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AuditOne Advisory: IRR Limits & Assumptions Analysis

AuditOne Advisory

From Bud Genovese, Chairman

This Advisory presents data that we have compiled to help you in management of your institution’s Interest Rate Risk (IRR) process. AuditOne performs remote-based IRR audits each week at institutions in the Western US and around the nation. One of our IRR audit specialists, Kruskal Hewitt, has developed the following presentation of IRR data on exposure limits and modeling assumptions from a range of our financial institution clients. Mr. Hewitt has been a risk manager, portfolio manager and trader at international and regional banks. I hope you find this information useful, and please share with your colleagues having responsibilities related to IRR modeling and related controls. Thank you, — Bud

AUDITONE LLC’S ANALYSIS OF IRR LIMITS AND ASSUMPTIONS 2017 – 2019

AuditOne LLC is a leading provider of outsourced internal audits for community banks and other small/mid-sized financial institutions (FIs), predominantly in the western US.  Please refer to our website (www.auditonellc.com) for further information.  Asset/Liability Management (ALM) is among AuditOne’s practice areas, and within that we perform many audits of Interest Rate Risk (IRR) management every year. US FIs are expected to have an annual internal audit of their modeling, monitoring and control of IRR.  Key to IRR modelling are several forward-looking assumptions.

AuditOne has compiled (anonymously) data from 80 of our IRR clients on IRR limits and assumptions from our last three years’ audits; we have used data from the most recent AuditOne IRR audit, no further back than 2017.  AuditOne believes this database is relevant to AuditOne clients because it covers a relatively narrow range of asset size, geography and business lines.  AuditOne updates this analysis annually.

DEFINITIONS

NII:  Net interest income.  FIs are expected to model and project (over at least a one- and two-year horizon) interest-sensitive revenues and expenses under different interest rate scenarios.

EVE:  Economic value of equity.  This is a theoretic valuation of the institution whereby cash flows from all assets and liabilities are discounted to their net present value (NPV), then summed.  EVE captures long term risk in the balance sheet.  Conceptually, EVE cam be thought of as the sum of the NPV of all future NII streams.

Instant vs. Ramped Interest Rate Shocks (for NII):  The averages showing in the tables below are for instant (or immediate) rate shocks (78 clients) which assumes rates change instantly, as opposed to a gradual and even rate rise (ramp) over 12 months.

Beta:  This represents the assumed percentage of a market rate change that is reflected in administered rates – most importantly, deposit rates.  For example, if the driver rate is Fed Funds and the beta for saving accounts is 45%, then for every 100-basis point rise in the Fed Funds rate, savings account rates are assumed (predicted) to rise 45 basis points.  Relatively few of our clients have different betas for down versus up rate movements.  Nineteen FIs assume a time lag in administered rate changes; most of these lags are 15 days and only three exceed 30 days.

Average Life:  Non-maturity deposits (NMDs) have no contractual maturity and therefore form a more stable, longer-term funding source.  In order to get a meaningful estimate of EVE, NMDs must be assigned an assumed (predicted) average life by account type.

Parallel vs. Non-Parallel Rate Shocks:  The standard rate shock set-up assumes the yield curve shifts in parallel fashion over the entire maturity spectrum.  However, many institutions also run simulations based on flatteners, steepeners and other non-parallel shocks.  These can be helpful for assessing specific balance sheet vulnerabilities.  But we advise against basing IRR limits on non-parallel shocks because shock specifications are very difficult to define for assessing limit compliance.

Static vs. Dynamic Balance Sheet:  For NII simulations, the balance sheet can either be static (constant), with like replacement of run-off assets and liabilities, or it can incorporate change, both growth and shrinkage (e.g., based on budgeted balances).  The 2010 Interagency Guidance specified that a static balance sheet be used, though simulations could also be run off a dynamic balance sheet as well.  

2017 – 2019 DATABASE ANALYSIS

There are no significant changes from the 2016 – 18 report to this 2017 – 19 report.  It presents results across the entire database of 80 IRR audit clients.  We would be happy to recalculate any of the results for subsets of institutions based on asset size, primary regulator, and/or model vendor; please contact our CEO Jeremy Taylor at 562-802-3581. 

See the final section below for the key identifiers.  Note, too, that we have presented only average (mean) figures in the tables below.  We also computed medians, but these were very close to the corresponding averages and have therefore not been presented separately here.

NII-at-risk (one-year) simulation limits

NII Shocks (bps)-200-100+100+200+300+400
Average Limit-14.3%-8.6%-8.4%-14.2%-20.3%-25.8%

EVE-at-risk simulation limits

EVE Shocks (bps)-200-100+100+200+300+400
Average Limit-18.3%-11.0%-11.4%-19.0%-26.6%-33.2%

Beta assumptions

Account TypeNOWSavingsMMACD
Average Beta (%)26.9%31.3%46.4%79.2%

Average life (AL) assumptions

Account TypeNOWSavingsMMADDA
Average AL (Months)52596662

Interest rate shocks (for NII limits) – number of FIs

InstantRamp
782

Note:  If asset and liability repricing is evenly spaced during the year (i.e., a ramped shock), then it has roughly half the impact on NII as an instantaneous shock at beginning of the year.  This means that institutions running ramped shocks would be expected to have NII risk limits at roughly half the limits for instantaneous shocks. 

DATABASE MIX SUMMARY

Database mix by asset size (all dollar figures in millions)

CountMaxMedianMin
80$11,400$322$24

Database mix by primary regulator (all dollar figures in millions)

80MAXMedianMin 
57$11,400$327$71FDIC
13$1,069$264$24OCC
7$834$322$194FRB
2nananaNCUA
1nananaFISCU

Database mix by primary regulator (all dollar figures in millions)

80MAXMedianMin 
14$723$308$68ALX Consulting
4$270$234$128Baker Group IRR Monitor
8$11,400$691$264Darling Consulting BASIS
4$834$251$172FIMAC Risk Analytics
9$2,133$321$174Fiserv Sendero
4$858$59$24Plansmith Bankers GPS
7$1,266$434$71Plansmith Compass
9$1,316$241$113Jack Henry Associates ProfitStar
12$4,786$426$140ZMDesk / ZMOnline
9$5,960$449$112Other Systems (8)

AuditOne LLC – Company Overview

AuditOne LLC is a leading provider of risk management services to financial institutions in the Western US and nationally.  Our sole focus enables us to deliver effective and efficient internal audit and credit review services.  This exclusive focus translates into exceptional benefits to our financial institution clients.  We have experience with all regulatory authorities and offer a full selection of audit services comprising BSA/ Anti-Money Laundering Program, Automated AML System Validation, Asset/Liability Management (ALM) and IRR Audits, a broad range of Compliance Reviews, IT/Information Security/Cybersecurity, Network Penetration Tests, Credit Review/ALLL, ACH Rules Compliance, Operations, Trust/Wealth Management, SOX/FDICIA Testing, and many specialty areas within each of these.

Our deep expertise is your edge.  For more information on this article, or to receive a proposal for Asset/Liability Management (ALM) or IRR Audits, please contact David Kellerman, ALM Practice Director, AuditOne LLC, at: Contact Us

For information on how our services can help reduce risk at your institution, contact Jeremy Taylor, CEO, at: Contact Us.  Also, for more information about AuditOne LLC and all our audit services see www.AuditOneLLC.com.