The Directors Education Series Interest Rate Risk Modeling and Monitoring Nicholas Hahn 0
Agenda and Overview Sources and measurement of interest rate risk ( IRR ) Current regulatory guidance governing IRR modeling and monitoring processes Regulatory expectations regarding IRR modeling and monitoring processes 1
Sources and measurement of IRR IRR is the risk to earnings and capital arising from movements in interest rates There are four types of IRR, described as follows: Repricing risk Caused by differences between the timing of interest rate changes and the timing of cash flows (i.e., maturities) Basis risk Caused by changing relationships among interest rate indices Yield curve risk Caused by changes in the slope of the yield curve Option risk Caused by embedded interest-related options in balance sheet products 2
Sources and measurement of IRR One primary measure of IRR is the change in the economic value of equity ( EVE ) under differing interest rate projections/scenarios Calculated as the present value of assets, less the present value of liabilities The IRR model s present value calculations generally include financial instruments: Balances Interest rates Maturities Repricing Optionality (i.e., puts, calls, prepayments, decay rates, etc.) EVE is a point-in-time measurement 3
Sources and measurement of IRR A second primary measure of IRR is the change in net interest income ( NII ) under differing interest rate projections/scenarios Calculated as projected interest income less projected interest expense The IRR model s income and expense calculations generally include financial instruments: Balances Interest rates Maturities Repricing Optionality (i.e., puts, calls, prepayments, caps, floors, decay rates, etc.) Betas and lags Net interest income and net interest expense should be projected over, at a minimum, the 12- and 24-month time horizons 4
Sources and measurement of IRR Interest rate scenarios At a minimum, IRR modeling processes should include evaluation of instantaneous rate shocks of up to 400 basis points (for both EVE and NII) Regulatory agencies encourage evaluation of additional interest rate scenarios, including: Interest rate projections, which reflect management s expectations of interest rates to be encountered throughout the period being modeled Interest rate ramps (i.e., gradual changes in interest rates throughout the period being modeled) Twists or changes in the slope of the yield curve 5
Current Regulatory Guidance Joint Agency Policy Statement on Interest Rate Risk (May 14, 1996) Interagency Advisory on Interest Rate Risk Management (January 6, 2010) Supervisory Guidance on Model Risk Management (April 4, 2011) Interagency Advisory on Interest Rate Risk Management Frequently Asked Questions (January 12, 2012) 6
Regulatory Expectations Regarding IRR Overall increase in examiners expectations regarding IRR modeling and monitoring processes Specific areas of focus include: Model capabilities Supportable financial institution-specific inputs and assumptions Risk limits and other policy items BOD reporting and review BOD training with respect to IRR Cross-training and succession planning for individuals involved in IRR modeling Independent model validations Stress testing 7
Model Capabilities Are you using the right model for your financial institution? Is the model able to appropriately address all of the optionality on your financial institution s balance sheet? Are there any work-arounds required as part of the current modeling process? Are you running the most current version of your chosen model? Is there a regular evaluation of the strengths/weaknesses of the model, as well as those of other modeling solutions? 8
Supportable Inputs and Assumptions Are model inputs and assumptions appropriately developed and monitored? Inputs and assumptions should be developed using financial institution-specific data and information All input and assumption fields within the model should be reviewed and updated (i.e., default inputs and assumptions should be modified as appropriate) An independent review of inputs and assumptions should take place on a periodic basis, including when significant inputs or assumptions change All changes to significant inputs or assumptions should be reported to the BOD 9
Risk Limits and Other Policy Items Risk limits should reflect the financial institution s tolerance for IRR Separate risk limits for changes in net interest income ( NII ) and the economic value of equity ( EVE ) should be clearly defined in the IRR policy The BOD should formally document their evaluation of model output reports in comparison to risk limits for each period modeled Risk limits are intended to function as an early warning system 10
Risk Limits and Other Policy Items Risk limits at set intervals (e.g., 10%-15%-20% or 10%-20%-30%) ignore the relative volatility of EVE and NII in more extreme interest rate scenarios Risk limits should be developed in the context of the financial institution s historical performance in increasing, decreasing and flat interest rate environments 11
Risk Limits and Other Policy Items Policy should be reviewed and approved at least annually Policy should should define the BOD s expectations for the modeling process, including model output reports Policy should define the responsibilities of the BOD and ALCO, as well as those delegated to management Policy should mirror applicable regulatory guidance Policy should be evaluated in conjunction with other related policies (e.g., asset/liability management policy, liquidity policy, investment policy, etc.) 12
BOD Reporting and Review BOD s responsibilities Establishing IRR policy, including risk tolerance limits Monitoring IRR (based on policy) to prevent excessive exposure Provide adequate resources for management to accomplish their goals Management s responsibilities Implementing procedures that translate the BOD s policies into operating strategies Maintaining an IRR measurement and monitoring system Establishing effective controls over the foregoing 13
BOD Reporting and Review IRR reporting should contain sufficient detail to permit the ALCO and BOD to: Identify the level of IRR present as of the measurement date Evaluate significant inputs and assumptions, including changes, if any Verify compliance with enacted policies and applicable risk limits 14
BOD Training with Respect to IRR The BOD is ultimately responsible for the monitoring and oversight of IRR Regulatory expectation is that BOD members understand the fundamentals of IRR and the nuances of their individual IRR modeling process to enable them to provide appropriate monitoring and oversight Given technical nature of IRR, regulators expect to see documented BOD training with respect to the foregoing 15
Cross-Training and Succession Planning IRR model operators at many financial institutions have significant accumulated knowledge that is vital to the IRR modeling process In the past, IRR model operation has typically been the responsibility of one individual Regulatory expectation is that financial institutions cross-train additional individuals to carry out the IRR modeling process Some financial institutions are opting for detailed procedures manuals to accomplish this task 16
Independent Model Validations Individuals performing IRR model validation should be independent of the modeling and oversight process Third-party model vendors should be able to offer a certification of the accuracy of their model s mechanics, mathematics and program code Validation should focus on the following key areas: Model inputs and assumptions Model calculations Model outputs and reports 17
Independent Model Validations Model validation should address: Internal controls surrounding the IRR process (e.g., security and change controls) Adequacy of the IRR policy Design and implementation of the model Theoretical and computational basis for the model Support for model inputs and assumptions, including sensitivity analysis Model operation Predictive value of model output reports (i.e., back testing) BOD and ALCO reporting 18
Stress Testing In addition to the interest rate scenario analysis performed as part of the IRR modeling process, regulators expect that financial institutions will perform stress testing to ensure the reasonableness of significant model inputs and assumptions, including, but not limited to: Asset prepayments Non-maturity deposit sensitivity Decay rates Key interest rate drivers 19
Stress Testing Stress testing allows financial institutions to identify which inputs and assumptions have the most significant impact on model outputs/results Inputs and assumptions determined to be significant based on stress testing procedures should be relatively more closely monitored by the BOD 20
Questions? Nicholas Hahn, CPA Manager Financial Institutions 414.298.2866 nicholas.hahn@mcgladrey 21