Environmental, social, and governance (ESG) strategy in financial services is inextricable from data. Sound decision-making and compliance rely on well-crafted ESG data and analytics processes, data management, and reporting frameworks.
Here, we’ll unpack ESG risk regarding data strategy and compliance, how your firm’s long-term aims should shape its ESG data management, and how ESG data and analytics must underpin decisions moving forward.
ESG in finance is a monumental data challenge, for several reasons. Thorough ESG data and analytics involve gathering new data inputs (beyond your organization itself, both downstream and upstream). Many of these are likely to be unstructured and open to varying interpretations. ESG reporting frameworks can also be unclear and even contradictory across jurisdictions, all while requirements continue to evolve.
To rapidly respond, the majority of financial services firms have tacked on ESG to their current data architecture. Yet this is risky. If each business unit is left to define distinct ESG data requirements and collection processes, the overall effect will rapidly be confusion, not clarity. Instead, an aligned, organization-wide, and long-term approach is needed.
Avoid creating the same old silos, just with new ESG data, by considering your firm’s long-term strategic needs. Fundamentally, you’ll want to avoid duplicate data, workloads, and unnecessarily high costs. Likewise, you’ll be aiming to enable aligned decision-making for successful firm-wide initiatives.
The solution is an ESG data platform that offers a single source of composable data for business users company-wide. Built and managed well, it will supply a compliance-guaranteed, shared view of the data many teams will need: Climate risk, counterparties (customers, suppliers, and investments), aspects of the firm’s own ESG status, and so on.
ESG metrics, objectives, and stakeholder priorities within the financial services sector are many and varied. As such, decision-making in the sector will gain additional nuance, requiring support from top-quality ESG data and analytics. Richer, (un)structured data sets and new analytical approaches will be needed to interpret more complex scenarios, both at present and in the future.
Our recent whitepaper on overcoming ESG challenges in finance delves deeper into the topic of data and more, as well as outlining actionable first steps to creating your firm’s ESG data platform.