Rethinking Macro Hedging: What are the Key Components of the DRM Model?

April 2024
7 min read

The aim of the DRM model is to tie together hedge accounting with risk management strategy so that an entity’s effort to mitigate interest rate risk is better reflected within their financial statement.


In the second instalment of the Zanders series on the DRM model, the Risk Management Strategy (“RMS”) and the DRM process are introduced and with it the new concepts that the IASB have established. The RMS sets out how an entity will manage its interest rate risk, which is the basis of every other part of the DRM model. The IASB has laid out the following expectations for a company’s RMS1:

  1. Process to approve and amend RMS 
  2. Risk management levels and scope of assets and liabilities 
  3. Risk metrics used 
  4. Range of acceptable risk limits (i.e. the target profile) 
  5. Risk aggregation method and risk management time horizon 
  6. Methodologies to estimate expected cash flows and/or core demand deposits. 

Changes to the RMS that result in a change in the target profile (“TP”), lead to a discontinuation of the hedge2. The IASB will further deliberate on when the discontinuation occurs and whether such changes lead to discontinuation of the model at a future date3.

The overall aim of the model is to compare the target profile (“TP”) with the current net open positions (“CNOP”) and thereby produce a risk mitigation intention (“RMI”), which represents the amount of risk that the entity intends to mitigate through the use of designated derivatives. The IASB has tentatively decided that each separate currency should have its own DRM model. 

Below a figure of the DRM process can be found that shows how the different components of the model relate to each other. In the following sections a detailed explanation will be provided for each of these elements.

Figure 1: DRM process

As part of the RMS the entity is required to define the target risk metric. The company cannot change this metric for each period and must stick to the metric specified within the RMS. However, the RMS can specify the use of a different metric over different future time horizons. E.g. the company’s RMS could be to stabilise NII for the first three years on notional exposure and then the present value using PV01 for the following years.  

Current Net Open Position 

The first step in implementing the model is to decide on the assets and liabilities that should be hedged through the DRM framework. The eligible assets and liabilities are currently: 

  • Financial assets or liabilities must be measured at amortised cost under IFRS 9 
  • Future transactions that result in financial assets or financial liabilities that are classified as subsequently measured at amortised cost under IFRS 9 ($4.2.1). 

Furthermore, the IASB has imposed the following criteria on the eligible assets/liabilities that can be designated in the CNOP4, 5; an asset/liability is only eligible if all the criteria are met: 

No.Eligibility criteria for the Assets/Liabilities as hedged items 
1The effect of credit risk does not dominate the changes in expected future cashflows.
2Future transactions must be highly probable except in the case of transactions that are the reinvestment or refinancing of existing financial assets/liabilities6
3Items already designated in a hedge accounting relationship are not eligible. 
4Items must be managed on a portfolio basis for interest rate risk management purposes. 

Table 2: Criteria for Assets & Liabilities

An asset/liability is eligible for the CNOP if all the above criteria are met. The IASB has explored other eligible assets/liabilities and have concluded that assets/liabilities that are FVOCI7 are recommended to be eligible while the ones that are FVPL8 were not recommended to be eligible. Equity was deemed not to be eligible for designation in the CNOP. Since the DRM model is still under review, the eligible assets/liabilities could change before the draft is finalised. Therefore, we advise companies to stay up to date with the latest information. 

Target Profile 

The Target Profile (TP) is linked to a company’s RMS. It sets the risk limits on the CNOP, before risk mitigation actions can be initiated. When the company assesses the risk over different time buckets, it needs to be consistent with the company’s RMS. All of this should be clearly documented within the company’s RMS. The TP should be set at the time when the hedge relationship is designated. The company can also take action to mitigate risks even before the limits are breached. Stakeholders have raised concerns regarding the granularity for the TP. Therefore, the IASB will conduct further research in this area to identify a common principle to be used universally for the allocation of risk limits for the TP.9

Risk Mitigation Intention 

The Risk Mitigation Intention (RMI) is a calculated metric based on the company's efforts, through the use of derivatives, to reduce its CNOP for each period to align with the TP outlined in the RMS. Once the RMI is set, it cannot be changed retrospectively. When an entity is deciding on its RMI the following should be considered10

  • The RMI cannot exceed the CNOP. When entities monitor their CNOP by time buckets, this must hold for any time bucket 
  • The RMI needs to transform the CNOP position to a residual risk position that sits within the TP 
  • The RMI needs to be evidenced by real actions taken such as the actual derivates traded in the market 

Stakeholders have been concerned that they may not be able to faithfully mitigate the risk with market traded instruments due to liquidity. E.g. there may be little liquidity for a nine-year interest rate swap to hedge an asset that reprices in nine years in the CNOP. Therefore, the IASB has tentatively stated that an entity could use a 10-year swap for a 9-year hedge. Then in the model the RMI is set to be 0 for the 10th year and the benchmark derivative matures on the 9th year. Therefore, the misalignment due to the extra year for the designated derivative would be reported in the profit and loss11.  

Designated Derivatives 

Designated derivatives are the instruments that mitigate interest risk for the company. These are entered into with external counterparties. They are also used to evidence the RMI that a company is taking. The full list of designated derivatives has not been set, it is expected it will contain interest rate swaps (including basis swaps), forward starting swaps and forward rate agreements12. In Staff Paper 4C – July 2023, the AISB recommended that non-linear derivatives, except for net written options, are eligible as designated derivatives. 

Benchmark Derivatives 

Benchmark derivatives (BD) are based on the same concepts as IFRS 9’s hypothetical derivatives. These are used to measure the efficacy of the hedging. The benchmark derivatives are based on the following specified characteristics13

  1. The benchmark derivative is constructed to be on-market at designation – i.e constructing a “hypothetical” derivative that is nil at zero, where the floating leg replicates the managed risk, and the fixed leg is calibrated to the yield curve. Note that benchmark derivatives are only constructed once and are therefore not reset at every period. 
  2. A benchmark derivative cannot be used to include features in the value of the RMI that only exist in the designated derivative (but not the RMI) – This means that features from the designated derivative cannot be used in the benchmark derivative if they don’t exist in the RMI. 
  3. The amount of risk and the tenor of the benchmark derivative is prescribed by the RMI and expressed in the risk metric (i.e. KPI) the entity manages at the repricing time period – E.g. if an company is using PV01 as the managed KPI, the amount of risk is measured as the sensitivity of one basis point shift in the managed yield curve. 

Transitioning to the new DRM model can be difficult due to the dynamic nature of the model, especially with a more complex balance sheet. Zanders can provide a wide range of expertise to support in the onboarding of the DRM model into your company’s hedging and accounting. We have successfully supported various clients with hedge accounting– including impact analyses, derivative pricing and model validation, and are familiar with the underlying challenges. Zanders can manage the whole project lifecycle from strategizing the implementation, alignment with key stakeholders and then helping design and implement the required models to successfully carry out the hedge accounting at every valuation period. As the deadline is quickly approaching it would benefit entities to start assessing the key characteristics of the DRM model in order to understand how to change their current framework to the new one.

For further information, please contact Pierre Wernert, or Alexander Oldroyd.

  1. IASB Webcast – October 2022  ↩︎
  2. Staff Paper 4A – November 2021  ↩︎
  3. Staff Paper 4A – April 2023  ↩︎
  4. Staff Paper 4B – April 2018 ↩︎
  5. Staff Paper 4A – February 2023 ↩︎
  6. Staff Paper 4C – April 2023 ↩︎
  7. Fair Value through Other Comprehensive Income  ↩︎
  8.  Fair Value through Profit or Loss. ↩︎
  9. Staff Paper AP4 – July 2022 ↩︎
  10. Staff Paper 4A – May 2022 ↩︎
  11. Staff Paper 4B – April 2023 ↩︎
  12. Staff Paper 4C – July 2023  ↩︎
  13. Staff Paper 4B – April 2023 ↩︎

Rethinking Macro Hedging: Introduction to DRM

March 2024
7 min read

The aim of the DRM model is to tie together hedge accounting with risk management strategy so that an entity’s effort to mitigate interest rate risk is better reflected within their financial statement.


The current standards for hedge accounting present significant challenges for financial institutions engaged in dynamically hedging their portfolios. The corresponding type of hedging accounting, known as “macro fair value hedge accounting”, is covered under IAS 39; however, the regulations fall short as they are unable to accurately reflect an organization’s risk management strategies in its financial reporting. In some instances, companies cannot apply hedge accounting as their hedge is deemed to be ineligible unless they perform some form of proxy hedging strategies. To address these issues, the international Accounting Standards Board (“IASB”) have introduced the Dynamic Risk Management (“DRM”) approach, which is intended to offer a more effective method for entities to apply macro hedging.

The current timeline by the IASB is for a first draft to be released in 2025. This article forms the first in a series of three that will delve into the DRM model, explore its improvements over the current regulations and provide a demonstration of a practical implementation of the current proposal. The insights provided within this series, are Zanders’ understanding drawn from the discussion papers that the IASB has released and so the information is subject to change before the publication of the draft in 2025.

The IASB is aiming for the DRM model to allow readers of the financial statement to gain the following insights: 

  • The entity’s interest rate risk management strategy and how it is applied to manage interest rate risk. 
  • How the entity’s interest rate risk management activities may affect the amount, timing and uncertainty of future cash flows. 
  • The effect of the DRM model on the entity’s financial position and financial performance. 

Within the May 2022 Staff Paper1, the IASB staff have identified a list of deficiencies of the current IAS 39 and IFRS 9 standards. The main limitations identified were: 

NumberAreaDescription of limitation
1Closed PortfoliosThe current regulations are designed for “closed portfolios” and requires the direct linkage of hedged items with a hedge. This causes problems as currently an “open portfolio” would be viewed as a set of multiple “closed portfolios”, each with short periodic lifespans. This leads to challenges, as any “open portfolio” hedge relationships need to be tracked individually and its hedge adjustments amortized accordingly.
2Risk Management on a net basisGenerally, entities will manage their exposures to interest rate risk on a net basis. However, currently hedges need to be managed on a gross basis. This means that interest rate risk management can be incorrectly represented to achieve the accounting requirements. 
3Dual character of net interest rate risk position The repricing risk of the net interest rate risk position arises from a combination of variable and fixed-rate exposures. The economic mismatch has both fair value and cash flow variability when interest rates change, and entities try to mitigate both aspects economically. However, the current hedge accounting requirements state that the  hedging relationship must be designated as either a fair value hedge with the fixed rate item or as a cash flow hedge with the variable item. 
4Demand depositsUnder the current regulations demand deposits cannot be hedged by banks as, from an accounting perspective, the fair value is constant. Since banks are unable to apply hedge accounting to demand deposits, they cannot accurately portray their risk management within the financial statements. 
Table 1: Limitations of Current Standards

The next two articles in this series will provide a comprehensive exploration of the DRM model and introduce the new concepts that the IASB has proposed. The next article offers a breakdown of the Risk Management Strategy (“RMS”) within the DRM model, how it factors into a company’s overarching strategy for managing their interest rate risk. It will cover the new concepts that the IASB have established. The third and final article in this series will provide an overview of the DRM cycle as well as an example taken from the IASB of how the DRM model would be applied in practice for a singular accounting period. Stay tuned!

What can Zanders offer? 

Transitioning to the new DRM model can be difficult due to the dynamic nature of the model, especially with a more complex balance sheet. Zanders can provide a wide range of expertise to support in the onboarding of the DRM model into your company’s hedging and accounting. We have supported various clients with hedge accounting– including impact analyses, derivative pricing and model validation, and are familiar with the underlying challenges. Zanders can manage the whole project lifecycle from strategizing the implementation, alignment with key stakeholders and then helping design and implement the required models to successfully carry out the hedge accounting at every valuation period.

For further information, please contact Pierre Wernert, or Alexander Oldroyd.

  1. Staff Paper 4B – May 2022  ↩︎ ↩︎

BKR – Towards the optimal registration period of credit registrations

Preventing problematic debt situations or increase access to finance after default recovery?


In countries worldwide, associations of credit information providers play a crucial role in registering consumer-related credits. They are mandated by regulation, operate under local law and their primary aim is consumer protection. The Dutch Central Credit Registration Agency, Stichting Bureau Krediet Registratie (BKR), has reviewed the validity of the credit registration period, especially with regards to the recurrence of payment problems after the completion of debt restructuring and counseling. Since 2017, Zanders and BKR are cooperating in quantitative research and modeling projects and they joined forces for this specific research.

In the current Dutch public discourse, diverse opinions regarding the retention period after finishing debt settlements exist and discussions have started to reduce the duration of such registrations. In December 2022, the four biggest municipalities in the Netherlands announced their independent initiative to prematurely remove registrations of debt restructuring and/or counseling from BKR six months after finalization. Secondly, on 21 June 2023, the Minister of Finance of the Netherlands published a proposal for a Credit Registration System Act for consultation, including a proposition to shorten the retention period in the credit register from five to three years. This proposition will also apply to credit registrations that have undergone a debt rescheduling.

The Dutch Central Credit Registration Agency, Stichting Bureau Krediet Registratie (BKR) receives and manages credit registrations and payment arrears of individuals in the Netherlands. By law, a lender in the Netherlands must verify whether an applicant already has an existing loan when applying for a new one. Additionally, lenders are obligated to report every loan granted to a credit registration agency, necessitating a connection with BKR. Besides managing credit data, BKR is dedicated to gathering information to prevent problematic debt situations, prevent fraud, and minimize financial risks associated with credit provision. As a non-profit foundation, BKR operates with a focus on keeping the Dutch credit market transparent and available for all.

BKR recognizes that the matter concerning the retention period of registrations for debt restructuring and counseling is fundamentally of societal nature. Many stakeholders are concerned with the current discussions, including municipalities, lenders and policymakers. To foster public debate on this matter, BKR is committed to conducting an objective investigation using credit registration data and literature sources and has thus engaged Zanders for this purpose. By combining expertise in financial credit risk with data analysis, Zanders offers unbiased insights into this issue. These data-driven insights are valuable for BKR, lawmakers, lenders, and municipalities concerning retention periods, payment issues, and debt settlements.

Problem Statement

The Dutch Central Credit Registration Agency, Stichting Bureau Krediet Registratie (BKR) receives and manages credit registrations and payment arrears of individuals in the Netherlands. By law, a lender in the Netherlands must verify whether an applicant already has an existing loan when applying for a new one. Additionally, lenders are obligated to report every loan granted to a credit registration agency, necessitating a connection with BKR. Besides managing credit data, BKR is dedicated to gathering information to prevent problematic debt situations, prevent fraud, and minimize financial risks associated with credit provision. As a non-profit foundation, BKR operates with a focus on keeping the Dutch credit market transparent and available for all.

The research aims to gain a deeper understanding of the recurrence of payment issues following the completion of restructuring credits (recidivism). The information gathered will aid in shaping thoughts about an appropriate retention period for the registration of finished debt settlements. The research includes both qualitative and quantitative investigations. The qualitative aspect involves a literature study, leading to an overview of benchmarking, key findings and conclusions from prior studies on this subject. The quantitative research comprises data analyses on information from BKR's credit register.

External International Qualitative Research

The literature review encompassed several Dutch and international sources that discuss debt settlements, credit registrations, and recidivism. There is limited research published on recidivism, but there are some actual cases where retention period are materially shortened or credit information is deleted to increase access to financial markets for borrowers. Removing information increases information asymmetry, meaning that borrower and lender do not have the same insights limiting lenders to make well-informed decisions during the credit application process. The cases in which the retention period was shortened or negative credit registrations were removed demonstrate significant consequences for both consumers and lenders. Such actions led to higher default rates, reduced credit availability, and increased credit costs, also for private individuals without any prior payment issues.

In the literature it is described that historical credit information serves as predictive variable for payment issues, emphasizing the added value of credit registrations in credit reports, showing that this mitigates the risk of overindebtedness for both borrowers and lenders.

Quantitative Research with Challenges and Solutions

BKR maintains a large data set with information regarding credits, payment issues, and debt settlements. For this research, data from over 2.5 million individuals spanning over 14 years were analyzed. Transforming this vast amount of data into a usable format to understand the payment and credit behavior of individuals posed a challenge.

The historical credit registration data has been assessed to (i) gain deeper insights into the relationship between the length of retention periods after debt restructuring and counseling and new payment issues and (ii) determine whether a shorter retention period after the resolution of payment issues negatively impacts the prevention of new payment issues, thus contributing to debt prevention to a lesser extent.

The premature removal of individuals from the system of BKR presented an additional challenge. Once a person’s information is removed from the system, their future payment behavior can no longer be studied. Additionally, the group subject to premature removal (e.g. six months to a year) after a debt settlement registration constitutes only a small portion of the population, making research on this group challenging. To overcome these challenges, the methodology was adapted to assess the outflow of individuals over time, such that conclusions about this group could still be made.

Conclusion

The research provided BKR with several interesting conclusions. The data supported the literature that there is difference in risk for payment issues between lenders with and without debt settlement history. Literature shows that reducing the retention period increases the access to the financial markets for those finishing a debt restructuring or counseling. It also increases the risk in the financial system due to the increased information asymmetry between lender and borrower, with several real-life occasions with

increased costs and reduced access to lending for all private individuals. The main observation of the quantitative research is that individuals who have completed a debt rescheduling or debt counseling face a higher risk of relapsing into payment issues compared to those without debt restructuring or counseling history. An outline of the research report is available on the website of BKR.

The collaboration between BKR and Zanders has fostered a synergy between BKR's knowledge, data, and commitment to research and Zanders' business experience and quantitative data analytical skills. The research provides an objective view and quantitative and qualitative insights to come to a well informed decision about the optimal registration period for the credit register. It is up to the stakeholders to discuss and decide on the way forward.

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The 2023 Banking Turmoil

November 2023
7 min read

The aim of the DRM model is to tie together hedge accounting with risk management strategy so that an entity’s effort to mitigate interest rate risk is better reflected within their financial statement.


Early October, the Basel Committee on Banking Supervision (BCBS) published a report[1] on the 2023 banking turmoil that involved the failure of several US banks as well as Credit Suisse. The report draws lessons for banking regulation and supervision which may ultimately lead to changes in banking regulation as well as supervisory practices. In this article we summarize the main findings of the report[2]. Based on the report’s assessment, the most material consequences for banks, in our view, could be in the following areas:

  • Reparameterization of the LCR calculation and/or introduction of additional liquidity metrics
  • Inclusion of assets accounted for at amortized cost at their fair value in the determination of regulatory capital
  • Implementation of extended disclosure requirements for a bank's interest rate exposure and liquidity position
  • More intensive supervision of smaller banks, especially those experiencing fast growth and concentration in specific client segments
  • Application of the full Basel III Accord and the Basel IRRBB framework to a larger group of banks

Bank failures and underlying causes

The BCBS report first describes in some detail the events that led to the failure of each of the following banks in the spring of 2023:

  • Silicon Valley Bank (SVB)
  • Signature Bank of New York (SBNY)
  • First Republic Bank (FRB)
  • Credit Suisse (CS)

While each failure involved various bank-specific factors, the BCBS report highlights common features (with the relevant banks indicated in brackets).

  • Long-term unsustainable business models (all), in part due to remuneration incentives for short-term profits
  • Governance and risk management did not keep up with fast growth in recent years (SVB, SBNY, FRC)
  • Ineffective oversight of risks by the board and management (all)
  • Overreliance on uninsured customer deposits, which are more likely to be withdrawn in a stress situation (SVB, SBNY, FRC)
  • Unprecedented speed of deposit withdrawals through online banking (all)
  • Investment of short-term deposits in long-term assets without adequate interest-rate hedges (SVB, FRC)
  • Failure to assess whether designated assets qualified as eligible collateral for borrowing at the central bank (SVB, SBNY)
  • Client concentration risk in specific sectors and on both asset and liability side of the balance sheet (SVB, SBNY, FRC)
  • Too much leniency by supervisors to address supervisory findings (SVB, SBNY, CS)
  • Incomplete implementation of the Basel Framework: SVB, SBNY and FRB were not subject to the liquidity coverage ratio (LCR) of the Basel III Accord and the BCBS standard on interest rate risk in the banking book (IRRBB)

Of the four failed banks, only Credit Suisse was subject to the LCR requirements of the Basel III Accord, in relation to which the BCBS report includes the following observations:

  • A substantial part of the available high quality liquid assets (HQLA) at CS was needed for purposes other than covering deposit outflows under stress, in contrast to the assumptions made in the LCR calculation
  • The bank hesitated to make use of the LCR buffer and to access emergency liquidity so as to avoid negative signalling to the market

Although not part of the BCBS report, these observations could lead to modifications to the LCR regulation in the future.

Lessons for supervision

With respect to supervisory practices, the BCBS report identifies various lessons learned and raises a few questions, divided into four main areas:

1. Bank’s business models

  • Importance of forward-looking assessment of a bank’s capital and liquidity adequacy because accounting measures (on which regulatory capital and liquidity measures are based) mostly are not forward-looking in nature
  • A focus on a bank’s risk-adjusted profitability
  • Proactive engagement with ‘outlier banks’, e.g., banks that experienced fast growth and have concentrated funding sources or exposures
  • Consideration of the impact of changes in the external environment, such as market conditions (including interest rates) and regulatory changes (including implementation of Basel III)

2. Bank’s governance and risk management

  • Board composition, relevant experience and independent challenge of management
  • Independence and empowerment of risk management and internal audit functions
  • Establishment of an enterprise-wide risk culture and its embedding in corporate and business processes.
  • Senior management remuneration incentives

3.Liquidity supervision

  • Do the existing metrics (LCR, NSFR) and supervisory review suffice to identify start of material liquidity outflows?
  • Should the monitoring frequency of metrics be increased (e.g., weekly for business as usual and daily or even intra-day in times of stress)?
  • Monitoring of concentration risks (clients as well as funding sources)
  • Are sources of liquidity transferable within the legal entity structure and freely available in times of stress?
  • Testing of contingency funding plans

4. Supervisory judgment

  • Supplement rules-based regulation with supervisory judgment in order to intervene pro-actively when identifying risks that could threaten the bank’s safety and soundness. However, the report acknowledges that a supervisor may not be able to enforce (pre-emptive) action as long as an institution satisfies all minimum requirements. This will also depend on local legislative and regulatory frameworks

Lessons for regulation

In addition, the BCBS report identifies various potential enhancement to the design and implementation of bank regulation in four main areas:

1. Liquidity standards

  • Consideration of daily operational and intra-day liquidity requirements in the LCR, based on the observation that a material part of the HQLA of CS was used for this purpose but this is not taken into account in the determination of the LCR
  • Recalibration of deposit outflows in the calculation of LCR and NSFR, based on the observation that actual outflow rates at the failed banks significantly exceeded assumed outflows in the LCR and NSFR calculations
  • Introduction of additional liquidity metrics such as a 5-day forward liquidity position, survival period and/or non-risk based liquidity metrics that do not rely on run-off assumptions (similar to the role of the leverage ratio in the capital framework)

2. IRRBB

  • Implementation of the Basel standard on IRRBB, which did not apply to the US banks, could have made the interest rate risk exposures transparent and initiated timely action by management or regulatory intervention.
  • More granular disclosure, covering for example positions with and without hedging, contractual maturities of banking book positions and modelling assumptions 

3. Definition of regulatory capital

  • Reflect unrealised gains and losses on assets that are accounted for at amortised cost (AC) in regulatory capital, analogous to the treatment of assets that are classified as available-for-sale (AFS). This is supported by the observation that unrealised losses on fixed-income assets held at amortised cost, resulting from to the sharp rise in interest rates, was an important driver of the failure of several US banks when these assets were sold to create liquidity and unrealised losses turned into realised losses. The BCBS report includes the following considerations in this respect:
    • If AC assets can be repo-ed to create liquidity instead of being sold, then there is no negative impact on the financial statement
    • Treating unrealised gains and losses on AC assets in the same way as AFS assets will create additional volatility in earnings and capital
    • The determination of HQLA in the LCR regulation requires that assets are measured at no more than market value. However, this does not prevent the negative capital impact described above
  • Reconsideration of the role, definition and transparency of additional Tier-1 (AT1) instruments, considering the discussion following the write-off of AT1 instruments as part of the take-over of CS by UBS

4. Application of the Basel framework

  • Broadening the application of the full Basel III framework beyond internationally active banks and/or developing complementary approaches to identify risks at domestic banks that could pose a threat to cross-border financial stability. The events in the spring of this year have demonstrated that distress at relatively small banks that are not subject to the (full) Basel III regulation can trigger broader and cross-border systemic concerns and contagion effects.
  • Prudent application of the ‘proportionality’ principle to domestic banks, based on the observation that financial distress at such banks can have cross-border financial stability effects
  • Harmonization of approaches that aim to ensure that sufficient capital and liquidity is available at individual legal entity level within banking groups

Conclusion

The BCBS report identifies common shortcomings in bank risk management practices and governance at the four banks that failed during the 2023 banking turmoil and summarizes key take-aways for bank supervision and regulation.

The identified shortcomings in bank risk management include gaps in the management of traditional banking risks (interest rate, liquidity and concentration risks), failure to appreciate the interrelation between individual risks, unsustainable business models driven by short-term incentives at the expense of appropriate risk management, poor risk culture, ineffective senior management and board oversight as well as a failure to adequately respond to supervisory feedback and recommendations.

Key take-aways for effective supervision include enforcing prompt action by banks in response to supervisory findings, actively monitoring and assessing potential implications of structural changes to the banking system, and maintaining effective cross-border supervisory cooperation.

Key lessons for regulatory standards include the importance of full and consistent implementation of Basel standards as well as potential enhancements of the Basel III liquidity standards, the regulatory treatment of interest rate risk in the banking book, the treatment of assets that are accounted for at amortised cost within regulatory capital and the role of additional Tier-1 capital instruments.

The BCBS report is intended as a starting point for discussion among banking regulators and supervisors about possible changes to banking regulation and supervisory practices. For those interested in engaging in discussions related to the insights and recommendations in the BCBS report, please feel free to contact Pieter Klaassen.


[1] Report on the 2023 banking turmoil (bis.org) (accessed on October 19, 2023)

[2] Although recognized as relevant in relation to the banking turmoil, the BCBS report explicitly excludes from its consideration the role and design of deposit guarantee schemes, the effectiveness of resolution arrangements, the use and design of central bank lending facilities and FX swap lines, and public support measures in banking crises.

Grip on your EVE SOT

May 2023
7 min read

The aim of the DRM model is to tie together hedge accounting with risk management strategy so that an entity’s effort to mitigate interest rate risk is better reflected within their financial statement.


Over the past decades, banks significantly increased their efforts to implement adequate frameworks for managing interest rate risk in the banking book (IRRBB). These efforts typically focus on defining an IRRBB strategy and a corresponding Risk Appetite Statement (RAS), translating this into policies and procedures, defining the how of the selected risk metrics, and designing the required (behavioral) models. Aspects like data quality, governance and risk reporting are (further) improved to facilitate effective management of IRRBB.

Main causes of volatility in SOT outcomes

The severely changed market circumstances evidence that, despite all efforts, the impact on the IRRBB framework could not be fully foreseen. The challenge of certain banks to comply with one of the key regulatory metrics defined in the context of IRRBB, the SOT on EVE, illustrates this. Indeed, even if regularities are assumed, there are still several key model choices that turn out to materialize in today’s interest rate environment:

  • Interest rate dependency in behavioral models: Behavioral models, in particular when these include interest rate-dependent relationships, typically exhibit a large amount of convexity. In some cases, convexity can be (significantly) overstated due to particular modeling choices, in turn contributing to a violation of the EVE SOT criterium. Some (small and mid-sized) banks, for example, apply the so-called ‘scenario multipliers’ and/or ‘scalar multipliers’ defined within the BCBS-standardized framework for incorporating interest rate-dependent relationships in their behavioral models. These multipliers assume a linear relationship between the modeled variable (e.g., prepayment rate) and the scenario, whereas in practice this relationship is not always linear. In other cases, the calibration approach of certain behavioral models is based on interest rates that have been decreasing for 10 to 15 years, and therefore may not be capable to handle a scenario in which a severe upward shock is added to a significantly increased base case yield curve.
  • Level and shape of the yield curve: Related to the previous point, some behavioral models are based on the steepness (defined as the difference between a ‘long tenor’ rate and a ‘short tenor’ rate) of the yield curve. As can be seen in Figure 1, the steepness changed significantly over the past two years, potentially leading to a high impact associated with the behavioral models that are based on it. Further, as illustrated in Figure 2, the yield curve has flattened over time and recently even turned into an inverse yield curve. When calculating the respective forward rates that define the steepness within a particular behavioral model, the downward trend of this variable that results due to the inverse yield curve potentially aggravates this effect.

Figure 1: Development of 3M EURIBOR rate and 10Y swap rate (vs. 3M EURIBOR) and the corresponding 'Steepness'

Figure 2: Development of the yield curve over the period December 2021 to March 2023.

  • Hidden vulnerability to ‘down’ scenarios: Previously, the interest rates were relatively close to, or even below, the EBA floor that is imposed on the SOT. Consequently, the ‘at-risk’ figures corresponding to scenarios in which (part of) the yield curve is shocked downward, were relatively small. Now that interest rates have moved away from the EBA floor, hidden vulnerability to ‘down’ scenarios become visible and likely the dominating scenario for the SOT on EVE.
  • Including ‘margin’ cashflows: Some banks determine their SOT on EVE including the margin cashflows (i.e., the spread added to the swap rate), while discounting at risk-free rates. While this approach is regulatory compliant, the inclusion of margin cashflows leads to higher (shocked) EVE values, and potentially leads to, or at least contributes to, a violation of the EVE threshold.

What can banks do?

Having identified the above issues, the question arises as to what measures banks should consider. Roughly speaking, two categories of actions can be distinguished. The first category encompasses actions that resolve an inadequate reflection of the actual risk. Examples of such actions include:

  • Identify and re-solve unintended effects in behavioral models: As mentioned above, behavioral models are key to determine appropriate EVE SOT figures. Next to revisiting the calibration approach, which typically is based on historical data, banks should assess to what extent there are unintended effects present in their behavioral models that adversely impact convexity and lead to unrepresentative sensitivities and unreliably shocked EVE values.
  • Adopt a pure IRR approach: An obvious candidate action for banks that still include margins in their cashflows used for the EVE SOT, is to adopt a pure interest rate risk view. In other words, align the cashflows with its discounting. This requires an adequate approach to remove the margin components from the interest cashflows.

The second category of actions addresses the actual, i.e., economic, risk position of bank. One could think of the following aspects that contribute to steering the EVE SOT within regulatory thresholds:

  • Evaluate target mismatch: As we wrote in our article ‘What can banks do to address the challenges posed by rising interest rates’, a bank’s EVE is most likely negatively affected by the rise in rates. The impact is dependent on the duration of equity taken by the bank: the higher the equity duration, the larger the decline in EVE when rates rise (and hence a higher EVE risk). In light of the challenges described above, a bank should consider re-evaluating the target mismatch (i.e. the duration of equity).
  • Consider swaptions as an additional hedge instrument: Convexity, in essence, cannot be hedged with plain vanilla swaps. Therefore, several banks have entered into ‘far out of the money’ swaptions to manage negative convexity in the SOT on EVE. From a business perspective, these swaptions result in additional, but accepted costs and P&L volatility. In case of an upward-sloping yield curve, the costs can be partly offset since the bank can increase its linear risk position (increase duration), without exceeding the EVE SOT threshold. This being said, swaptions can be considered a complex instrument that presents certain challenges. First, it requires valuation models – and expertise on these models – to be embedded within the organization. Second, setting up a heuristic that adequately matches the sensitivities of the swaptions to those of the commercial products (e.g., mortgages) is not a straightforward task.

How can Zanders support?

Zanders is thought leader in supporting banks with IRRBB-related topics. We enable banks to achieve both regulatory compliance and strategic risk goals, by offering support from strategy to implementation. This includes risk identification, formulating a risk strategy, setting up an IRRBB governance and framework, policy or risk appetite statements. Moreover, we have an extensive track record in IRRBB and behavioral models, hedging strategies, and calculating risk metrics, both from a model development as well as a model validation perspective.

Are you interested in IRRBB related topics? Contact Jaap KarelseErik Vijlbrief (Netherlands, Belgium and Nordic countries) or Martijn Wycisk (DACH region) for more information.

CEO Statement: Why Our Purpose Matters

May 2023
5 min read

CEO Laurens Tijdhof explains the origins and importance of the Zanders group’s purpose.


The Zanders purpose

Our purpose is to deliver financial performance when it counts, to propel organizations, economies, and the world forward.

Recently, we have embarked on a process to align more effectively what we do with the changing needs of our clients in unprecedented times. A central pillar of this exercise was an in-depth dialogue with our clients and business partners around the world. These conversations confirmed that Zanders is trusted to translate our deep financial consultancy knowledge into solutions that answer the biggest and most complex problems faced by the world's most dynamic organizations. Our goal is to help these organizations withstand the current macroeconomic challenges and help them emerge stronger. Our purpose is grounded on the above.

"Zanders is trusted to translate our deep financial consultancy knowledge into solutions, answering the biggest and most complex problems faced by the world's most dynamic organizations."

Laurens Tijdhof

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Our purpose is a reflection of what we do now, but it's also about what we need to do in the future.

It reflects our ongoing ambition - it's a statement of intent - that we should and will do more to affect positive change for both the shareholders of today and the stakeholders of tomorrow. We don't see that kind of ambition as ambitious; we see it as necessary.

The Zanders’ purpose is about the future. But it's also about where we find ourselves right now - a pandemic, high inflation and rising interest rates. And of course, climate change. At this year's Davos meeting, the latest Disruption Index was released showing how macroeconomic volatility has increased 200% since 2017, compared to just 4% between 2011 and 2016.

So, you have geopolitical volatility and financial uncertainty fused with a shifting landscape of regulation, digitalization, and sustainability. All of this is happening at once, and all of it is happening at speed.

The current macro environment has resulted in cost pressures and the need to discover new sources of value and growth. This requires an agile and adaptive approach. At Zanders, we combine a wealth of expertise with cutting-edge models and technologies to help our clients uncover hidden risks and capitalize on unseen opportunities.

However, it can't be solely about driving performance during stable times. This has limited value these days. It must be about delivering performance despite macroeconomic headwinds.

For over 30 years, through the bears, the bulls, and black swans, organizations have trusted Zanders to deliver financial performance when it matters most. We've earned the trust of CFOs, CROs, corporate treasurers and risk managers by delivering results that matter, whether it's capital structures, profitability, reputation or the environment. Our promise of "performance when it counts" isn't just a catchphrase, but a way to help clients drive their organizations, economies, and the world forward.

"For over 30 years, through the bears, the bulls, and black swans, financial guardians have trusted Zanders to deliver financial performance when it matters most."

Laurens Tijdhof

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What "performance when it counts" means.

Navigating the current changing financial environment is easier when you've been through past storms. At Zanders, our global team has experts who have seen multiple economic cycles. For instance, the current inflationary environment echoes the Great Inflation of the 1970s. The last 12 months may also go down in history as another "perfect storm," much like the global financial crisis of 2008. Our organization's ability to help business and government leaders prepare for what's next comes from a deep understanding of past economic events. This is a key aspect of delivering performance when it counts.

The other side of that coin is understanding what's coming over the horizon. Performance when it counts means saying to clients, "Have you considered these topics?" or "Are you prepared to limit the downside or optimize the upside when it comes to the changing payments landscape, AI, Blockchain, or ESG?" Waiting for things to happen is not advisable since they happen to you, rather than to your advantage. Performance when it counts drives us to provide answers when clients need them, even if they didn't know they needed them. This is what our relationships are about. Our expertise may lie in treasury and risk, but our role is that of a financial performance partner to our clients.

How technology factors into delivering performance when it counts.

Technology plays a critical role in both Treasury and Risk. Real-time Treasury used to be an objective, but it's now an imperative. Global businesses operate around the clock, and even those in a single market have customers who demand a 24/7/365 experience. We help transform our clients to create digitized, data-driven treasury functions that power strategy and value in this real-time global economy.

On the risk management front, technology has a two-fold power to drive performance. We use risk models to mitigate risk effectively, but we also innovate with new applications and technologies. This allows us to repurpose risk models to identify new opportunities within a bank's book of business.

We can also leverage intelligent automation to perform processes at a fraction of the cost, speed, and with zero errors. In today's digital world, this combination of next generation thinking, and technology is a key driver of our ability to deliver performance in new and exciting ways.

"It’s a digital world. This combination of next generation of thinking and next generation of technologies is absolutely a key driver of our ability to deliver performance when it counts in new and exciting ways."

Laurens Tijdhof

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How our purpose shapes Zanders as a business.

In closing, our purpose is what drives each of us day in and day out, and it's critical because there has never been more at stake. The volume of data, velocity of change, and market volatility are disrupting business models. Our role is to help clients translate unprecedented change into sustainable value, and our purpose acts as our North Star in this journey.

Moreover, our purpose will shape the future of our business by attracting the best talent from around the world and motivating them to bring their best to work for our clients every day.

"Our role is to help our clients translate unprecedented change into sustainable value, and our purpose acts as our North Star in this journey."

Laurens Tijdhof

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Increase confidence in your organization with proactive fraud prevention measures

March 2023
5 min read

CEO Laurens Tijdhof explains the origins and importance of the Zanders group’s purpose.


With every improvement, fraudsters look for and find new opportunities to exploit. When the opportunity arises, some people see a big incentive or pressure to commit fraud, and most will be able to justify to themselves why it is acceptable to commit fraud (as shown in the Fraud triangle – Figure 1). Unfortunately, the impact of fraud on organizations, individuals and society in general is substantial.

In a recent report by the Association of Certified Fraud Examiners (ACFE), Occupational Fraud 2022: A report to the nations, it is estimated that organizations lose about 5% of their revenue each year due to employees committing fraud against their employer. It is estimated that more than USD 4.7 trillion is lost worldwide to occupational fraud.  Of these, most cases were identified through a tip to a hotline and most were not detected until 12 to 18 months later. The longer the fraud was undetected, the higher the loss. But organizations do not only fight fraud internally; external threats are also on the rise. As businesses evolve and processes are automated and digitalized, fraud activities become much more complex.

Data and modeling approach to fraud prevention

To effectively prevent fraud, it first needs to be identified. Traditionally, employees are trained to identify anomalies or inconsistencies in their daily work environment. It is still crucial that your employees know what to look for and how to spot suspicious activities. But due to the complexities and vast amounts of information available, and because fraudsters are becoming more sophisticated, it becomes much more difficult to determine whether a potential customer is a fraudster or a real client.

The good news is that digitalization and increased data availability provides the opportunity for data analytics. It is important to note here that it does not completely replace your current processes; it should be used in addition to your traditional prevention and/or detection methods to be more effective to proactively identify and prevent fraud in your organization.

Benefits of data analytics

Traditionally, sampling was done on a population to test for fraud instances, but this may not be as effective because it only looks at a small population. Because fraud numbers reported usually being small (but with a large monetary impact), it is possible to overlook valuable insights if only samples of populations are investigated. Ideally, all data should be included to identify trends and potential fraudulent activities, and with data analytics that is possible. By analyzing large amounts of data, organizations can identify patterns and trends that may indicate fraudulent activity. It can help to improve the accuracy of fraud detection systems, as they can be trained to recognize these patterns.

Data analytics can increase efficiency by reducing false positives and false negatives and assists organizations to automate parts of the fraud detection processes, which can save time and resources. This allows the business to focus on other important strategic objectives and tasks such as customer service and product development.

By using data analytics to identify and prevent fraudulent activity, organizations can help to protect their customers against financial losses and other harm. Customer trust and loyalty are built when organizations show they are serious about the welfare and safety of their customers.

Detecting and preventing fraud

Reality is that preventing fraud upfront or in an early stage is much more economical and beneficial than having to detect fraud after the fact, as investigations are time-consuming and the fraud is not always easy to proof in court. Moreover, by the time it is detected, a loss may have already been incurred. Using data analytics to identify fraudsters and fraudulent activities earlier, can protect the bottom line by reducing financial losses and improving the organization’s overall financial performance.

By using analytics to detect and prevent fraud, organizations can demonstrate to regulatory bodies that they are taking compliance seriously. Reporting suspicious transactions and activities to regulatory bodies is a key component of complying with anti-money laundering and counter-terrorism financing legislation, and analytics can assist with identifying these transactions and activities more effectively.

Data analytics can be used to prevent fraud at onboarding, detect it in the existing customer base, and to make your operational processes more efficient. More specifically, data analytics can be used and leveraged as follows:

  • Identifying outlier trends and hidden patterns can highlight areas and/or transactions that are more vulnerable to fraud.
  • Automating identification of exceptions removes manual intervention and makes the identification criteria more consistent.
  • Traditional physical reviews using limited resources to investigate is time-consuming. Data analytics can be used to prioritize the ones with the highest impact and risk, e.g. investigate the suspicious transactions with the highest value first.
  • Combining data from different data sources to feed into a model provides a more holistic view of a customer or scenario than looking at individual transactions or applications in isolation.
  • Both structured and unstructured data can be used to prevent and detect fraud.
  • Fraud propensity model scoring can run automatically and generate results to be reviewed and investigated in real-time or near real-time.
  • Analyzing relationships between various entities and customers using Social Network Analysis (SNA). Traditionally, networks/links were identified by the investigator while building a case. By using analytics, less time is needed to identify these relationships. Also, it identifies valuable links previously unknown, as additional levels of relationships can be examined.
  • Specific modus operandi identified by the organization’s internal fraud team can be translated into data models to automate identification of similar cases. (See Case study below)
  • Applying a fraud model to the organization’s bad debt book can assist with your collections strategy. Fraudsters never intended to pay and focusing your collection efforts on them wastes time and valuable resources. Most efforts should be on those cases where money can be collected.

Case study

The Zanders data analytics team has experience with applying data analytics within a company to identify customers who create synthetic profiles at point of application. By working closely with investigators, a model was developed in which one out of every three applications referred for investigation was classified as fraudulent.

The benefit of introducing analytics was twofold – from an onboarding- and existing customer point of view. The number of fraudsters identified before onboarding increased, preventing (potential) losses. Using the positive identified frauds at point of application, and checking the profile against the existing book, helped to identify areas that were more vulnerable where investigation should be prioritized.

The project proved that:

  • Data analytics is valuable and combining it with insights from the operational teams is powerful.
  • The buy-in from the stakeholders made the model more effective. If the team investigating the alert does not trust the model or does not know what to look for, there will be resistance in investigating the alerts.
  • Taking your internal fraud team on a data and analytics journey is a must. They need to understand the impact that their decisions and captured outcomes can have on future models.
  • Challenges with false positives (within business appetite and investigation capacity) are a reality, but having a model is better than searching for a needle in a haystack. Learning from the results and outcomes of the investigations, even if they were false positives, will enhance your next model.
  • One size does not fit all. Fraud models need to be tailored to the business’ needs.

Conclusion

While using data analytics to identify fraudulent activities is an investment, organizations need to outweigh the benefit of incorporating data analytics in their current processes against the potential losses. Fraud not only results in monetary losses, it can lead to reputational damage and have an impact on the organization’s market share as customers will not do business with an organization where they don’t feel protected. Your customers also expect great customer service and implementing proactive fraud prevention measures increases confidence in your organization.

How can Zanders help your organization?

Did you find this article helpful but do you still have questions or need additional assistance? Our team of experts is ready to assist you in finding the solutions you need. Please feel free to reach out to us to discuss your needs in more detail. Whether you’re looking for advice on a specific project or just need someone to exchange ideas with, we are here to assis

Are climate change risks properly captured in the prudential framework?

February 2023
5 min read

CEO Laurens Tijdhof explains the origins and importance of the Zanders group’s purpose.


More simply put, the EBA was asked to investigate whether the current prudential framework properly captures environmental and social risks. In response, the EBA published a Discussion Paper (DP) [1] in May 2022 to collect input from stakeholders such as academia and banking professionals.

After briefly presenting the DP, this article reviews the current Pillar 1 Capital (P1C) requirements. We limit ourselves to the P1C requirements for credit risk as this is by far the largest risk type for banks. Furthermore, we only discuss the interaction of the P1C with climate change risks (as opposed to broader environmental and/or social risk types). After establishing the extent to which the prudential framework takes climate change risks into account, possible amendments to the framework will be considered.

Key take-aways of this article:

  • The current prudential framework includes several mechanisms that allow the reflection of climate change risks into the P1C.
  • The interaction between P1C and climate change risks is limited to specific parts of the portfolio, and in those cases, it remains to be seen to what extent this is properly accounted for at the moment.
  • Amendments to the prudential framework can be considered, but it is important to avoid double counting issues and to take into account differences in time horizons.
  • The EBA is expected to publish a final report on the prudential treatment of environmental risks in the first half of this year.
  • Financial institutions that are using the internal ratings-based approach are advised to start with the incorporation of climate change risks into PD and LGD models.

EBA’s Discussion Paper

In the introduction of the DP, the EBA mentions the increasing environmental risks – and their interaction with the traditional risk types – as the trigger for the review of the prudential framework. One of the main concerns is whether the current framework is sufficiently capturing the impact of transition risks and the more frequent and severe physical risks expected in the coming decades. In this context, they stress the special characteristics of environmental risks: compared to the traditional risk types, environmental risks tend to have a “multidimensional, non-linear, uncertain and forward-looking nature.”

The EBA also explains that the P1C requirements are not intended to cover all risks a financial institution is exposed to. The P1C represents a baseline capital requirement that is complemented by the Pillar 2 Capital requirement, which is more reflective of a financial institution’s specific business model and risks. Still, it is warranted to assess whether environmental risks are appropriately reflected in the P1C requirements, especially if these lead to systemic risks.

Even though the DP raises more questions than it provides answers, some starting points for the discussion are introduced. One is that the EBA takes a risk-based approach. Their standpoint is that changes to the prudential framework should reflect actual risk differentials compared to other risk types and that it should not be a tool to (unjustly) incentivize the transition to a sustainable economy. The latter lies “in the remit of political authorities.”

The DP also discusses some challenges related to environmental risks. One example is the lack of high-quality, granular historical data, which is needed to support the calibration of the prudential framework. The EBA also mentions the mismatch in the time horizon for the prudential framework (i.e., a business cycle) and the time horizon over which the environmental risks will unfold (i.e., several decades). They wonder whether “the business cycle concepts and assumptions that are used in estimating risk weights and capital requirements are sufficient to capture the emergence of these risks.”

Finally, the EBA does not favor supporting and/or penalizing factors, i.e., the introduction of adjustments to the existing risk weights based on a (green) taxonomy-based classification of the exposures1. They are right to argue that there is no direct relationship between an exposure’s sustainability profile and its credit risk. In addition, there is a risk of double counting if environmental risk drivers have already been reflected in the current prudential framework. Consequently, the EBA concludes that targeted amendments to the framework may be more appropriate. An example would be to ensure that environmental risks are properly included in external credit ratings and the credit risk models of financial institutions. We explain this in more detail in the following paragraphs.

Pillar 1 Capital requirements

The assessment to what extent climate change risks are properly captured in the current prudential framework requires at least a high-level understanding of the framework. Figure 1 presents a schematic overview of the P1C requirements.

The P1C (at the top of Figure 1) depends on the total amount of Risk-Weighted Assets (RWAs; on the row below)2. RWAs are determined separately for each (traditional) risk type. As mentioned, we only focus on credit risk in this article. The RWAs for credit risk are approximately 80% of the average bank’s total RWAs3. Financial institutions can choose between two methodologies for determining their credit risk RWAs: the Standardized Approach (SA)4 and the internal ratings-based (IRB) approach5 . In Europe, on average 40% of the total RWAs for credit risk are based on the SA, while the rest is based on the IRB approach:

Figure 1 – Schematic overview of the P1C requirements and the interaction with climate change risks

Standardized Approach

In the SA, risk weights (RWs) are assigned to individual exposures, depending on their exposure class. About 50% of the RWAs for credit risk in the SA stem from the Corporates exposure class7. Generally speaking, there are three possible RW drivers: the RWAs depend on the external credit rating for the exposure, a fixed RW applies, or the RW depends on the Loan-to-Value8 (LtV) of the (real estate) exposure. The RW for an exposure to a sovereign bond for example, is either equal to 100% if no external credit rating is available (a fixed RW) or it ranges between 0% (for an AAA to AA-rated bond) and 150% (for a below B-rated bond).

Internal Ratings-Based Approach

Within the IRB approach, a distinction is made between Foundation IRB (F-IRB) and Advanced IRB (A-IRB). In both cases, a financial institution is allowed to use its internal models to determine the Probability of Default (PD) for the exposure. In the A-IRB approach, the financial institution in addition is allowed to use internal models to determine the Loss Given Default (LGD), Exposure at Default (EAD), and the Effective Maturity (M).

Interaction with climate change risks

The overview of the P1C requirements introduced in the previous section allows us to investigate the interaction between climate change risks and the P1C requirement. This is done separately for the SA and the IRB approach.

Standardized Approach

In the SA, there are two elements that allow for interaction between climate change risks and the resulting P1C. Climate change risks could be reflected in the P1C if the RW depends on an external credit rating, and this rating in turn properly accounts for climate change risks in the assessment of the counterparty’s creditworthiness (see 1 in Figure 1). The same holds if the RW depends on the LtV and in turn, the collateral valuation properly accounts for climate change risks (see 2 in Figure 1). This raises several concerns:

First, it can be questioned whether external credit ratings are properly capturing all climate change risks. In a report from the Network for Greening the Financial System (NGFS) [3], which was published at the same time as EBA’s DP, it is stated that credit rating agencies (CRAs) have so far not attempted to determine the credit impact of environmental risk factors (through back-testing for example). Also, the lack of high-quality historical data is mentioned as an explanation that statistical relationships between environmental risks and credit ratings have not been quantified. Further, a paper published by the ECB [4] concludes that, given the current level of disclosures, it is impossible for users of credit ratings to establish the magnitude of adjustments to the credit rating stemming from ESG-related risks. Nevertheless, they state that credit rating agencies “have made significant progress with their disclosures and methodologies around ESG in recent years.” The need for this is supported by academic research. An example is a study [5] from 2021 in which a correlation between credit default swap (CDS) spreads and ESG performance was demonstrated, and a study from 2020 [6] which demonstrated that high emitting companies have a shorter distance-to-default.

Secondly, the EBA has reported in the DP that less than 10% of the SA’s total RWAs is derived based on external credit ratings. This implies that a large share of the total RWAs is assigned a fixed RW. Obviously, in those cases there is no link between the P1C and the climate change risks involved in those exposures.

Finally, climate change risks only impact the P1C maintained for real estate exposures to the extent that these risks have been reflected in collateral valuations. Although climate change risks are priced in financial markets according to academic literature, many papers and institutions indicate that these risks are not (yet) fully reflected. In a survey held by Stroebel and Wurgler in 2021 [7], it is shown that a large majority of the respondents (consisting of finance academics, professionals and public sector regulators, among others) is of the opinion that climate change risks have insufficiently been priced in financial markets. A nice overview of this and related literature is presented in a publication from the Bank for International Settlements (BIS) [8]. The EBA DP itself lists some research papers in chapter 5.1 that indicate a relationship between a home’s sales price and its energy efficiency, or with the occurrence of physical risk events. It is unclear though if climate change risks are fully captured in the collateral valuations. For example, research is presented that information on flood risk is not priced into residential property prices. Recent research by ABN AMRO [9] also shows this.

Internal Ratings-Based Approach

In the IRB approach, financial institutions have more flexibility to include climate change risks in their internal models (see 3 in Figure 1). In the F-IRB approach this is limited to PD models, but in the A-IRB approach also LGD models can be adjusted.

A complicating factor is the forward-looking nature of climate change risks. In recent years, the competent authorities have pressured financial institutions to use historical data as much as possible in their model calibration and to back-test the performance of their models. As climate change risks will unfold over the next couple of decades, these are not (yet) reflected in historical data. To incorporate climate change risk, expert judgement would therefore be required. This has been discouraged over the past years (e.g., through the ECB’s Targeted Review of Internal Models (TRIM)) and it will probably trigger a discussion with the competent authorities. A possible deterioration of model performance (due to higher estimated risks compared to historically observations) is just one example that may attract attention.

Another complicating factor is that under the IRB approach, the PD of an obligor is estimated based on long-run average one-year default rates. While this may be an appropriate approach if there are no clear indications that the overall risk level will change, this does not hold if climate change risks increase in the future, and possibly increase systemic risks. By continuing to base a PD model on historical data only, especially for exposures with a time to maturity beyond a couple of years, the credit risk may be understated.

Are amendments to the prudential framework needed?

We have explained that there are several mechanisms in the prudential framework that allow environmental risks to be included in the P1C: the use of external credit ratings, the valuation of collateral, and the PD and LGD models used in the IRB approach. We have also seen, however, that it is questionable whether these mechanisms are fully effective. External credit ratings may not properly reflect all environmental risks and these risks may not be fully priced in on capital markets, leading to incorrect collateral values. Finally, a large share of the RWAs for credit risk depends on fixed RWs that are not (environmentally) risk-sensitive.

Consequently, it can be argued that amendments or enhancements to the prudential framework are needed. One must be careful, however, as the risk of double counting is just around the corner. Therefore, the following amendments or actions should be considered:

  • Further research should be undertaken to investigate the relationship between climate change risk and the creditworthiness of counterparties. If there is more clarity on this relationship, it should also be assessed to what extent this relationship is sufficiently reflected in external ratings. Requiring more advanced disclosures from credit rating agencies could help to understand whether these risks are sufficiently captured in the prudential framework. One should be cautious to amend the ratings-based RWs in the SA, since credit rating agencies are continuously working on the inclusion of environmental risks into their credit assessments; there would be a real risk of double counting.
  • The potential negative impact of climate change risks on collateral value should be further investigated. Financial institutions are already required by the ECB9 to consider environmental risks in their collateral valuations but this is not at a sufficient level yet. It will be important to consider the possibility of sudden value changes due to transition risks like shifting consumer sentiment or awareness.
  • To improve the risk-sensitivity of the framework, a dependency on the carbon emissions of the counterparty could be introduced in the fixed RWs, possibly only for the most carbon-intensive sectors. It could be argued that there are other factors that have a more significant relationship with the default risk of a certain counterparty that could be included in the SA. Climate change risks, however, differ in the sense that they can lead to a systemic risk (as opposed to an idiosyncratic risk) that is currently not captured in the overall level of the RWs.
  • In the SA, a distinction could be introduced based on the exposure’s time to maturity. For relatively short-term exposures, the current calibrations are probably fine. For longer-term exposures, however, the risks stemming from climate change may be underestimated as these are expected to increase over time.
  • In the IRB approach, a reflection of climate change risk would require the regulator to allow for forward-looking expert judgment in the (re)calibration of PD and LGD models. Further guidance from the competent authorities on the potentially negative impact on model performance based on historical data would also be useful.

Conclusion

Based on the schematic overview of the P1C requirements and the (potential) interaction with climate change risks, we conclude that several mechanisms in the prudential framework allow for climate change risks to be incorporated into the P1C. At the same time, we conclude that this interaction is limited to specific parts of the portfolio, and that in those cases it remains to be seen to what extent this is properly accounted for. To remedy this, amendments to the prudential framework could be considered. It is important, however, to avoid double counting issues and to be mindful of time horizon differences.

It is expected that the EBA will publish a final report on the prudential treatment of environmental risks in the first half of this year. However, especially financial institutions that are using the IRB approach should not take a wait-and-see approach. Given the complexity of modeling climate change risks, it is prudent to start incorporating climate change risks into PD and LGD models sooner rather than later.

With Zanders’ extensive experience covering both credit risk modeling and climate change risk, we are well suited to support with this process. If you are looking for support, please reach out to us.

1 Supporting factors are currently in place for SMEs and infrastructure projects, but the EBA advocated their removal.
2 See RBC20.1 in the Basel Framework.
3 See for example the results from the EBA’s EU-wide transparency exercise. This is reflected in Figure 1 by the percentage in the grey link between P1C and RWAs for credit risk.
4 See CRE20 to CRE22 in the Basel Framework.
5 See CRE30 to CRE36 in the Basel Framework.
6 In the Netherlands, less than 20% of the total RWAs is based on the SA. See the EBA’s EU-wide transparency exercise for more information. The percentages in the grey link between ‘Risk-weighted assets’ and ‘Methodology’ in Figure 1 are based on the European average.
7 See the EBA’s Risk assessment of the European banking system [2]. The percentages in the grey link between ‘Standardized Approach’ and the ‘Exposure class’ in Figure 1 reflect the share of RWAs in the SA for each of the different exposure classes.
8 The LtV is defined as the ratio between the loan amount and the value of the property that serves as collateral.
9 See expectation 8.3 in the ECB’s Guide on climate-related and environmental risks.

References

  1. The role of environmental risks in the prudential framework, European Banking Authority, Discussion Paper, 2 May 2022
  2. Risk assessment of the European banking system, European Banking Authority, December 2022
  3. Capturing risk differentials from climate-related risks, Network for Greening the Financial System, Progress Report, May 2022
  4. Disclosure of climate change risk in credit ratings, European Central Bank, Occasional Paper Series, No. 303, September 2022
  5. Pricing ESG risk in credit markets, Federated Hermes, March 2021
  6. Climate change and credit risk, Capasso, Gianfrate, and Spinelli, Journal of Cleaner Production, Volume 266, September 2020
  7. What do you think about climate finance?, Stroebel and Wurgler, Journal of Financial Economics, vol 142, no 2, November 2021
  8. Pricing of climate risks in financial markets, Bank for International Settlements, Monetary and Economic Department, December 2022
  9. Is flood risk already affecting house prices?, ABN AMRO, 11 February 2022
  10. Guide on climate-related and environmental risks, European Central Bank, November 2020

BCBS Principles for the effective management of climate-related financial risks

February 2023
5 min read

CEO Laurens Tijdhof explains the origins and importance of the Zanders group’s purpose.


These risks stem from the transition towards a low carbon economy and from the physical risks of damages due to extreme weather events. To address climate-related financial risks within the banking sector, the Basel Committee on Banking Supervision (BCBS) established a high-level Task Force on Climate-related Financial Risks in 2020. It contributes to the BCBS’s mandate to strengthen the regulation, supervision and practices of banks worldwide with the purpose of enhancing financial stability.

Both the BCBS’s Core principles for effective banking supervision1 and the Supervisory Review and Evaluation Process (SREP) within the existing Basel Framework are considered sufficiently broad and flexible to accommodate additional supervisory responses to climate-related financial risks. It was felt, however, that supervisors and banks could benefit from the publication of the Principles for the effective management and supervision of climate-related financial risks2. Through this publication, the BCBS seeks to promote a principles-based approach to improving risk management and supervisory practices regarding climate-related financial risks. The document contains principles directed to banks and principles directed to supervisory authorities. In this article, we present an overview of the principles directed to banks.

The BCBS published a draft of their Principles in November 2021. During the consultation phase, which lasted until February 2022, banks and supervisors could provide feedback. The BCBS incorporated their feedback in the final version of the Principles that were published in June 2022.

Principles for the management of climate-related financial risks

In total, twelve bank-focused principles are presented and grouped in eight categories. Each of the eight categories is briefly discussed below:

Corporate governance – Principles 1 to 3

The principles related to corporate governance state that banks first need to understand and assess the potential impact of climate risks on all fields they operate in. Subsequently, appropriate policies, procedures and controls need to be implemented to ensure effective management of the identified risks. Furthermore, roles and responsibilities need to be clearly defined and assigned throughout the bank. To successfully manage climate-related risks, banks should ensure an adequate understanding of climate-related financial risks and as well as adequate resources and skills at all relevant functions and business units within the bank. Finally, the board and senior management should ensure that all climate-related strategies are consistent with the bank’s stated goals and objectives.

Internal control framework – Principle 4

The fourth principle within the internal control framework subcategory requires banks to include clear definitions and assignment of climate-related responsibilities and reporting lines across all three lines of defense. Further requirements are then presented for each line of defense.

Capital and liquidity adequacy – Principle 5

After the identification and quantification of the climate-related financial risks, these risks need to be incorporated into banks’ Internal Capital (and Liquidity) Adequacy Assessment Process (ICLAAP). Banks should provide insights in which climate-related financial risks affect their capital and liquidity position. In addition, physical and transition risks relevant to a bank’s business model assessed as material over relevant time horizons, should be incorporated into their stress testing programs in order to evaluate the bank’s financial position under severe but plausible scenarios. Furthermore, the described incorporation in the ICLAAP to handle such financial risks, should be done iteratively and progressively, as the methodologies and data used to analyze these risks continue to mature over time.

Risk management process – Principle 6

The sixth principle connects to the previous one, as it states that a bank needs to identify, monitor and manage all climate-related financial risks that could materially impair their financial condition, including their capital resources and liquidity positions. The bank’s risk management framework should be comprehensive with respect to the (material) climate-related financial risks they are exposed to. Clear definitions and thresholds should be set for materiality. These need to be monitored closely and adjusted, if necessary, as climate-related risks are evolving.

Management monitoring and reporting – Principle 7

After ensuring that the risk framework is comprehensive, banks need to implement the monitoring and reporting of climate-related financial risks in a timely manner to facilitate effective decision-making. To achieve such reporting, a good data infrastructure should be in place at the bank. This allows it to identify, collect, cleanse, and centralize the data necessary to assess material climate-related financial risks. Furthermore, banks should actively collect additional data from clients and counterparties in order to develop a better understanding of their client’s transition strategies and risk profiles.

Management of credit, market, liquidity, operational risk – Principles 8 to 11

Banks should understand the impact of climate-related risk drivers on their credit risk profiles, market positions, liquidity risk profiles and operational risks. Clearly articulated credit policies and processes to identify, measure, evaluate, monitor, report and control or mitigate the impacts of material climate-related risk drivers on banks’ credit risk exposures should be in place. From a market risk perspective, banks should consider the potential losses in their portfolios due to climate-related risks. On the business operation and strategy side of banking activities, the impact of climate-related risks also plays a large role. For example, physical risks have to be taken into account when drafting business continuity plans. After understanding the different risks and their impacts, a range of risk mitigation options to control or mitigate climate-related financial risks need to be considered.

Scenario analysis – Principle 12

The final principle states that banks need to use scenario analysis to assess the resilience of their business models and strategies to a range of plausible climate-related pathways, and to determine the impact of climate-related risk drivers on their overall risk profile. Scenario analysis should reflect the overall relevant climate-related financial risks for banks, including both physical and transition risks. This analysis should be performed for different time horizons, both short- and long-term, and should be highly dynamic.

Changes to the BCBS risk framework draft and related publications

The final Principles have not changed much compared to the November 2021 consultation document. The most important changes are that the first principle, concerning corporate governance of banks, and the fifth principle, concerning capital and liquidity adequacy, have been extended. The corporate governance principle, for example, now also includes that banks should ensure that their internal strategies and risk appetite statements are consistent with any publicly communicated climate-related strategies and commitments. The capital and liquidity adequacy principle now includes a section requiring banks to incorporate material climate-related financial risks in their stress testing programs.

These twelve bank-focused principles, providing banks guidance on effective risk management of climate-related financial risks, can also be linked to the initiatives of other regulators such as the ECB. In November 2020, for example, the ECB provided a guide that describes how it expects institutions to consider climate-related and environmental risks, when formulating and implementing their business strategy, governance and risk management frameworks (the ECB expectations). These ECB expectations are in line with the BCBS Principles (and often more elaborate).

Zanders has gained relevant experience in implementing the ECB expectations at several Dutch banks. This experience ranges from risk identification and materiality assessments to the quantification of climate-related risks, ESG data frameworks, model validations, and scenario analysis. Please reach out to us if your bank is seeking support in implementing the BCBS Principles.

References
1) Basel Committee on Banking Supervision (2012). Core Principles for Effective Banking Supervision.
2) Basel Committee on Banking Supervision (2022). Principles for the effective management and supervision of climate-related financial risks.

Regulatory timelines ESG Risk Management

January 2023
5 min read

CEO Laurens Tijdhof explains the origins and importance of the Zanders group’s purpose.


In the below overview, we present an overview of the main ESG-related publications from the European Commission (EC), the European Central Bank (ECB), and the European Banking Authority (EBA).

This is complemented by the most important timelines that are stipulated in these regulations and guidelines. Additional regulations and guidelines that are expected for the next couple of years are also highlighted.

If you want to discuss any of them, don’t hesitate to reach out to our subject matter experts.

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