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New methods and models to understand the impacts of climate change
What are the most common challenges connected to IFRS9 model implementation and usage?
The current economic environment provides a significant challenge for lenders and how they will manage and report IFRS 9. The need for forward-looking estimates of expected credit loss under a range of economic scenarios has always been a particular challenge. The last three years have presented highly unexpected circumstances and lenders have had to adapt not only to represent that new reality, but also incorporate that into their modelling universe. The need to understand the sensitivity of the risk drivers to economic conditions requires analysis of historical data to demonstrate reasonable and supportable assumptions. The COVID-19 pandemic and the associated government support schemes provided a significant challenge to the relevance of recent data and in this most recent set of conditions, high inflation and higher interest rates are not something that has been seen in recent economic data, particularly with the post-2008 financial crisis where we had record low-interest rates and inflation. It is a significant challenge to maintain and ensure models are reliable and to incorporate adjustments into such models to be able to reasonably reflect a changing outlook where historic data may not include such conditions. It is also a challenge to know where that is not a suitable approach and where additional adjustments are required to the outputs from those models – so called post-model adjustments. When such adjustments are material it makes decision-makers uncertain what they can believe and rely upon, and auditors and regulators increasingly nervous. But, we cannot dictate our history (what has happened before), nor what will happen in the future (the forward-looking views) and so we must understand those realities and what can be extracted from them into our models and what else is needed to support IFRS 9 reporting. Compounding the current reporting is how inflation is manifesting in impacts in living costs for customers. This significantly affects what a customer can afford and their ability to repay their loans, however, it is highly nuanced and different for many customers requiring a granular approach to understand customer circumstances and what may affect them. Establishing confidence in any Post Model Adjustments to reflect the increase in risk requires up-to-date information in an area that many lenders do not maintain. Affordability is typically assessed and confirmed at origination, and occasionally when there is a major change to lending like an extension to credit or difficulty in payment, but having a regular view on customer affordability is something new. Setting any PMA for IFRS 9 purposes, is likely to require ongoing monitoring and reporting against expectations as such adjustments unwind. Any permanent effects need to be understood and incorporated into models and no doubt future scenarios will also need to be adapted to consider a wider set of outcomes in years to come.
What are the most expected major changes in the credit risk environment?
There are numerous changes in credit risk. It is a risk type that appears well understood – people often borrow and their obligation to repay borrowed money and interest. However, it is quite an advanced risk type in terms of processes for identifying drivers of risk and measurement and reporting of that risk. It is also the case that new drivers of credit risk can emerge. For example, Climate Change is driving new credit risks. If climate change results in more and greater impacts for flooding we will see more homes damaged and that has a real impact on the value and viability of property as collateral for mortgage lending. We are already seeing laws and legislation introduced to force certain polluting motor vehicles off the road, that also has the potential to change the value of vehicles and residual risk for some forms of lending. There are companies that produce high levels of carbon in their productions and the like and such companies may have a reduced demand, increased risk of penalties or through any number of ways their financial viability may be impacted by activism. There are so many ways in which climate change is going to affect credit risk. That requires new data to be captured, the melding together of traditional models with new drivers of risk and very different time horizons and considerations. We are already working with clients to develop new methods and models to understand the impacts of climate change. Data is a key part of this and as more extreme events occur, more data is captured about emissions and production of carbon and other contaminants we expect climate analysis and modelling into credit risk to be a key emerging area. Regulators are already requiring firms to understand their exposure to the Physical and Transition Risks of climate change through various stress testing exercises. These exercises are becoming more granular in nature and it is expected across the industry that this will start to influence how banks manage credit on a day-to-day basis. We are already seeing products designed to support consumers and businesses move towards energy efficiency and de-carbonisation and we expect climate risks to have a greater influence on all areas of bank operations moving forward, particularly with greater regulatory scrutiny, government initiatives, and growing consumer sentiment towards greener finance. It is also likely as impacts are better measured and scenarios developed that such measurements will become core requirements under capital and solvency rules.
What are the main challenges of the implementation of climate stress testing?
Likely the most significant challenge for stress testing going forward will be the incorporation of climate risks, both technically into stress test modelling capabilities, and operationally into capital requirements, risk appetite, and internal control frameworks.
On the technical side, both the BoE and the ECB have released their feedback on the climate stress test exercises carried out over 2021/22. Both reports highlighted the problems of obtaining, processing, and integrating climate risk data, and the need for lenders to use proxy data and estimates to fill data gaps. Similarly, lenders in both the UK and Europe faced challenges with using the full availability of climate risk information and linking climate risk to credit risk metrics in ways that satisfactorily transmitted these risks into forecasts of expected loss and capital requirements. Models were generally found to be in an early stage of development, making use of manual adjustments and simplifying assumptions, and leading to significant model-related variation in predictions among lenders. Both reports were optimistic, however, that as techniques continued to evolve, data frameworks developed, and lenders became comfortable with incorporating climate risk, the quality of climate risk stress testing would continue to improve and lenders would be able to satisfy the climate risk requirements of their respective regulators.
On the operational side, however, there is greater uncertainty. Almost certainly, as stated earlier, banks and insurers will be required to hold capital against climate risks in possibly many different ways, however, in the short term, it is not clear through what process this will take place. The recent publication by the Basel Committee on climate-related financial risks emphasises that climate risk should be a consideration in rating systems and risk weighting, but provides little practical guidance. We are working with some clients who are starting to incorporate climate data into their front-end-scorecard model developments. It will be for national supervisors to weigh in on such topics as integrating risks across multiple climate change scenarios, ensuring consistency in approach across lenders (where approaches may have to consider risk decades into the future), and incorporating climate risk into Pillar 1 vs. Pillar 2. None of this should prevent lenders from factoring climate risk into their risk appetite and control frameworks, however. In this, smaller and more specialised lenders have the advantage of being able to rapidly evaluate their portfolios, adopt climate risk policies, and adjust their risk appetite accordingly. For larger banks, material changes in risk appetite may have to wait until the issues surrounding risk data and linking risk to outcomes have evolved.
4most is a risk analytics consultancy delivering analytically led solutions globally in financial services and insurance. We work with firms that need insight and deep expertise in measuring and analysing risks including many unicorn FinTechs, mid-sized challengers and some of the largest global lenders and insurers. We offer complete bespoke solutions from design, build and embedding and we have many clients where that relationship continues on into new areas. Founded in 2011, we have grown to become one of the most respected independent risk and actuarial consultancies and are recognised as one of the most dynamic risk consulting firms globally. Please visit www.4-most.co.uk to learn more.