THE STATE OF INTEREST RATE RISK MANAGEMENT

Financial Services THE STATE OF INTEREST RATE RISK MANAGEMENT FINDINGS FROM AN OLIVER WYMAN INDUSTRY SURVEY AUTHORS Ugur Koyluoglu, Partner Umit Kaya, Partner

INTRODUCTION As the recent financial crisis unfolded, the focus of risk management practitioners turned in large part to capital adequacy and liquidity management amid piling credit losses, capital adequacy concerns and funding problems. Comprehensive stress testing thus became the focal point, and in that context, credit dynamics and liquidity stress testing have been extensively analyzed. Meanwhile, in the context of markedly low interest rates and elevated regulatory scrutiny on interest rate risk (IRR) management 1, effective risk management in this arena has also required re-assessment and adaptation. Banks are challenged to generate earnings in the face of low interest rates and lack of credit growth and as a result of this environment, strategically reviewing interest rate risk metrics has now become a priority. Based on findings from a recent Oliver Wyman survey of North American banks, this paper discusses current industry practices and leading approaches to IRR management as well as strategic implications for broader balance sheet optimization. IRR MANAGEMENT CONTEXT AND SURVEY OVERVIEW The interest rate environment has been nothing but extraordinary during and after the crisis. Many countries are still at historically low levels of interest rates with a steep yield curve as a result of both monetary policy responses and investor behavior. In the face of many levels of uncertainty, such as credit growth, volatility in the financial markets, changes in the banking environment, and the continuation (and eventual reversal) of unorthodox monetary policies, IRR management presents significant challenges for financial institutions of all sizes. In particular, institutions currently face the challenge of generating higher net interest income (NII) while maintaining value-based IRR levels within acceptable limits. Banking regulators have also placed greater emphasis on IRR measurement and management, as evidenced by the comprehensive guidance document issued by US regulatory agencies in January 2010. Sheila Bair, then-chairwoman of the FDIC, also stated that, interest rates represent the next big risk for depository banks. Shortly thereafter, the Basel III capital and liquidity framework that was released in December 2010 also had substantial implications for management of the balance sheet and the ALM position. The framework has fundamentally impacted the maturity transformation role of banks through new liquidity rules and a change in the treatment of other comprehensive income (OCI) for capital adequacy purposes. Our survey of eighteen North American banks, with assets totaling approximately $8.5 TN, set out to examine how banks are responding to the uncertainty through their IRR management and measurement practices. The participants are a diverse group across many dimensions: universal vs. regional in market scope, asset-driven vs. liability-driven, US vs. Canadian, large vs. mid-size, single-currency vs. multi-currency balance sheets, and 1 IRR refers to the risk in the structural interest rate (i.e. ALM) position in this paper, but not to the interest rate risk in the trading book Copyright 2012 Oliver Wyman 2

retail branch based vs. wholesale. The diverse nature of participants enabled us to robustly identify trends and emerging best practices. Broadly, the survey confirmed our hypotheses from our client work that banks are responding to the low interest rate environment and regulatory pressures by extensively revisiting past practices in what we see as two major areas. First, we observe a secular shift towards a more balanced approach to managing IRR in terms of earnings and value risks, through a more prominent use of the value-based view. With this more balanced view, banks are enhancing their measurement practices, especially with respect to economic value of equity (EVE). Second, banks are rethinking their behavioral deposit models given the importance of deposit modeling in a low interest rate environment and possible structural shifts in depositor behavior. We see the related balance sheet optimization problem in the current environment as particularly challenging given the onerous capital and liquidity requirements being phased into the system, low asset growth, NIM pressure in a low rate environment, and many regulatory and compliance issues. Banks are responding with mostly tactical steps to increase earnings but we believe that an integrated approach to balance sheet risk-return optimization also needs to be a significant part of the solution. MOVING TOWARDS A MORE BALANCED IRR MANAGEMENT APPROACH Change in interest rates pose risks for banks in two fundamental ways. First, they affect value of future cash flows; second, they affect future interest income and expenses. Immunizing the bank from both risks is impossible, and there is a trade-off between the optimal management of these two risks. Historically, most US banks have emphasized earningsbased IRR management (i.e., tighter control on NII volatility) over value-based management (i.e., tighter control on EVE volatility). Our survey indicates that the historical pattern still continues to hold with 61%, 28%, and 11% of participants stating earnings, both earnings and value, and value focus, respectively (Exhibit 1). However, our follow-up discussions with participants indicated that many are considering value more prominently in their ALM strategy. Most institutions that consider earnings as their primary focus indicated that the weight they put on EVE is getting more significant. One institution that was purely managing IRR based on an earnings perspective is now overhauling the entire framework and moving toward a balanced approach. Copyright 2012 Oliver Wyman 3

This broader trend is due in part to regulatory emphasis on a balanced view, the susceptibility of the current interest rate environment to large movements, and also to the increasing importance of economic capital and stress testing, which heavily use value-based metrics. The trend is most pronounced in the way that banks articulate their risk appetites. Less than 20% of the banks that choose earnings as their primary focus indicated that their risk appetite statements only refer to NII volatility. Similarly, ~90% of all participants employ Board-level limits for both earnings- and value-based metrics (Exhibit 1). Exhibit 1: WHAT IS YOUR INSTITUTION S PRIMARY FOCUS IN MANAGING IRR? MANAGEMENT S PRIMARY FOCUS IN MANAGING INTEREST RATE RISK RISK APPETITE AND BOARDLIMIT STRUCTURE EARNINGS 61% IS PRIMARY FOCUS BOTH 28% ARE PRIMARY FOCUS VALUE 11% IS PRIMARY FOCUS PARTICIPANTS 89% HAVE BOTH EARNINGS & VALUE-BASED LIMITS NII LIMITS ONLY 6% (HAVE NO VALUE-BASED LIMITS) DURATION LIMITS ONLY 6% (HAVE NO EARNINGS- BASED LIMITS) ADVANCES IN MEASUREMENT AND METHODOLOGIES One of the biggest concerns around the value-based view of IRR compared to the earningsbased view has been the reliance of EVE analysis on many significant modeling assumptions, which has always questioned confidence in the results. Banks are increasingly pushing the envelope in refining those assumptions to mitigate this shortcoming. Through the survey and our follow-up discussions, we were able to distill the most pertinent methodology issues that practitioners face. MORE ADVANCED SCENARIO GENERATION TECHNIQUES: First and foremost, all of the participants in the survey have standalone economic capital calculations for IRR, and almost 90% of respondents define their EC metric as the change in EVE (Exhibit 2), indicating convergence in the industry across these dimensions. Economic capital and stress testing require tail scenarios to generate large hypothetical losses in EVE, and the historical simulation technique is emerging as the preferred approach for this purpose. Copyright 2012 Oliver Wyman 4

Exhibit 2: SCENARIO GENERATION TECHNIQUES USED FOR EVE % OF PARTICIPANTS 50 40 30 20 10 0 Historical simulation Probabilistic shock scenario analysis Monte Carlo simulation Heuristic shock scenario analysis Parametric VaR Source: Oliver Wyman Interest Rate Risk Management Survey (2011) More than one response possible MODELING OF MULTIPLE YIELD CURVES: About 55% of the participants have significant exposure to multiple currencies, and this has significance for IRR management as yield curves for different currencies move in tandem. Banks largely use separate yield curves to model exposure in foreign currencies, but only about half of them tailor scenarios to particular yield curves and/or incorporate the necessary correlations into their analysis. The aforementioned historical simulation approach is also conducive for analysis in a multiple yield curve environment, since the correlations are already embedded in historical data. MANAGEMENT INTERVENTION: Treasury units typically manage IRR in an active manner through market transactions. This intervention behavior tends to mitigate risks by bringing companies to within their risk tolerance/appetite; therefore modeling these interventions can provide a more accurate view of risk. We found that half of the banks in the survey take management intervention into consideration for extreme IRR measurement purposes. This practice can be as simple as applying a haircut to results or as complex as incorporating dynamic hedging rules into the mechanics of the EVE, economic capital and NII models. MORE REALISTIC BALANCE SHEET MODELING: Typically NII analysis uses a dynamic balance sheet with new business volume assumptions, while EVE analysis uses a static balance sheet view in run-off model. Many banks consider this difference to be one of the weaknesses of the value-based approach. We have found that some banks are now beginning to incorporate dynamic modeling assumptions into their framework which in turn heightens the importance of a rigorous approach to modeling management intervention. We view all of these advances as productive steps for responding to the low interest rate environment and elevated regulatory scrutiny as well as important drivers of better informed management decisions. Copyright 2012 Oliver Wyman 5

DEPOSIT CHARACTERIZATION: GUARDING AGAINST A FUNDAMENTAL SHIFT Banks are doing an extensive amount of work in deposit modeling, particularly on indeterminate maturity deposits. One of our survey questions gauged how comfortable the participants were with cash flow modeling across major balance sheet items. We found that banks are generally comfortable in this aspect, except for deposits for which about one-third of participants outright indicated that they were not comfortable. More strikingly, most institutions (including some that stated that they are generally comfortable with their deposit models) are concerned that their models may not behave well in the current environment. The primary reason for this is that the models have been calibrated based on historical customer behavior from typical economic cycles, and the current environment presents many structural differences and possible paradigm shifts raising concerns about the applicability of historical data. Banks with robust deposit modeling capabilities generally use some combination of segmentation, balance stability, rate re-pricing, balance sensitivity, and account attrition analyses. Oliver Wyman s deposit characterization framework (Exhibit 3) illustrates the typical approach, which merges the analytics and benchmarks with forward-looking amendments. The adjustments are important to accurately capture specific behavioral traits of particular products. However, in the current environment the amendments are critical for reasons including: Possible secular change in deposits attractiveness to consumers as an asset class, due to an increase in the savings rate and shifts in expected risk-return trade-off for alternative assets Historically low interest rates (both real and nominal) Combined impact on opportunity costs to depositors of holding deposits amid possibly large rate shocks vs. possibly higher volatility Changes to deposit insurance schemes (both temporary and permanent) Changes in banks administration of deposit pricing given the current banking and interest rate environment We believe that deposit modeling is likely to constitute the single most important input to making accurate ALM decisions in the current environment. From an NII point of view, deposit pricing is critical to earnings given pressure from historically low interest rates. From an EVE point of view, the modeled behavior of deposits is critical to determine the bank s overall ALM position. In one client situation, we have found that the earnings impact of mischaracterizing deposit behavior can be on the order of 2% of the mischaracterized deposits over 10 years for the same level of IRR. Copyright 2012 Oliver Wyman 6

Exhibit 3: OLIVER WYMAN DEPOSIT CHARACTERIZATION FRAMEWORK Historical data Balance volatility Benchmarking Segmentation Attrition and maturity Rate sensitivity and repricing APPLICATIONS Forward-looking adjustments Balance macro-sensitivity IMPLICATIONS FOR BALANCE SHEET OPTIMIZATION In addition to the complexity of target setting for managing the ALM position and IRR, there are myriad constraints now imposed on balance sheet optimization. For example, liquidity risk management represents a significant constraint, given that the new regulations will likely transform the funding and liquid assets of banks. In this regard, isolated approaches to ALM and liquidity risk management would result in a suboptimal outcome. Moreover, Basel III and CCAR style stress tests are introducing major new constraints. Banks are trying to fully comprehend the economics of the new normal resulting from the various constraints and find ways to generate earnings in an environment marked by low interest rates and lack of credit growth. In particular, many banks are: Incentivizing loan growth through incorporating subsidies into FTP frameworks Growing relatively riskier businesses such as small business banking, and expanding lending into niche segments such as equipment financing Increasing use of floors in loan pricing and aggressively keeping deposit rates low Revisiting the composition and duration of investment portfolios as well as the HTM vs. AFS accounting designation Optimizing funding costs through taking on long-term debt at low interest rates Increasing the amount and stability of non-interest income in earnings Hedging These arguably tactical types of initiatives need to be factored into the optimization framework. We thus believe that a more integrated treasury management approach is crucial to achieving business goals in the face of multiple other constraints and considerations. An integrated approach with clearly delineated objectives and recognition of constraints provides a robust platform to navigate the new environment. For example, a new framework of this kind should clearly link to the CCAR style stress testing capabilities that many institutions are rapidly building, as well as recognize the constraints imposed by liquidity risk management. Copyright 2012 Oliver Wyman 7

CONCLUSION Historically, managing IRR has been a critical success factor for US banks because of the complex reaction to interest rates that many instruments have, e.g., the large deposit base in the banking system and long term fixed-rate mortgages with embedded prepayment options. As a result, most banks invested considerably in analytics, systems and processes for several years leading up to the crisis. For those that did not sufficiently invest in the past, we recommend catching up as quickly as possible (among top North American banks, we believe this to be a very small group). For those banks that did already make these investments, we recommend rethinking and refining IRR management and ALM approaches, in light of the current environment, in order to make the best use of their existing infrastructure a set of recommended action items here include: Evaluate whether the pendulum has swung too far toward one side in IRR management, and investigate ways to consider both earnings and value views in making strategic decisions Revisit deposit characterization and consider the potential impact of various possible structural changes Ensure a robust pricing process that takes into account possible paths of the evolution of rates and response to the continuation/reversal of unorthodox monetary policies Reconsider the embedded simplifications around modeling of the portfolio and the cash flows Enhance methodologies around interest rate scenario generation, e.g., consider efficient use of the richness in historical data Most importantly, evaluate the implications for balance sheet management and build capabilities for an integrated approach to balance sheet risk-reward management with explicit linkages to the newly emerging stress testing framework Based on ongoing work with clients in these areas, we believe that the many challenges imposed by the current environment also ultimately present opportunities for a more integrated approach to treasury risk management; a catalyst for balance sheet riskreturn optimization. Copyright 2012 Oliver Wyman 8

Oliver Wyman is a global leader in management consulting that combines deep industry knowledge with specialized expertise in strategy, operations, risk management, organizational transformation, and leadership development. For more information please contact the marketing department by email at info-fs@oliverwyman.com or by phone at one of the following locations: AMERICAS +1 212 541 8100 EMEA +44 20 7333 8333 ASIA PACIFIC +65 6510 9700 ABOUT THE AUTHORS Ugur Koyluoglu is a Partner and Head of the Americas Corporate & Institutional Banking practice. Umit Kaya is a Partner in the Americas Finance & Risk practice. www.oliverwyman.com Copyright 2012 Oliver Wyman All rights reserved. This report may not be reproduced or redistributed, in whole or in part, without the written permission of Oliver Wyman and Oliver Wyman accepts no liability whatsoever for the actions of third parties in this respect. The information and opinions in this report were prepared by Oliver Wyman. This report is not investment advice and should not be relied on for such advice or as a substitute for consultation with professional accountants, tax, legal or financial advisors. Oliver Wyman has made every effort to use reliable, up-to-date and comprehensive information and analysis, but all information is provided without warranty of any kind, express or implied. Oliver Wyman disclaims any responsibility to update the information or conclusions in this report. Oliver Wyman accepts no liability for any loss arising from any action taken or refrained from as a result of information contained in this report or any reports or sources of information referred to herein, or for any consequential, special or similar damages even if advised of the possibility of such damages. The report is not an offer to buy or sell securities or a solicitation of an offer to buy or sell securities. This report may not be sold without the written consent of Oliver Wyman.