What is decision-ready ESG data for risk integration?
ESG risk integration is no longer a matter of preference or positioning. In the EU, it is a regulatory requirement tied directly to fiduciary duty, risk management, and capital allocation. For asset managers, SFDR requires sustainability risks to be integrated into investment decision-making processes across all asset classes, including credit-related exposures. For banks, this obligation is reinforced by supervisory expectations set out by the European Banking Authority, which require ESG risks to be identified, assessed, and managed as part of core risk management frameworks.
Importantly, this obligation is not weakened or altered by the SFDR 2.0 proposal for asset managers, nor by ongoing discussions on disclosure simplification. At the same time, EBA supervisory expectations for banks continue to tighten, with ESG risks increasingly treated as standard risk drivers rather than sustainability add-ons.
Yet despite widespread adoption of ESG data, many institutions are still not decision-ready.
ESG risk integration is not ESG reporting
A fundamental problem in today’s market is that ESG data is often confused with ESG risk intelligence.
Many ESG data vendors focus on presenting corporate ESG data in a structured, visually appealing way. Scores, pillars, heatmaps, dashboards. These are useful for reporting, benchmarking, and communication. They are far less useful for meeting SFDR risk integration requirements for asset managers or EBA supervisory expectations for banks.
ESG risk integration requires something different. It requires understanding how sustainability risks can affect enterprise value, creditworthiness, cash flows, and downside exposure. This is central to SFDR for asset managers, and explicitly reflected in EBA expectations for banks, where ESG risks are expected to be considered in combination with traditional financial risk drivers in credit assessment and portfolio monitoring.
There is a critical distinction between corporate ESG data and ESG research data. Corporate ESG data reflects disclosures, policies, and stated ambitions. ESG research data interprets those disclosures through a risk lens, assesses credibility and gaps, and links them to material risk drivers.
Only the latter is decision-ready.
Only understood risks can be integrated
Regulators are increasingly explicit on this point. Sustainability risks cannot be integrated mechanically. They must be understood.
Understanding risk requires analysis. It requires assessing what a company says about its sustainability risk exposure, governance, controls, incidents, and mitigation measures, and evaluating how this aligns with the risk profile of its actual activities. For asset managers, this underpins SFDR-aligned investment decisions. For banks, it reflects EBA expectations around explainability and traceability of ESG risk assessments at counterparty level.
This cannot be achieved through generic scores alone. A score does not explain what the risk is, why it matters, how severe it could be, or where the uncertainty lies. For banks, this lack of explainability creates a direct supervisory vulnerability where ESG factors influence credit decisions, pricing, or risk appetite. For asset managers, it undermines the credibility of ESG risk integration under SFDR.
Decision-ready ESG data therefore starts with structured sustainability risk assessment, grounded in company communication and interpreted against a clear risk framework.
ESG risk assessment must be activity-specific
A company’s sustainability risk profile is driven by what it does, not by what it calls itself.
To assess the total sustainability risk of a company, institutions must have a clear and explicit view on sustainability risk materiality across different types of activities. Manufacturing, extractives, financial services, technology, infrastructure, agriculture, and real estate all face different sustainability risk drivers. This activity-specific perspective is critical both for SFDR-aligned investment analysis by asset managers and for EBA-aligned credit risk frameworks in banks.
Without an activity-specific materiality lens, ESG risk integration becomes superficial. Risks are either overstated, understated, or misclassified. This leads to poor capital allocation and weak defensibility under regulatory or supervisory review. In a banking context, it also undermines the credibility of ESG risk treatment within loan origination, internal rating systems, and portfolio monitoring.
Decision-ready ESG data therefore requires a sector-aware, activity-based risk taxonomy that translates sustainability topics into financially relevant risk areas.
Build internally or buy externally
Institutions essentially face two options.
They can build sustainability risk assessment capabilities internally, or they can source them externally.
Building internally is possible, but it is not trivial. It requires specialist sustainability risk competence, sector expertise, regulatory interpretation, and scalable analytical infrastructure. For asset managers, this includes alignment with SFDR methodologies and disclosures. For banks, it also requires alignment with credit processes, governance structures, and documentation standards expected under EBA supervision. For many institutions, this quickly becomes resource-intensive, costly, and difficult to maintain at the required level of consistency.
Buying externally can be efficient, but only if the provider delivers true sustainability risk research, not just repackaged disclosures or opaque scores. Both asset managers and banks remain fully responsible for how externally sourced ESG risk inputs are used within investment or credit decisions. From a supervisory perspective, outsourced ESG risk inputs must still be explainable, auditable, and defensible.
If the ESG data cannot be explained, challenged, and traced back to underlying company statements and risk logic, it is not decision-ready.
Fiduciary duty applies to all decisions, including credit
A common blind spot in the market is credit.
Many global ESG data providers focus primarily on listed equities. Coverage in private markets, corporate lending, project finance, and SME exposure is often limited or inconsistent. However, EU regulation does not make this distinction.
SFDR requires asset managers to integrate sustainability risks across all investment decisions. In parallel, EBA supervisory expectations require banks to integrate ESG risks into all credit risk assessment, loan origination, and portfolio monitoring across corporate lending and bank loan books. Credit is therefore not an exception, but a core focus area for both groups.
Supervisors increasingly expect ESG risks to be assessed in a forward-looking and activity-specific manner, with clear articulation of how these risks influence investment decisions for asset managers and credit decisions, pricing, and risk appetite for banks. Generic scores or high-level ESG indicators do not meet this expectation.
Regulatory pressure will increase, not decrease
Supervisors are moving from high-level expectations to detailed scrutiny. Institutions are already being asked to explain methodologies, assumptions, and data sources. Over time, tolerance for vague explanations and black-box scores will decline.
For banks, ESG risk integration is becoming a standing supervisory topic under EBA oversight. For asset managers, ESG risk integration under SFDR is increasingly tested through regulatory review, investor scrutiny, and enforcement. In both cases, the ability to demonstrate structured, explainable, and decision-ready sustainability risk assessment is becoming a prerequisite for defensibility.
This is not only a compliance issue. It is a strategic one. Institutions that invest early in decision-ready sustainability risk intelligence will be better positioned to allocate capital efficiently, price risk accurately, and respond to regulatory change without constant remediation.
Conclusion
Decision-ready ESG data is not about more data. It is about better risk understanding.
It is data that translates company communication into structured sustainability risk assessments. Data that is grounded in activity-specific materiality. Data that can be explained to regulators, supervisors, investment committees, and boards. And data that can be integrated consistently across investment and credit decisions in line with SFDR requirements for asset managers and EBA supervisory expectations for banks.
As regulatory expectations tighten, the cost of not having decision-ready sustainability risk intelligence will only increase.
The real question is not whether sustainability risk integration is required. That question is settled.
The question is whether your organisation is ready to do it properly. What do you choose?
