Climate Risk Data Strategy

Climate-related risk is becoming a more accepted and integrated part of banks’ risk management. However, rather than be positioned as its own distinct risk type, climate-related risk impacts are often integrated into existing credit, market, and operational risk capabilities. This means that while Environmental, Social and Governance (ESG) is often led by a dedicated sustainability function, climate risk initiatives often have enterprise-wide data management, governance, and architecture implications – similar to those of BCBS 239, Effective Risk Data Aggregation and Risk Reporting – that span across functions and business units.

 

With many banks considering their strategic response to climate-related risks and the wider topic of ESG, there is a real threat that the operations that support banks’ newly developed ESG strategies will languish or worse, remain as tactical ad hoc solutions with little consideration for the longevity of the firms’ ESG data strategy and greater operating model.

 

 

In order to avoid “snowballing” data issues – including disparate data sources, limited controls and oversight, poor data quality and ineffective data governance – Monocle stresses the need for an effective and co-ordinated climate risk data strategy. This means applying the same effort and foresight that is afforded to traditional risk types to meet future compliance requirements and audit scrutiny, as well as service the needs of cross-enterprise stakeholders.

Driving out a climate risk data strategy

 

 

It is telling how climate-related initiatives globally are progressing when we find that 41% of banks disclose their boards’ oversight of climate-related risks and opportunities, while only 28% disclose their managements’ roles in assessing and managing these risks and opportunities.(1) In Europe, related bank progress is more advanced but still disparate, with board and managerial governance sitting at 68% and 55% respectively. Operational activities, particularly those related to the assessment and management of climate-related risks and opportunities, have yet to hit their stride.

 

Banks’ strategic vs operational priorities

 

Heads of Sustainability alongside Chief Data Officers are best positioned to take ownership of their banks’ climate risk data strategies. However, without management’s deliberate and active involvement in co-ordinating and driving out a bank’s climate risk data strategy, impacted activities – such as credit pricing, onboarding, stress testing and regulatory reporting – will continue to operate in silos. This often leads to data and process redundancies, and inevitably technical debt.

 

A common example of these shortcomings is that many financial institutions have isolated sustainability reporting teams at the group level that often complete regulatory reporting without active engagement and co-ordination with business stakeholders.

Adding “climate risk data” as a standing agenda item across relevant committee meetings, launching a formal climate risk data program, and raising awareness across business functions are starting points for proactive engagement across the bank.

Finding your starting point

 

 

 

Nonetheless, many climate data use cases will share similar data requirements. For example, banks are maturing their scope 3 (financed) emission reporting capabilities. However, this data is also required for setting and monitoring strategic emission targets set by the board. It is equally pivotal to credit teams when structuring sustainable finance deals.

 

These data synergies should be identified early on. As discussed above, bank functions including finance, risk, compliance and sustainability should be actively engaging with one another regarding their climate risk activities. These activities include: data sourcing and transformations, data ownership, agreeing upon data definitions and various other critical data management and governance decisions.

Leveraging an integrated data architecture

 

 

A lack of strategic investment is a common denominator across most deficient bank data capabilities. From the outset, banks have the opportunity to proactively drive out an integrated climate risk data architecture as a part of their risk data strategy, with considerations for enterprise-wide data management and governance. When considering this, there are two leading factors:

1. Centralised data platform

Many financial institutions have pursued a centralised data vision through solutions like enterprise-wide data warehousing and single source of information. Climate-related data should be treated in a similar fashion – developed into existing centralised data platforms that are integrated with established finance and risk systems as well as external third-party data platforms. As climate-related regulation and policy is often framed as an institutionwide initiative, a centralised approach allows for the enforcement of data standards and data governance across functions.

This also allows for the development of a centralised ESG data model to accommodate various downstream application and use cases. Additionally, critical data management processes such as those related to data lineage, data quality and importantly, data ownership can also be embedded and managed centrally. Practically, data quality tools and dashboards should be considered to monitor and improve data quality – particularly as climate-related data becomes more readily available. Data ownership can also be enforced through documented responsibilities to support the effective use of datasets that are becoming increasingly utilised across functions, such as scope 3 emissions and client transition targets.

 

Integrating climate-related data into a centralised data platform

 

2. Standardised data definitions

While there are various considerations surrounding data management, it is critical to establish consistent, firm-wide climate risk data definitions from the outset. This is particularly important as banks are expected to source and store novel and unfamiliar datasets such as GHG emissions or geospatial coordinates that will be utilised by various bank stakeholders. Standard data definitions with comprehensive metadata ensures semantic clarity and ensures data users know how it should be interpreted and used.

Additionally, climate data is set to become more reliable, granular and available over the medium term as assumptions and proxies become more accurate, counterparties disclose more non-financial data and third-party services become increasingly mature. From an implementation perspective, banks will need to be flexible in their ESG data strategies and continue to drive cross-function and cross-business unit engagement as the ESG data landscape evolves.

How Monocle can assist?

 

 

With over 20 years of expertise related to data intensive risk, finance and regulatory projects for our banking and insurance clients, Monocle has extensive expertise, not only, in the execution of our clients’ strategic data projects but also a deep understanding of the operational mechanisms and considerations that underlie an effective data-driven
enterprise.

We assist our clients on the front line of their climate risk and greater ESG initiatives, including physical and transition risk modelling as part of banking book credit risk; emissions data sourcing and financed emissions calculations; and ESG and climate-related reporting and dashboarding. Moreover, we are thoroughly familiar with the various process, people, system and policy challenges that arise from developing cutting-edge climate risk intellectual property. Critically, we approach all ESG initiatives with the intention of designing and implementing long-term and robust deliverables, which form part of the mature and established finance, risk and compliance solutions for our clients.

1. TCFD, 2023 Status Report, 466 international banks surveyed (expanded population)

2. Ibid