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PremiumRBI should quickly get our lenders to enhance their climate risk management capabilities
In line with other central banks (CBs) globally, the Reserve Bank of India (RBI) has increasingly been highlighting climate risk and its potential impact on banks’ lending books. In advanced economies (AEs), CBs have already started stress-testing the impact of adverse climate scenarios on their banks’ portfolios and equity capital. While methodologies for climate risk management are still evolving, it is clear that it would require banks to ramp up their capabilities very significantly. An assessment by the European Central Bank (ECB) of its 112 supervised banks found that 90% of their climate-related and environment risk practices did not meet its expectations. It also found that 50% of these institutions face material climate-related risks over a three-to-five year horizon.
Despite its pockets of excellence, Indian banking in general suffers from a comparative atrophy of risk management capabilities. This may be attributable partly to some regulatory leeway provided by an otherwise strict RBI. If Indian banking is to comprehensively meet its climate risk management challenges, it must rapidly enhance its capabilities.
How could climate risk impact a bank’s portfolio?: It may impact borrowers in two ways. First, by way of physical losses due to adverse events like a sea-level rise, droughts and weather fluctuations. The second and more immediate is the transition impact. As the global financing system moves towards green financing and various stakeholders show a preference for dealing only with green companies, some business borrowers may end up with unsupportable or unfunded business models and stranded assets. Central banks are stress-testing possible portfolio losses attributable to such impacts.
Challenges of risk management: In this initial phase, banks face at least two major challenges, one of definition and data, and the other of quantitative modelling. Definitions of ‘green assets’ are not consistent across countries. Even within the same country, asset tagging is more of an ‘accounting’ issue and the capacity for physical validation of claims and measurement of emissions at scale is limited. Regulator-suggested normative emission values often leave scope for manipulation, thereby posing an audit challenge. Thus, the mapping of assets to emission or climate-risk sensitivity is a data challenge. In addition, portfolio behaviour with respect to weather fluctuations has not been systematically studied by most banks. Besides , climate impacts play out on a decadal scale and the best risk models go only as far as 5 years. Given these challenges, not to mention the uncertain nature of the problem itself, stress testing by using exhaustive alternate scenarios is currently among the most robust approaches.
The self-inflicted atrophy of risk-management skills: Banks in AEs and several emerging nations have done better on developing advanced risk capabilities, including the use of cleaner risk data, institutional skills of risk analysis and the embedding of the same in their business. This can be attributed to their adoption of three regulatory requirements.
The first is the Internal Rating-Based (IRB) advanced approach.This requires an internal capability to develop credit probability of default (PD) and loss given default (LGD) models and then assess unexpected losses to calculate capital requirements.
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Second, IFRS9 (IND-AS) requires forward- looking assessments of a portfolio loss rate.
Third, bank-level stress testing requires the development of various macro-economic scenarios to stress-test portfolio losses.
For a plethora of understandable reasons, RBI has not pushed for comprehensive adoption of the above. While a few Indian banks have these capabilities, many remain weak on these dimensions.
So, while most banks may think they have 5-7 years of data, say, to build a LGD model, few actually have the clean data needed for modelling. Many banks fail to realize this because there was no regulatory requirement to build risk models on the basis of through-the-cycle databases.
Likewise, predictive modelling skills are more focused on retail loans, while banks have little proven capability for corporate-risk modelling on sparse data, or models with tenures more than 12-18 months. Also lacking is a robust portfolio-loss prediction ability under diverse macro-economic scenarios. With the exception of a few banks, most perform analytically shallow stress-testing, usually done more to meet compliance requirements than to understand and quantify the impact on loan books.
In short, the building blocks needed to handle climate risk are weaker than desired.
A stitch in time…: Banking regulations are a matter of the regulator’s discretion in terms of their degree of sophistication and time schedules of implementation. As a case in point, the IND-AS implementation in Indian banks has been continually postponed. However, climate risk is different. Regulators cannot afford to indefinitely postpone the adoption of climate risk management practices without impacting the stability of banking systems. Thus, RBI needs to prepare Indian banks for tackling the climate risk challenge and must strengthen the building blocks for this. A possible start may be to initiate parallel runs of the IRB advanced approach and IND-AS among Indian banks.
Thankfully, the books of Indian banks are in much better shape than before in terms of systemic equity capital and non-performing assets. This may therefore be an opportune moment to start the exercise. The clock is ticking. Let’s transform this challenge into an opportunity to enhance Indian banking’s risk management capabilities.
Deep Mukherjee is a quantitative risk management professional and a visiting faculty of risk management at IIM Calcutta
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