corporate. In many markets, there is very little ESG data for collectors and providers, or financial institutions themselves, to work with. Data is in short supply when it comes to smaller public corporates. There is also a lack of granularity on ESG impacts at very local levels.
Almost all ESG data is backwards looking — often significantly so given the extended timelines of corporate reporting. Every assessment of corporates’ ESG performance rate the organization on where it was at a point in time, rather than where it is today.
Many are short of the skills and tools they require to build their own ESG data analytics operations, leaving them exposed to the weaknesses of the ESG data industry. Legacy technologies and a shortage of data science expertise are significant problems.
Financial institutions cannot find all the ESG data they require from any one provider. This requires them to confront the inconsistencies of the ESG data industry, as well as the technical difficulties of compiling multiple data sources. They may also lack the expertise necessary to weigh the merits of different providers.
Beginning to fill in the gaps
The financial services sector needs to begin to confront the multiple ESG data challenges it faces, starting with the characteristics that a credible and coherent ESG data solution would offer.
The right solution needs to provide a data set that covers all of the entities in which an organization invests or does business with, provide information on every element of environment, social and governance, as well as the means which with to compare performance on key issues in each of these areas across the portfolio.
The solution also needs to enable firms to gather information from multiple perspectives in a timely way.
There is no ‘one size fits all’ answer to the ESG data challenge as the needs and use cases of individual financial organizations are very different.
Closing the ESG data gap is likely to require significant investment in new skills and resources. It will require new data sources, new tools and methodologies to access these new data sets and leverage actionable insight from them and technology capable of delivering insight at scale.
The business case for change
There is significant work to do to rise to the challenges that ESG data presents, but with challenges come opportunities – whether it be building new value propositions and developing new products and solutions for clients that add value, or maintaining competitive advantage and driving sustainable growth.
Leveraging ESG data can open a plethora of exciting new propositions across the financial services industry. There is every opportunity to do well at the same time as doing good. Is your organization ready?
KPMG and Google Cloud working to drive innovative business outcomes
KPMG and Google Cloud are working together to make new advances in ESG data science. Our aim is to drive innovative business outcomes as ESG scoring, reporting and assurance for financial services companies evolve at pace. With data and analytics as critical components to any ESG assessment, Google Cloud provides the engine needed to power more sophisticated reporting and scoring models.
More broadly, the combination of KPMG and Google Cloud can help drive business transformation across Asset Management, Banking, Capital Markets, Insurance, Private Equity and Payments. We can support your innovation, customer experience, security, and compliance needs. Contact us to learn more.