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Basel III Endgame

The next generation of risk-weighted assets

The Basel Committee for Banking Supervision (BCBS) proposed finalization of Basel III encompasses so many changes that the industry started referring to it as Basel III Endgame. Basel III Endgame changes the calculation of risk-weighted assets (RWA) which will have a significant impact on business models and forces banks to rethink their capital allocation strategies.

BCBS published its final documents on the reform of Basel III in December 2017, which are now commonly referred to as “Basel III Endgame.” In the interim, implementation of Basel III Endgame has been deferred to January 2023, and the US Federal Reserve has yet to publish their final ruling. However, understanding the potential impacts of Basel III Endgame now is key, and will give firms a head start in implementation efforts once the final ruling is published.

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Credit Risk - Standardized Approach

Key changes to Basel III

  • Introduces due diligence requirements for certain types of counterparties

  • Adds more granular counterparty types (e.g. specialized lending), with distinct risk-weighting rules

  • Increases requirements for meeting certain treatments (e.g. real estate secured)

  • Segregates real estate exposure risk weights based on Loan-To-Value (LTV)

Key considerations for Basel III Endgame

  • Credit card impact will be driven by customer behavior

  • Real estate exposure may receive relief

  • Corporate impact will be driven by counterparty type

  • New exposure classes require system changes

  • Impact will vary based upon business model

Key considerations when implementing Credit Risk-SA

Credit card impact will be driven by customer behavior

The CCF for unused consumer credit balances will increase from 0% to 10%.

Credit limit increases and customer spend behavior (e.g., “transactor” vs “revolving”) will directly impact capital requirements.

The ability to forecast expectations on both of these aspects should be a part of capital planning.

Real estate exposure may receive relief

Introduction of risk weights scaled based on LTV band for commercial and residential real estate mortgages will likely provide a significant RWA benefit for banks’ real estate portfolios with lower LTVs.

Corporate impact will be driven by counterparty type

A reduced risk weight is proposed for Investment Grade (IG) corporate exposures with public securities (100% to 65%) and for small and medium sized (SME) (100% to 75% or 85%) enterprises.

New exposure classes require system changes

New exposures classes to the US SA for Credit Risk introduced, including retail, specialized lending and commercial real estate. New exposure classes require banks to update their exposure classification systems, processes and data.

Impact will vary based upon business model

Meaningful insights require more granular impact analysis to identify business impacts, refine capabilities, and identify opportunities and challenges.

Overcoming Credit Risk-SA implementation challenges

Business model impact

Common issues achieving Credit Risk-SA requirements
  • Certain exposure classes see significant changes in RWA (e.g. Credit cards). There will be significant impacts on the banks’ business models.
  • Historically, the US regulators have deviated from BCBS proposed rules. Determining the full impact to your business model requires more certainty from regulators.
Approach to addressing these issues
  • Start with regular impact assessments with a range of outcomes. Meaningful insights require more granular impact analysis to identify business impacts, refine capabilities, and identify opportunities and challenges.
  • Implementation of the known and stable elements of the proposed rules offers earlier insight into your capabilities and accelerates identification of where your system and data infrastructure may be lacking and start building flexible capabilities which allow for implementation of different outcomes.

Technology and operational processes

Common issues achieving Credit Risk-SA requirements
  • More granular requirements for counterparties to be eligible for favorable risk weightings, requiring incremental analysis and data (e.g., Transactors vs. revolving for credit credit cards, LTV for CRE, CET1 ratio for banks).
  • Reclassification of counterparties to align to more granular risk weight categories, new categories and corresponding updates to systems.
  • Updates to systems to reflect more granular calculation logic for banks, corporations, real estate and specialized lending.
Approach to addressing these issues
  • Start collecting essential data elements for areas where the most relief can be achieved (e.g. 12 month repayment data for credit cards).
  • The rules incentivize having the required data elements, investing in a proper data infrastructure may be worth it.
  • System enhancements, business rule changes and data requirements associated with Basel III Endgame implementation should be coordinated with other critical in-flight programs.

Interaction with other rules and capital planning

Common issues achieving Credit Risk-SA requirements
  • Interacting parts of the rule (e.g. SA-CCR, Securitizations, IRB approach) mean full impact will only be known when all parts have been Implemented.
  • Changes will impact other regulations besides RWA (e.g. Single Counterparty Credit Limits, Leverage Ratio). Changes have to be assessed comprehensively.
  • SA-CR is the starting point for CCAR stress tests. Understanding the full impact of the changes requires assessing the impact on CCAR as well.
Approach to addressing these issues
  • Business engagement and ownership in the implementation process is essential for effective capital planning and development of mitigation strategies.
  • Centralized and comprehensive impact studies allow for a thousand foot view on impact to the combined impact of the changes.

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Credit Risk - Internal Ratings Based Approach

Key changes to Basel III

  • Introduces restrictions on which type of counterparties the IRB Approach may be used
  • Applies floors to Probability of Default (PD), Loss Given Default (LGD) and Credit Conversion Factor (CCF) to the portfolios that remain eligible for the use of the advanced approach

Key considerations for Basel III Endgame

  • Uncertain if US regulators will allow F-IRB approach
  • IRB approach may become the RWA floor
  • A reduced scope in IRB may lead to higher RWA

Key considerations when implementing Credit Risk-IRB

Uncertain if US regulators will allow Foundation IRB (F-IRB) approach

BCBS proposes to discontinue Advanced IRB (A-IRB) for equities, large corporates and banks. US regulators never implemented F-IRB under Basel II, so there is significant uncertainty regarding implementation.

IRB approach may become the RWA floor

Increase of PD and LGD floors and introduction of Supervisory-set LGD’s, may result in higher RWA under the Advanced Approach. Changes in PDs, LGDs resulting in higher RWA may result in the Advanced Approach becoming the RWA floor under the Collins Amendment, shifting capital planning and allocation practices.

A reduced scope in IRB may lead to higher RWA

Basel III Endgame narrows the applicability of the Advanced IRB approach for equities, large corporates and banks. Using the F-IRB approach or SA generally leads to higher RWA.

Overcoming Credit Risk-IRB impact implementation challenges

Capital allocation and planning

Common issues achieving IRB requirements
  • Revised approach to capital allocation and optimization for portfolios for which IRB will still be eligible.
  • Allocation of capital may become a mix of the SA, F-IRB, A-IRB, CCAR and economic capital models.
  • Global banks will have to deal with local regulators implementing rules differently, making business model impact geographically specific.
Approach to addressing these issues
  • Start with regular impact assessments. Meaningful insights require more granular impact analysis to identify business impacts, refine capabilities, and identify opportunities and challenges.
  • Assess per exposure class the incremental effort and benefit of using SA, A-IRB or F-IRB.
  • Constraints to the use of IRB allows banks to apply IRB per exposure class. This allows for optimization of exposures classes in effort and capital requirements, within supervisory expectations.

Technology and operational processes

Common issues achieving IRB requirements
  • Additional data requirements on collateral type for calibration of LGD for secured corporate and retail exposures.
  • Redundant historical databases and models used for parameters estimation of observations.
  • Historically, the US regulators have deviated from BCBS proposed rules. Determining the full impact to your business model requires more certainty from regulators.
Approach to addressing these issues
  • Implementation of the known and stable elements of the proposed rules offers earlier insight into your capabilities and accelerates identification of where your system and data infrastructure may be lacking.
  • Build infrastructure components that allow for flexible implementation of new rules.
  • Establish roll-out plans for exposure classes where the approach changes and assess the need for systems, processes, data and reporting requirements going forward.

Modeling practices

Common issues achieving IRB requirements
  • Due to the greater specification in the rules about how to determine model parameters, reassessment and recalibration of PD, LGD and EAD may be needed.
  • Re-thinking of model structure for segments with issues on collateral recovery data for LGD estimates based on a mix of own LGD—for unsecured part—and regulatory LGDs for the secured part of exposure.
  • Under A-IRB, guarantees and credit derivatives must apply method used to determine the RW % for a direct exposure to the guarantor or protection seller.
Approach to addressing these issues
  • Assess current modeling practices against updated parameter requirements for A-IRB and F-IRB to determine potential gaps.
  • Change models, e.g. insured / guaranteed products might need to be out-scoped from LGD model development activities.

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Standardized Approach - Counterparty Credit Risk

Key changes to Basel III

  • Replaces the Current Exposure Method (CEM)
  • Introduces hedging sets for specific asset classes
  • Provides better recognition of secured and cleared trades
  • Introduces increased risk sensitivity by addressing over-collateralisation and negative market values

Key considerations for Basel III Endgame

  • Increased data granularity results in more precise calculations
  • Optimization focuses on net exposure rather than gross notional reduction
  • Allocation of netting set level Exposure At Default (EAD) to trades and “what-if” analysis can improve capital management

Key considerations when implementing SA-CCR

Increased data granularity results in more precise calculations

SA-CCR’s EAD calculation is based on over 100 data elements that include trade, collateral, hedging set and counterparty information.

Robust data management practices for sourcing this granular data can improve the precision of the calculation and reduce exposure.

Optimization focuses on net exposure rather than gross notional reduction

Netting of offsetting exposures will shift the focus of portfolio optimization from reducing gross notional exposures to reducing net exposure.

Netting of offsetting exposures may change the relative costs of some products, e.g., reducing the exposure from interest rate swaps but increasing the exposure from foreign exchange products.

Revised netting set and “what-if” analysis improves capital management

Netting of offsetting transactions makes it no longer possible to see the capital charge associated with each trade.

Development of an allocation methodology and the ability to run “what-if” analysis can help to understand the capital charge of a trade before it is booked.

Overcoming SA-CCR implementation challenges

Data requirements

Common issues achieving SA-CCR requirements
  • Increased complexity with multiple data sources.
  • Lack of standard nomenclature of derivative and long dated settlement product types to map to SA-CCR requirements.
  • Data redundancy within risk systems.
  • Linkage of transaction data to client reference data such as netting, collateral, margin information, etc.
  • Decomposition of complex products such as digital options.
Approach to addressing these issues
  • Approach to addressing these issuesApproach to addressing these issuesEnhance and streamline data governance across front-office and risk systems.
  • Create a standardized nomenclature across all derivative and long dated settlement products to facilitate integration with the rest of the ecosystem.
  • Normalize database layers to remove data redundancy and develop a data lineage document to identify single source of truth for a data element.

Technology and operational processes

Common issues achieving SA-CCR requirements
  • Inconsistent and redundant data infrastructure and lack of data lineage across market risk, credit risk, business unit risk and profit / loss controller groups.
  • Organize and streamline data storage and pipelines in order to accommodate increased data volume demands.
  • Ineffective document governance leads to increased time in locating correct version of data transformation documentation.
Approach to addressing these issues
  • Build a SA-CCR data interface layer with a standardized list of data elements for standard derivative and long dated settlement product types from all data sources.
  • Assess and develop a plan to procure additional computing resources to manage the data volume demands.
  • Implement development framework to accelerate release process.

Calculator documentation and validation

Common issues achieving SA-CCR requirements
  • Lack of end-to-end testing plan buildout for User Acceptance Testing of all product type from each data source.
  • Increased complexity with calculation of EAD for complex products at an aggregated and disaggregated level.
  • Lack of an effective challenger calculator to validate test results from the SA-CCR calculator.
Approach to addressing these issues
  • Develop an end-to-end testing plan for all product types from each data source.
  • Leverage a third party Challenger SA-CCR calculator to validate test results from the SA-CCR calculator.

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Fundamental Review of the Trading Book / Credit Valuation Adjustment

 Key changes to Basel III

  • Introduces risk sensitivity-based Standardized Approach (SA) calculations for market risk capital floor
  • Internal Model Approach (IMA) requires enhanced considerations
  • CVA Internal Model Method (IMM) will not be allowed
  • Introduces product-based banking boundary versus trading book

Key considerations for Basel III Endgame

  • Infrastructure and growth plans dictate IMA versus SA election
  • Systems/operational overhaul may be more optimal
  • IMA risk factor governance is a significant hurdle
  • CVA-SA suited for sophisticated CVA models and hedging
  • Reoptimization of banking vs trading designation

Key considerations when implementing FRTB/CVA

Infrastructure and growth plans dictate IMA versus SA election

Electing IMA can be costly and costs depends on trading desk.

For larger/growing flow businesses with liquid underlying products, investing in infrastructure to get IMA approval is recommended.

For smaller desks and/or less liquid and complex desks, IMA approval is too costly.

Systems/operational overhaul may be more optimal

FRTB is significantly more complex in calculations, governance and data needs, especially for IMA trading and CVA-SA.

Depending on current state and scope of infrastructure, it may be more optimal to overhaul operating model of current risk/modeling/PnL infrastructure and process for long term sustainability.

IMA risk factor governance is a significant hurdle

Getting and maintaining IMA approval requires careful selection of risk factors that has appropriate depth to explain PnL in PLA/backtesting and also has sufficient market observable price discovery per FRTB prescription (RFET).

Governance around market data will require upgrades to related processes and potential streamlining of front-to-back market data.

CVA-SA suited for sophisticated CVA models and hedging

CVA-SA allows for more capital efficiency if the bank can demonstrate proper governance around CVA trading desk set up and models/calculations on par with industry standard.

If bank has material CVA hedging program, investing in upgrading infrastructure and governance to utilize CVA-SA is desirable.

Reoptimization of banking vs trading designation

FRTB requires reclassification of banking and trading book based on highly prescriptive product based designations, which can lead to significant added governance.

This change may require reoptimization of strategy and hedges, as needed.

Overcoming FRTB/CVA implementation challenges

Data requirements

Common issues achieving FRTB/CVA requirements
  • For IMA, increased operational complexity with multiple data sources e.g. improve RFET eligibility, including tracking internal trade quotes.
  • For SA, harmonizing sensitivity calculations across all systems/business units and conforming to BCBS prescribed risk buckets.
Approach to addressing these issues
  • Enhance and streamline data governance across front office and risk systems.
  • Create a standardized nomenclature across all reference products.
  • Normalize database layers to enable cloud computing and add elasticity.

Technology and operational processes

Common issues achieving FRTB/CVA requirements
  • Inconsistent and redundant data infrastructure across market risk, credit risk, BU Risk and PnL controller groups.
  • Computational needs, e.g. PLA full revaluation enhancements.
  • Increased data volume demand.
Approach to addressing these issues
  • Ensure that risk systems are streamlined/upgraded and are consumable by downstream models (e.g., Market/Credit/BU Risk, PnL controller).
  • Implement development framework to accelerate upgrade process.
  • Reassess depth and timeliness of business processes and governance.

Model documentation and validation

Common issues achieving FRTB/CVA requirements
  • New PLA test requires significant governance and front office pricing models to synchronize with back office risk models.
  • Products with pricing gaps during stress periods are problematic.
Approach to addressing these issues
  • Gap analysis for PLA tests for key products/desks/models.
  • Improve front to back governance processes, e.g create process to monitor cliff effects if desk become IMA ineligible during stress period.

Overlap with LIBOR transition

Common issues achieving FRTB/CVA requirements
  • FRTB implementation will compete for same resources at same time as LIBOR transition, creating significant overload and delivery risks during 2021-23.
  • For new interest rates risk factors associated with LIBOR transition, there may not be sufficient history of market data.
Approach to addressing these issues
  • Anticipate overload and delivery risks and dedicate resources to simultaneously implement FRTB and LIBOR transition.
  • Develop data as needed for new interest rate risk factors per FRTB requirements.

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Operational Risk

Key changes to Basel III

  • Introduces a new SA to replace the Advanced Measurement Approach (AMA) for calculating operational risk capital requirements
  • Calculates capital requirements using financial statement-based proxies and an Internal Loss Multiplier (scaling factor based on average historical losses)

Key considerations for Basel III Endgame

  • Amplification of operational Risk losses
  • Keeping up with operational loss data requirements
  • System enhancements to capture and log operational events

Key considerations implementing Operational Risk in Basel III Endgame

Amplification of operational risk losses

There is considerable uncertainty around implementation of the operational risk framework into the US rules.

Operational risk RWA under the SA may be greater than the current AMA due to Internal Loss multiplier; The impact of operational risk losses on capital may be amplified due to capital requirements driven by the SCB through CCAR operational risk losses.

Keeping up with operational loss data requirements

Banks should have robust processes for appropriately capturing operational risk loss data, including loss dates, accounting dates and recovery (legal and insurance) data.

High-quality operational loss data must extend back ten years.

System enhancements to capture and log operational events

Technology systems should be comprehensive and linked to the General Ledger to facilitate the capture of operational loss data, including the required operational loss data elements.

Banks need to have independent assurance that operational loss tracking systems, processes, and controls provide for high-quality data.

Overcoming Operational Risk implementation challenges

Data requirements

Common issues achieving operational risk requirements
  • Banks must continue to implement robust processes for appropriately capturing operational risk loss data, including loss dates, accounting dates and recovery (legal and insurance) data.
  • Banks may not have a full ten years of high-quality operational loss data.
Approach to addressing these issues
  • Refine suite of existing operational risk capital policies and procedures.
  • Develop data governance model for operational loss data.
  • Perform lookback reviews to review and cleanse historical operational loss data.
  • Request regulatory approval for using five years of operational loss data, if needed.

Technology and operational processes

Common issues achieving operational risk requirements
  • Many banks have developed homegrown systems for capturing operational loss data. These systems may need to be enhanced to capture all of the required operational loss data elements.
  • Banks need to continue to have independent assurance that operational loss tracking systems, processes and controls provide for high-quality data.
Approach to addressing these issues
  • Develop capabilities within existing operational loss systems to capture required data elements.
  • Include annual assessments of operational risk capital modeling within the scope of internal audit plans, model validation plans and third-party assessments.

Capital requirements

Common issues achieving operational risk requirements
  • Required capital under Basel III Endgame may increase due to potential amplification of operational losses between Basel III Endgame and CCAR/DFAST.
Approach to addressing these issues
  • Clearly articulate operational risk RWA calculation methodologies and assumptions for Basel III Endgame and CCAR/DFAST in Basel Pillar III disclosures, 10-Qs, 10-Ks and CCAR/DFAST annual stress tests.
  • Benchmark operational risk RWA against peer institutions to confirm efficacy of operational loss modeling.

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Regulators can pull many levers to keep Basel III Endgame capital neutral. These are the most impactful:

Levers

Description

Likelihood of incorporation

Real Estate Exposures

Maintain BCBS proposed risk weights for loan-to-value bands

Medium

Corporate Exposures

Align the definition of investment grade with current industry practices and internal processes for evaluating and measuring risk

High

Retail Exposures

Maintain BCBS proposed risk weights for retail and credit card balances

Medium

Capital Floors

Align Collins Amendment with proposed capital floors to effectively keep capital neutral

Low

CVA

Address potential double count of market risk losses between Standardized Approach (SA) and CCAR by further reducing the multiplier in the SA

Medium

Unused Commitments

Decrease the proposed Credit Conversion Factor (CCF) of 10% or maintain the current 0% CCF for unused unconditionally cancelable commitments

Low

Operational Risk

Address potential double count of operational risk RWA in the SA and stress losses in CCAR through the SCB

Medium

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