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  • 6 Interest Rate Risk in the Banking Book

    • 6.1 Scope

      6.1.1
             		For the purpose of this section, and in order to simplify technical considerations, both interest rate risk (for conventional products) and profit rate risk (for Islamic products) will be referred to as Interest Rate Risk in the Banking Book (“IRRBB”). Both lead to a similar structural risk on institutions’ balance sheet.
       
      6.1.2
             		Institutions should implement models to address the requirements articulated in “Interest rate and rate of return risk in the banking book Standards” issued by the CBUAE in 2018 (notice 165/2018), hereby referred to as the “CBUAE Standards on IRRBB”. In addition to the CBUAE Standards, institutions should refer to the Standards articulated by the Basel Committee on Banking Supervision in April 2016: “Interest rate risk in the banking book”, hereby referred as the “Basel Standards on IRRBB”.
       
      6.1.3
             		According to the CBUAE Standards on IRRBB, interest rate risk should be captured through changes in both (i) expected earnings and (ii) the economic value of the balance sheet. In order to ensure more homogeneity in the methodology employed by institutions across the UAE, the MMG hereby presents some guidance on IRRBB modelling. The IRRBB requirements related to governance, management, hedging and reporting are covered in a separate CBUAE Standards on IRRBB.
       

    • 6.2 Metrics

      6.2.1
             		Institutions should identify all positions in interest sensitive instruments including:
       
       (i)
             		All assets, which are not deducted from Common Equity Tier 1 (“CET1”) capital, and which exclude (a) fixed assets such as real estate or intangible assets and (b) equity exposures in the banking book.
       (ii)All liabilities, including all non-remunerated deposits, other than CE1 capital ; and
       (iii)
             		Off-balance sheet items.
       
      6.2.2
             		Institutions should reconcile their exposures against their general ledger and their published financials. Differences may arise for valid reasons, which should be documented. This reconciliation process should be included in the model documentation and should be verified by the finance team on a yearly basis.
       
      6.2.3
             		Changes in expected earnings and economic value can be captured through several possible metrics. At a minimum, the following metrics should be computed. These are referred as “IRRBB metrics”:
       
       (i)
             		Gap risk: It is defined as the difference between future cash in-flows and cash-outflows generated by both assets and liabilities. The cash in-flows and out-flows are derived from the allocation of all relevant interest rate sensitive instruments into predefined time buckets according to their repricing or their maturity dates. These dates are either contractually fixed or based upon behavioural assumptions. The resulting metrics is the net position (gap) of the bank per future time bucket.
       (ii)
             		Gap risk duration: Also referred to as partial duration or partial “PV01”. It is defined as the modified duration of the gap per maturity bucket. The modified duration is the relative change in the present value of the position caused by a 1 basis point change in the discount factor in a specific maturity bucket. The resulting metrics is a term structure of PV01 per maturity bucket.
       (iii)
             		Economic value of equity: Also referred to as “EVE”. It is defined as the difference between the present value of the institution’s assets minus the present value of liabilities. The change in EVE (“∆EVE”) is defined as the difference between the EVE estimated with stressed discount factors under various scenarios, minus the EVE estimated with the discount factors as of the portfolio reporting date.
       (iv)
             		Net interest income: For the purpose of the MMG, and in order to simplify notations, both Net Interest Income (for conventional products) and/or Net Profit Income (for Islamic Products) are referred to as “NII”, defined as the difference between total interest (profit) income and total interest (profit) expense, over a specific time horizon and taking into account hedging. The change in NII (“∆NII”) is defined as the difference between the NII estimated with stressed interest rates under various scenarios, minus the NII estimated with the interest rates as of the portfolio reporting date. ∆NII is also referred to as earning at risk (“EAR”).
       

    • 6.3 Modelling Requirements

      6.3.1
             		The models employed to compute the metrics above should follow the principles articulated in the MMS. In particular all IRRBB models should follow the steps in the model life-cycle. The assumptions and modelling choices surrounding IRRBB models should not be the sole responsibility of the ALM function nor the market risk function. Rather, these assumptions should be presented to and discussed at the appropriate governance forum reporting to the Model Oversight Committee.
       
      6.3.2
             		The modelling sophistication of the EVE should depend upon the size and complexity of institutions. For that purpose, different requirements are defined in function of their systemically important nature. The modelling requirements presented hereby should be regarded as minimum standards. To remain coherent with Basel principles, higher standards apply to large and/or sophisticated institutions (“LSI”). However, the other institutions may choose to implement models with higher standards than the one prescribed for them. This proportionality is an exception to the MMG due to the prescriptive nature of the Basel methodology surrounding IRRBB.
       
      6.3.3
             		The requirements below refer to the methodology articulated in section IV (“The standardised framework”) of the Basel Standards on IRRBB. All institutions are requirements to fully understand this framework.
       

             		Table 10: Components of IRRBB models
       
      ComponentLSIsOther institutions
      Computation
      granularity      		Facility level or facility type if groups of facilities are homogeneousSummation of facilities within buckets, according to the Basel Standards
      Time bucketsGranular bucketing depending on the composition of the booksStandardised bucketing according to the Basel Standards on IRRBB
      Option riskIncluded in both EVE and NIIIncluded in EVE
      Optional from NII
      Commercial marginsOptional from EVE
      Included in NII      		Optional from EVE
      Included in NII
      Basis riskIncludedOptional
      CurrencyEstimation for each material currencyEstimation for each material currency
      ScenariosStandard plus other scenarios defined by institutionsStandard six scenarios
      IT-systemDedicated systemSpreadsheets can be used if the model and its implementation are independently validated

       

      6.3.4
             		The estimation of EVE should be based upon the following principles: (a) it includes all banking book assets, liabilities and off-balance sheet exposures that are sensitive to interest rate movements, (b) it is based on the assumption that positions roll off, and (c) it excludes the institution’s own equity. The approach subsequently depends on the type of institutions.
       
       (i)
             		LSIs should compute EVE as the difference between discounted assets and liabilities at a granular level. Institutions should aim to perform this computation at a facility level. For practical reasons, some facilities could be aggregated, provided that they are homogeneous and share the same drivers and features. All inputs including, but not limited to, cash-flows, time buckets, risk-free rates, option risk and basis risk should also be estimated at a granular level.
       (ii)
             		It should be noted that the Gap risk and the Gap risk duration are not directly used to estimate EVE in the context of a granular full revaluation. However, the Gap risk and Gap risk duration should be estimated and reported in order to manage IRRBB.
       (iii)
             		Non-LSI can compute EVE at a higher level of granularity, according to the principles outlined in the Basel Standards on IRRBB and in particular according to article 132. The methodology is based upon the summation of discounted Gap risk across time buckets, rather than a granular NPV estimation at facility level. Institutions should pay particular attention to the cash flow allocation logic in each time bucket.
       (iv)
             		Irrespective of their size, all institutions should compute ?EVE as the difference between EVE estimated under interest rate scenarios and the EVE under the current risk-free rates. The final EVE loss and the standardised risk measure employed in Pillar II capital should be computed according to the method explain in the article 132 (point 4) of the Basel Standards on IRRBB, whereby EVE loss should be aggregated across currencies and scenarios in a conservative fashion.
       
      6.3.5
             		The estimation of NII should be based upon the following principles: (a) it includes all assets and liabilities generating interest rate revenue or expenses, (b) it includes commercial margins and (c) no discounting should be used when summing NII across time buckets. The approach subsequently depends on the type of institutions.
       
       (i)
             		LSIs should compute NII at a granular level, both for facilities and maturity time steps. NII should be based on expected repricing dates upon institutions’ business plan of future volume and pricing. Therefore LSIs should estimate ∆NII as the difference in NII under the base and the stress scenarios. Such granular computation should include option risk and basis risk.
       (ii)
             		Non-LSIs can compute ?NII by allocating interest revenue and interest expenses in the standardised time buckets used for EVE. Non-LSI institutions can compute ?NII by estimating directly their earning at risk on each expected repricing date.
       (iii)
             		For the purpose of risk management, institutions are free to model NII based on static or dynamic balance sheet assumptions (although LSIs are recommended to employ the latter). Institutions can also choose the NII forecasting horizon. However, for Pillar II assessment as part of the ICAAP and for reporting to the CBAUE, the following, institutions should compute NII over 1 year; in addition LSIs should also compute NII over 3 years.
       
      6.3.6
             		Institution’s own equity: For NII estimation, institutions should include interest-bearing equity instruments. For EVE, in the context of the MMG, institutions should compute two sets of metrics by first including and then excluding instruments related their own equity. These two types of EVE will be used for different purposes.
       
       (i)
             		CET1 instruments should be excluded at all times to avoid unnecessary discrepancies related to the choice of behavioural maturity associate to this component.
       (ii)
             		Some institutions have a large proportion of interest-sensitive instruments, in particular in the AT1 components. Consequently, these institutions should estimate and report a first set of EVE sensitivities by including these instruments. This type of EVE is useful for proactive management of IRRBB.
       (iii)
             		Conversely, one of the objectives of assessing IRRBB is to ensure that institutions hold enough capital to cover such risk, which is articulated through the ICAAP. Institutions should not use part of their capital to cover a risk that is itself generated from capital. Therefore, institutions should also compute and report EVE by excluding their own equity entirely. This type of EVE is useful to estimate the Pillar II capital charge arising from IRRBB.
       
      6.3.7
             		Commercial margins: The treatment of commercial margins is different between NII and EVE. However, the recommendation is similar for both LSIs and non-LSIs.
       
       (i)
             		All institutions should include commercial margins in NII estimation. Margins should be adjusted based on business plans and expected customer behaviour in a given interest rate environment. For instance, it might be assumed that margins will be increased to retain depositors in a falling interest rate environment.
       (ii)
             		All institutions have the option to include or exclude commercial margins in EVE estimation. However, institutions should also aim to estimate the impact of commercial margins on EVE. For consistency, if margins are included in the cash flows (numerator), then discount factors should also reflect the corresponding credit spread of the obligors (denominator). Such estimation should be done at homogeneous pools obligors with similar credit risk profiles.
       
      6.3.8
             		Basis risk: This risk arises when assets and liabilities with the same tenor are discounted with different ‘risk-free’ interest rates. Potential credit risk embedded in these rates makes them not entirely risk-free, hence the existence of bases. A typical example is an asset priced with the US LIBOR curve but funded by a liability priced with the US Overnight Index Swap (“OIS”) curve, thereby creating an LIBOR-OIS basis leading to different NPV and NII from both the asset and the liability. Another example is the recent introduction of USD Secured Overnight Financing Rate (“SOFR”) creating a LIBOR-SOFR basis. LSIs are required to fully identify and assess basis risk. They should employ the appropriate risk-free rate for each instrument type, thereby capturing basis risk in all the IRRBB metrics. While non-LSIs are not expected to fully quantify basis risk on a regular basis, they should perform an approximation of this risk to assess whether further detailed quantification is necessary.
       
      6.3.9
             		Currency risk: The currencies of assets and liabilities have a material impact on the resulting IRRBB, therefore this dimension should be fully addressed by institutions’ modelling practice.
       
       (i)
             		All the IRRBB metrics should be estimated for each currency in which the institution has material exposures, i.e. when the gross exposure accounts for more than five percent (5%) of either the gross banking book assets or gross liabilities. For those, the interest rate shocks should be currency-specific.
       (ii)
             		For the estimation of the capital charge, the Basel Standards on IRRBB suggests to sum the maximum change in EVE across currencies without offsetting. While the CBUAE recognises that no offsetting is conservative for pegged currencies, (typically USD/AED), institutions should manage basis risk appropriately since material bases have been observed between USD rates and AED rates. Consequently, each institution has the option to offset ?EVE between pegged currencies, only if it can demonstrate that it does capture the basis risk between these currencies with dedicated stress scenarios.
       
      6.3.10
             		Non-performing assets (“NPA”): Institutions should define clearly the treatment of non-performing assets in their modelling practice, according to the following principles.
       
       (i)
             		NPA (net of provisions) should be included in the estimation of EVE. In most default cases, LGD>0% therefore a recovery is estimated at some point in the future. The LGD is estimated by discounting expected recoveries with a discount rate generally based on the effective interest rate of the facility. In the context of IRRBB, a change in the interest rate environment should have an impact the present value of discounted recoveries and therefore on LGD. This effect could likely impact EVE. Finally, consideration should also be given to rescheduled facilities and/or forbearance with payment holidays where interests are accrued. The postponement could results in lower PV under scenarios with increasing rates.
       (ii)
             		The treatment of NPA (net of provisions) for NII computation is left to the discretion of banks. Under a static balance sheet assumption, non-performing assets will not generate cash inflows. A change in rates would have no impact the NII from such assets. However, under dynamic a balance sheet assumption, some NPA could return to a performing status and therefore impact NII.
       

    • 6.4 Option Risk

      6.4.1
             		Option risk constitutes a fundamental building block of IRRBB. Option risk is defined as the potential change of the future flows of assets and liabilities caused by interest rate movements. In the context of the MMG, option risk refers to deviations from either contractual maturity or expected behavioural maturity. Consequently, these options can be explicit or implicit. The exercise of these options are a function of the contractual features of the product, the behaviour of the parties, the current interest rate environment and/or the potential interest shocks. All institutions should capture option risks, irrespective of their size and sophistication.
       

             		Table 11: Categories of option risk
       
      Financial productRiskBehavioural triggerAutomatic trigger
      Non-maturing depositsEarly redemption riskYesNo
      Fixed rate loansPrepayment risk and restructuring riskYesNo
      Term depositsEarly redemption riskYesNo
      Automatic interest rate optionsEarly redemption risk and prepayment riskNoYes

       

      6.4.2
             		In order to model option risk appropriately, all institutions should, at a minimum, undertake the following steps:
       
       (i)Identify all material products subject to embedded options,
       (ii)Ensure that assumptions employed in modelling are justified by historical data,
       (iii)
             		Understand the sensitivity of the IRRBB metrics to change in the assumptions related to option risk, and (iv) Fully document the method and assumptions used to model option risk.
       
      6.4.3
             		LSIs should incorporate option risks at a granular level and undertake the necessary analysis to substantiate their assumptions. Option risk can be modelled and estimated at an aggregated level that displays similar behavioural characteristics, but the model results should be applied as a granular level. For that purpose, LSIs can use the standardised approach as a starting point and elaborate on it, in such a way that the approach meets the size and complexity of the institution. Ultimately, cash flows from assets and liabilities should be conditional upon the level of interest rates in each scenario. The methodology and assumptions employed to model optionality should be fully documented.
       
      6.4.4
             		Non-LSIs should use the EVE approach articulated in the Basel Standards on IRRBB, whereby option risk is incorporated via the dependency of cash flows on interest rate levels by using conditional scalers. Subsequently, under each stress scenario with specific interest rate shocks, institutions should employ a different set of netted cash flows per bucket to compute EVE. In other words and using the Basel formulation, the cash flow CFi,c(tk) should vary for each interest rate scenario, where i, c and tk are respectively the interest rate scenario, the currency and the time bucket. The below steps explain further the standardised approach.
       
      6.4.5
             		Non-maturity Deposits (“NMD”): All institutions should model option risk for NMD, as described in the Basel Standards on IRRBB, from article 110 to 115. The objective is to assess the behavioural repricing dates and cash flow profiles of NMD. In particular, institutions should undertake the following steps:
       
       (i)
             		Segregate NMD into categories of depositors, considering at a minimum, retail clients, wholesale clients and Islamic products.
       
       (ii)
             		Identify stable and core deposits, defined as those that are unlikely to be repriced, even under significant changes in the interest rate environment. For that purpose, institutions should analyse historical patterns and observe the change in volume of deposits over long periods. Institutions should describe the data sample and the statistical methodology used for this analysis.
       (iii)
             		For each segment, apply the caps mentioned in Table 2 of the Basel Standards on IRRBB and allocate the cash flows in the appropriate time bucket based on their estimated maturity.
       (iv)
             		Construct assumptions regarding the proportion of core deposits and their associated maturity under each interest rate scenario and in particular the potential migrations between NMD and other types of deposit. These assumptions should reflect the most likely client behaviour but with a degree of conservatism. Institutions should bear in mind the importance of portfolio segmentation on behavioural modelling.
       
      6.4.6
             		Fixed rate loans: Such instruments are subject to prepayment risk because a drop in interest rates is susceptible to accelerate their early prepayment. In addition, restructuring events can also change their expected cash flow profiles. Consequently, all institutions should implement the approach mentioned in articles 120 to 124 of the Basel Standards on IRRBB. In particular, institutions should proceed as follows.
       
       (i)Business-as-usual prepayment ratios should be estimated per product type and per currency.
       (ii)
             		These ratios should be multiplied by the scalers in Table 3 of the Basel Standards on IRRBB, that depend on the interest rate shock scenarios, in order to derive adjusted prepayment rates. If the institution has already defined prepayment rates under each scenario based on its own internal historical data, then it can use these rates, provided that they are fully documented and justified. Portfolio concentration and segmentation should be taken into account when performing such behavioural modelling.
       (iii)
             		The adjusted prepayment rates should be employed to construct the repayment schedule under a given scenario. The choice of the time buckets where the prepayments are made, should also be justified and documented.
       
      6.4.7
             		Term deposits: Such instruments are subject to redemption risk because an increase in interest rates is susceptible to accelerate their early withdrawal. Consequently, all institutions should implement the approach mentioned in the articles 125 to 129 of the Basel Standards on IRRBB. In particular, institutions should proceed as follows:
       
       (i)Business-as-usual redemption ratios should be estimated per product type and per currency.
       (ii)
             		These ratios should be multiplied by the scalers in Table 4 of the Basel Standards on IRRBB, that depend on the interest rate shock scenarios, in order to derive adjusted redemption rates.
       (iv)
             		The adjusted redemption rates should be used to derive the proportion of outstanding amount of term deposits that will be withdrawn early under a given scenario. If the institution has already defined redemption rates under each scenario based on its own internal historical data, then it can use these rates, provided that they are fully documented and justified. Portfolio concentration and segmentation should be taken into account when performing such behavioural modelling.
       (iii)
             		That proportion is finally allocated to the overnight time bucket, per product type and per currency, as per article 127 of the Basel Standards on IRRBB.
       (iv)
             		Finally, institutions should take into consideration off-balance sheet exposures in the form of future loans and expected drawings on committed facilities.
       
      6.4.8
             		Automatic interest rate options: All institutions should follow the methodology articulated in the Basel Standards on IRRBB in articles 130 to 131. Automatic interest rate options should be fully taken into account in the estimation of both EVE and NII.
       

    • 6.5 Interest Rate Scenarios

      6.5.1
             		All institutions should compute ∆EVE and ∆NII under the six scenarios prescribed in Annex 2 of the Basel Standards on IRRBB and pasted in the following table. The interest rate shocks for AED can be directly derived from those corresponding to USD. For convenience, the AED shocks have been computed and provided below. For other currencies, all institutions should compute themselves the corresponding interest shocks based on the methodology outlined in the Basel Standards on IRRBB. The six interest rate shocks are as follows:
       
       (i)Parallel shock up,
       (ii)Parallel shock down,
       (iii)Steepener shock (short rates down and long rates up),
       (iv)Flattener shock (short rates up and long rates down),
       (v)Short rates shock up, and
       (vi)
             		Short rates shock down.
       
      6.5.2
             		In addition to the standard shocks prescribed by the Basel Standards on IRRBB, LSIs should define other scenarios combining shift of yield curves with changes in basis and commercial margins in order to comprehensively capture the risk profile of their balance sheet structure. These institutions should ensure that scenarios are commensurate with the nature, and complexity of their activities.
       

             		The choice of scenarios should be supported by an appropriate governance and fully documented. All institutions should integrate the IRRBB scenarios and results in their stress testing framework and in enterprise-wide stress testing exercises.
       

             		Table 12: Standard shocks per scenario (bp) for AED prescribed by the BIS method
       
      Time Buckets (M: months ; Y: Years)Tenors
      (years)      		(i)(ii)(iii)(iv)(v)(vi)
      Short-Termt = Overnight (O/N)0.0028200-200-195240300-300
      O/N < t <= 1M0.0417200-200-192237297-297
      1M < t <= 3M0.1667200-200-182227288-288
      3M < t <= 6M0.375200-200-165210273-273
      6M < t <= 9M0.625200-200-147192257-257
      9M < t <= 1Y0.875200-200-130175241-241
      1Y < t <= 1.5Y1.25200-200-106151219-219
      1.5Y < t <= 2Y1.75200-200-78123194-194
      Medium-Term2Y < t <= 3Y2.5200-200-4287161-161
      3Y < t <= 4Y3.5200-200-348125-125
      4Y < t <= 5Y4.5200-200281797-97
      5Y < t <= 6Y5.5200-20052-776-76
      6Y < t <= 7Y6.5200-20070-2559-59
      Long-Term7Y < t <= 8Y7.5200-20084-3946-46
      8Y < t <= 9Y8.5200-20096-5136-36
      9Y < t <= 10Y9.5200-200104-5928-28
      10Y < t <= 15Y12.5200-200121-7613-13
      15Y < t <= 20Y17.5200-200131-864-4
      t > 20Y25200-200134-891-1

       

      6.5.3
             		Institutions should consider the possibility of negative interest rates and understand the impact on their balance sheet and business models. For each asset and liability, if the legal documentation of the contract stipulates a certain treatment of negative rates, then this treatment should be used. If the legal documentation is silent on the treatment of negative rates, then such negative rates should be used to price assets, but they should be floored at 0% for deposits (liabilities) because there is little evidence supporting the assumption that both retail and corporate clients would accept being charged for depositing their funds in UAE banks.
       
       

    • 6.6 Validation of EVE and NII Models

      6.6.1
             		Institutions should validate all EVE and NII models according to the principles articulated in the MMS and in particular related to model life cycle management.
       
      6.6.2
             		The validation of EVE and NII models should be based upon the principles articulated for both deterministic and statistical models. The validation exercise should ensure that modelling decisions are justified and documented and cover all the model components presented in the previous sections. In particular, the appropriate use of data input should also be reviewed by the validator.
       
       (i)
             		The validator should ensure that the mechanistic construction of these models is sound. This should be tested with partial replication and internal consistency checks.
       (ii)
             		The validator should ensure that the financial inputs are correctly flowing into these models. This step may require the join work between several teams including the risk and finance teams.
       (iii)
             		The validator should ensure that the results produced by these models are coherent. For that purpose sensitivity analysis can be performed.
       (iv)
             		Finally, some of the inputs are derived from statistical models, including the behavioural patterns observed for non-maturity deposits, fixed rate loans and term deposits. Consequently, the validation should consider the robustness, stability and accuracy of the ancillary statistical models employed to derived inputs to EVE and NII models.
       
      6.6.3
             		Overall, the validation process of EVE and NII models should focus on the economic meaning and business intuition of the model outputs. The development and validation processes should not be dominated by the mechanistic aspect of these models, but also ensure that those are suitably designed to support robust decision making and the appropriate management of interest rate risk in the banking book.