PRA policy statement PS23/25 and an amendment to supervisory statement SS5/25 sounds at first glance much like a less than riveting read for a bank’s legal department. The regulations relate to climate related financial risks and so one might expect a bank’s ESG team to take a close interest.
The regulations are however no mere set of guidelines, of interest to a small number of executives.
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In brief, the new rules aim to set a new regulatory bar for how banks and insurers should manage climate-related risks. And the provisions should catch the attention of all the C-suite. The rules highlight the policy goal to shift from raising awareness to embedding consistent and effective risk management practices.
Levent Ergin, Chief Climate, Sustainability & AI Strategist at Informatica from Salesforce, argues that siloed or incomplete data can leave boards and risk teams unable to identify exposure before assets become impaired, uninsurable or commercially unattractive. That sort of risk ought certainly to grab the attention of the entire C-suite.
Given his wealth of banking experience – past senior banking roles include Global Head of Customer Data Governance and Data Risk & Controls Remediation at HSBC, Global Head of Reference Data at Deutsche Bank and Group Basel 3 Data Governance Lead at RBS/NatWest, Ergin is well qualified to comment on how UK banks must act in response to the new regs.
And he tells RBI that all is not doom and gloom, additional regulatory expense and oversight. In particular, he explains how AI-enabled risk intelligence can help firms move from backward-looking reporting towards more forward-looking resilience planning.
RBI: Can you summarise the importance of the new regs and why you have argued that the PRA deadline marks a shift from climate ‘awareness’ to embedded prudential oversight?
Levent Ergin, Chief Climate, Sustainability & AI Strategist at Informatica from Salesforce:
I describe this as embedded prudential oversight because firms are being asked to understand where climate-related risks sit across assets, counterparties, properties, supply chains and portfolios, how those risks could affect resilience over time, and where there are gaps in their current approach.
Boards are also expected to have the information they need to challenge decisions and oversee the response. Financial institutions are expected to understand climate risk, assess resilience under different scenarios and make decisions based on that understanding. That is very different from treating climate risk as a standalone reporting exercise.
RBI: What evidence is there for the argument that climate risk is increasingly being treated as a balance sheet, resilience, and governance issue, not just an ESG reporting exercise?
Levent Ergin: For me, the strongest evidence is the focus on asset-level exposure. Firms are being asked to understand which assets, counterparties, properties, supply chains and portfolios are exposed to physical and transition risks, and how those risks could affect resilience over time.
This is not just about reporting. If firms cannot connect climate risks to the assets sitting on their balance sheet, they risk mispricing exposure or failing to identify issues before assets become impaired, uninsurable or commercially unattractive.
That brings climate risk much closer to financial resilience and business performance. The discussion becomes less about what organisations disclose and more about understanding where risk sits and how it could affect the business.
RBI: Can you explain why siloed or incomplete data can leave boards and risk teams unable to identify exposure before assets become impaired, uninsurable or commercially unattractive
Levent Ergin: “You cannot manage climate risk if you cannot see where it exists.” The challenge for many financial services firms is that the data needed to understand exposure often sits across different systems and datasets.
A lender may have information about a property, for example, but struggle to connect that information to location-based climate risks. That makes it harder to identify areas of exposure within a portfolio and understand how those risks are changing over time.
Without a clear view of the underlying data, boards and risk teams can miss risks until they begin to affect asset values, insurance availability or commercial viability.
RBI: In what way is AI-enabled risk intelligence helping firms move from backward-looking reporting towards more forward-looking resilience planning
Levent Ergin: A lot of climate reporting tells you what has already happened. AI is helping firms combine internal exposure data with geospatial, satellite and remote-sensing information so they can see how risks are developing across assets and locations as conditions change.
That creates a more complete picture of physical and transition risks than organisations can get from reporting alone. Firms can bring together information about assets, properties and portfolios with data on environmental conditions and potential climate impacts.
Risk teams have a broader range of information available when assessing resilience under different scenarios. They can use those insights to support planning, lending, investment and insurance decisions, and to better understand how climate-related risks may affect assets over time.
RBI: And something on the Informatica value proposition? How is the firm working with financial services clients to ensure compliance here?
Levent Ergin: “The foundation for all of this is trusted data and trusted context. Financial institutions cannot assess climate-related risks effectively if information is fragmented across different systems, business functions and datasets.
Our role is to help organisations create governed, connected, trusted and traceable data environments so risk, finance, compliance and business teams are working from the same trusted information. That requires master data management capabilities such as lineage, quality and governance.
For financial services firms, that becomes particularly important when climate-related risks need to be understood across assets, portfolios and counterparties. The more confidence organisations have in the underlying data and context, the better positioned they are to support risk assessment, reporting and decision-making.
