Access to high quality, reliable environmental, social and governance (ESG) data enables businesses to achieve their ESG ambitions. In the financial service sector, business leaders are now looking into ESG factors on a regular basis to inform their decisions —  from day-to-day operational choices to long-term strategic investment and planning.

In this report, KPMG and Google Cloud explore the challenges financial services faced when attempting to gather high quality ESG data. Detailed ESG data will provide financial institutions with a great opportunity to secure competitive advantage while continuously driving environmetally and socially sustainable actions.

The ESG data landscape

Despite many factors putting ESG principles at the centre of financial services institutions activities — including customer demand in ESG products — fulfilling their data needs proves to be a constant struggle. There is no globally agreed definition of the term “ESG” and there are no standardised definitions of ESG reporting – either what it means or what is required. In the absence of any global agreement on harmonised 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

The lack of standardisation in the data landscape and the lack of consistency on the definitions of ESG itself bring various challenges:

  • ESG data is voluntary, inconsistent, and difficult to compare

    ESG data is voluntary, inconsistent, and difficult to compare

    With the lack of standardised ESG disclosure obligations, businesses tend to use different templates and standards to report on their ESG activities, making the reports difficult to compare.

  • ESG data is compromised by interdependence

    ESG data is compromised by interdependence

    The weaknesses of primary ESG data feeds through the value chain are magnified in the process. Data collectors and providers depend on self-assessed disclosures and interpret this data according to their own varying practices.

  • Data collectors and providers’ outputs are unverified and inconsistent

    Data collectors and providers’ outputs are unverified and inconsistent

    While ESG data aggregators serve some useful purpose, the lack of reporting standardisation often results in agencies awarding corporates very different ESG ratings and financial institutions don't have the means to verify the accuracy of the data.

  • ESG data is patchy and often out of date

    ESG data is patchy and often out of date

    The quality and quantity of ESG reporting varies enormously by jurisdiction, by asset class, and by size of the company. Data is in short supply when it comes to smaller public organisations. There is also a lack of granularity on ESG impacts at very local levels.

    To make matters worse, almost all ESG data is backwards looking. Every assessment of businesses’ ESG performance rate the organisation on where it was at a point in time, rather than where it is today.

  • Financial services organisations lack their own ESG data competencies

    Financial services organisations lack their own ESG data competencies

    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.

  • There is no single source of the truth

    There is no single source of the truth

    Evolving work patterns, climate change and the need for greater connectivity demand a rethink of our approach to places, suburbs and precincts.

    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.

Enhanced ESG data system will open up exciting new opportunities

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 to deliver actionable insights at scale.

The right solution needs to provide a data set that covers all of the entities in which an organisation 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 across the portfolio. It also needs to enable organisations to gather information from multiple perspectives in a timely manner.

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 wide range 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 organisation ready?

KPMG and Google Cloud collaboration 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. 

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