What is Interest Rate Risk in the Banking Book (IRRBB)?

In 2016, the Basel Committee on Banking Supervision (BCBS) issued new standards on Interest Rate Risk in the Banking Book commonly referred to as IRRBB. Before these standards, the Basel Committee had issued guidance on interest rate risk management in their 2004 paper “Principles for the management and supervision of interest rate risk” The new standards are expected to replace this old guidance.

IRRBB Definition

The interest rate risk in banking book refers to the risk to a bank’s capital and earnings arising from adverse movements in interest rates that affect banking book positions. Any changes in interest rates have an impact on the present value of future cash flows on the bank. This impacts the underlying value of the bank’s assets, liabilities and off-balance sheet items. This results in a chance in its economic value. When interest rates change, it will impact the bank’s earnings as its net interest income (NII) will change that depends on interest-rate sensitive income and expenses.

The IRRBB arises in three forms:

  1. Gap risk: This arises from the changes in term structure of interest rates that impacts the banking book instruments.
  2. Basis risk: This describes the impact of relative changes in interest rates for financial instruments that have similar tenors but are priced using different interest rate indices.
  3. Option risk: This arises from option derivative positions or from optional elements embedded in a bank’s assets, liabilities and/or off-balance sheet items

IRRBB Measurement

As per the new IRRBB standards, banks are required to calculate their IRRBB exposures based on the impact on economic value of equity (EVE) under a set of prescribed interest rate shock scenarios, either using the standardised framework or internal models.

Banks that have IRRBB exposures exceeding 15% of their Tier 1 capital are identified as “outliers” and considered as potentially having undue IRRBB and subject to review. In addition, banks are required to disclose their IRRBB exposures to the public on a regular basis.

The Revised IRR Principles

The Basel Committee has provided the following principles for the measurement and management of interest rate risk.

  • Principle 1: IRRBB is an important risk for all banks that must be specifically identified, measured, monitored and controlled. In addition, banks should monitor and assess CSRBB (Credit Spread Risk in Banking Book).
  • Principle 2: The governing body of each bank is responsible for oversight of the IRRBB management framework, and the bank’s risk appetite for IRRBB. Monitoring and management of IRRBB may be delegated by the governing body to senior management, expert individuals or an asset and liability management committee. Banks must have an adequate IRRBB management framework, involving regular independent reviews and evaluations of the effectiveness of the system.
  • Principle 3: The banks’ risk appetite for IRRBB should be articulated in terms of the risk to both economic value and earnings. Banks must implement policy limits that target maintaining IRRBB exposures consistent with their risk appetite.
  • Principle 4: Measurement of IRRBB should be based on outcomes of both economic value and earnings-based measures, arising from a wide and appropriate range of interest rate shock and stress scenarios.
  • Principle 5: In measuring IRRBB, key behavioural and modelling assumptions should be fully understood, conceptually sound and documented. Such assumptions should be rigorously tested and aligned with the bank’s business strategies.
  • Principle 6: Measurement systems and models used for IRRBB should be based on accurate data, and subject to appropriate documentation, testing and controls to give assurance on the accuracy of calculations. Models used to measure IRRBB should be comprehensive and covered by governance processes for model risk management, including a validation function that is independent of the development process.
  • Principle 7: Measurement outcomes of IRRBB and hedging strategies should be reported to the governing body or its delegates on a regular basis, at relevant levels of aggregation (by consolidation level and currency).
  • Principle 8: Information on the level of IRRBB exposure and practices for measuring and controlling IRRBB must be disclosed to the public on a regular basis.
  • Principle 9: Capital adequacy for IRRBB must be specifically considered as part of the Internal Capital Adequacy Assessment Process (ICAAP) approved by the governing body, in line with the bank’s risk appetite on IRRBB.
  • Principle 10: Supervisors should, on a regular basis, collect sufficient information from banks to be able to monitor trends in banks’ IRRBB exposures, assess the soundness of banks’ IRRBB management and identify outlier banks that should be subject to review and/or should be expected to hold additional regulatory capital.
  • Principle 11: Supervisors should regularly assess banks’ IRRBB and the effectiveness of the approaches that banks use to identify, measure, monitor and control IRRBB. Supervisory authorities should employ specialist resources to assist with such assessments. Supervisors should cooperate and share information with relevant supervisors in other jurisdictions regarding the supervision of banks’ IRRBB exposures.
  • Principle 12: Supervisors must publish their criteria for identifying outlier banks. Banks identified as outliers must be considered as potentially having undue IRRBB. When a review of a bank’s IRRBB exposure reveals inadequate management or excessive risk relative to capital, earnings or general risk profile, supervisors must require mitigation actions and/or additional capital.

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Data Science in Finance: 9-Book Bundle

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Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
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  • Python for Data Science
  • Machine Learning in Finance using Python

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