Section 7.1 Sensitivity to Market Risk

SENSITIVITY TO MARKET RISK Section 7.1

INTRODUCTION.............................................................. 2

TYPES AND SOURCES OF INTEREST RATE RISK .... 2

Types of Interest Rate Risk ............................................ 2

Sources of Interest Rate Risk ......................................... 2

RISK MANAGEMENT FRAMEWORK .......................... 3

Board Oversight ............................................................. 4

Senior Management Oversight ....................................... 4

Policies and Procedures .................................................. 4

Interest Rate Risk Strategies .......................................... 4

Risk Limits and Controls ................................................ 5

Risk Monitoring and Reporting ...................................... 5

INTEREST RATE RISK ANALYSIS ............................... 5

INTEREST RATE RISK MEASUREMENT METHODS 6

Gap Analysis .................................................................. 6

Duration Analysis ........................................................... 7

Earnings Simulation Analysis ........................................ 8

Economic Value of Equity ............................................. 8

STRESS TESTING ............................................................ 9

INTEREST RATE RISK MEASUREMENT SYSTEMS10

Measurement System Capabilities ............................... 10

System Documentation ................................................ 11

Adequacy of Measurement System Inputs ................... 11

Account Aggregation ................................................... 11

Assumptions ................................................................. 12

Sensitivity Testing - Key Assumptions ........................ 12

Measurement System Reports ...................................... 14

Measurement System Results ....................................... 14

Variance Analysis ........................................................ 14

Assumption Variance Analysis .................................... 15

OTHER RISK FACTORS TO CONSIDER .................... 16

Interest Rate Risk Mitigation ....................................... 16

INTERNAL CONTROLS ................................................ 17

Independent Reviews ................................................... 18

Independent Review Standards .................................... 18

Scope of Independent Review ...................................... 18

Theoretical and Mathematical Validations ................... 19

EVALUATING SENSITIVITY TO MARKET RISK .... 20

Examination Standards and Goals ................................ 20

Interagency Policy Statement on Interest Rate Risk .... 20

Interagency Advisory-Interest Rate Risk Management 21

EXAMINATION PROCESS ........................................... 21

Citing Examination Deficiencies .................................. 21

MARKET RISK GLOSSARY ......................................... 22

Deterministic Rate Scenarios ....................................... 22

Non-parallel Yield Curve Shifts ................................... 22

Static Models ................................................................ 22

Dynamic Models .......................................................... 22

Stochastic Models ........................................................ 22

Monte Carlo Simulation ............................................... 22

Spread Types ................................................................ 23

Duration Calculations ................................................... 23

Convexity ..................................................................... 24

Effective Duration and Effective Convexity ................ 24

RMS Manual of Examination Policies 7.1-1 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

INTRODUCTION

Sensitivity to market risk reflects the degree to which

changes in interest rates, foreign exchange rates,

commodity prices, or equity prices can adversely affect a

financial institution’s earnings or capital. For most

community banks, market risk primarily reflects exposure

to changing interest rates. Therefore, this section focuses

on assessing interest rate risk (IRR). However, examiners

may apply these same guidelines when evaluating foreign

exchange, commodity, or equity price risks. A brief

discussion of other types of market risks is included at the

end of this section.

Market risks may include more than one type of risk and

can quickly impact a financial institution’s earnings and

the economic value of its assets, liabilities, and off-balance

sheet items. In order to effectively manage IRR, each

institution should have an IRR management program that

is commensurate with its size and the nature, scope, and

risk of its activities.

The adequacy of a bank’s IRR program is dependent on its

ability to identify, measure, monitor, and control all

material interest rate exposures. To do this accurately and

effectively, institutions need:

• Appropriate IRR policies, procedures, and controls;

• Sufficiently detailed reporting processes to inform

senior management and the board of IRR exposures;

• Comprehensive systems and standards for measuring

and monitoring IRR; and

• Appropriate internal controls and independent review

procedures.

←

TYPES AND SOURCES OF INTEREST

RATE RISK

IRR can arise from a variety of sources and financial

transactions and has many components including repricing

risk, basis risk, yield curve risk, option risk, and price risk.

Types of Interest Rate Risk

Repricing risk reflects the possibility that assets and

liabilities will reprice at different times or amounts and

negatively affect an institution’s earnings, capital, or

general financial condition. For example, management

may use non-maturity deposits to fund long-term, fixed-

rate securities. If deposit rates increase, the higher funding

costs would likely reduce net yields on fixed-rate

securities.

Basis risk is the risk that different market indices will not

move in perfect or predictable correlation. For example,

LIBOR-based deposit rates may change by 50 basis points

while prime-based loan rates may only change by 25 basis

points during the same period.

Yield curve risk reflects exposure to unanticipated

changes in the shape or slope of the yield curve. It occurs

when assets and funding sources are linked to similar

indices with different maturities. For example, a 30-year

Treasury bond’s yield may change by 200 basis points, but

a 3-year Treasury note’s yield may change by only 50-

basis points during the same time period. This risk is

commonly expressed in terms of movements of the yield

curve for a type of security (e.g., a flattening, steepening,

or inversion of the yield curve).

Option risk is the risk that a financial instrument’s cash

flows (timing or amount) can change at the exercise of the

option holder, who may be motivated to do so by changes

in market interest rates. Lenders are typically option

sellers, and borrowers are typically option buyers (as they

are often provided a right to prepay). The exercise of

options can adversely affect an institution’s earnings by

reducing asset yields or increasing funding costs.

For example, assume that a bank purchased a 30-year

callable bond at a market yield of 10 percent. If market

rates subsequently decline to 8 percent, the bond’s issuer

will be motivated to call the bond and issue new debt at the

lower market rate. At the call date, the issuer effectively

repurchases the bond from the bank. As a result, the bank

will not receive the originally expected yield (10 percent

for 30 years). Instead, the bank must re-invest the

principal at the new, lower market rate.

Price risk is the risk that the fair value of financial

instruments will change when interest rates change. For

example, trading portfolios, held-for-sale loan portfolios,

and mortgage servicing assets contain price risk. When

interest rates decrease, the value of an institution’s

mortgage servicing rights generally decrease because the

total cash flows from servicing fees decline as consumers

refinance. Because servicing assets are subsequently

measured at fair value, or carried at amortized cost and

tested for impairment, the fair value adjustment or any

impairment is reflected in current earnings.

Sources of Interest Rate Risk

Funding sources may involve repricing risk, basis risk,

yield curve risk, or option risk, and examiners should

carefully evaluate all significant relationships between

funding sources and asset structures. Potentially volatile

or market-based funding sources may increase IRR,

especially when matched to a longer-term asset portfolio.

Sensitivity to Market Risk (7/18) 7.1-2 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

For example, long-term fixed-rate loans funded by

purchased federal funds may involve repricing risk, basis

risk, or yield curve risk. As a result, interest rate

movements could cause funding costs to increase

substantially while asset yields remain fixed.

Derivative instruments may be used for hedging but can

introduce complex IRR exposures. Depending on the

specific instrument, derivatives may create repricing, basis,

yield curve, option, or price risk.

Mortgage banking operations may create price risk

within the loan pipeline, held-for-sale portfolio, and

mortgage servicing rights portfolio. Interest rate changes

affect not only current values, but also future business

volumes and related fee income.

Fee income businesses may be influenced by IRR,

particularly mortgage banking, trust, credit card servicing,

and non-deposit product sales. Changing interest rates

could affect such activities.

Product pricing strategies may introduce IRR,

particularly basis risk or yield curve risk. Basis risk exists

if funding sources and assets are linked to different market

indices. Yield curve risk exists if funding sources and

assets are linked to similar indices with different

maturities.

Embedded options associated with assets, liabilities, and

off-balance sheet derivatives can create IRR. Embedded

options are features that provide the holder with the right,

but not the obligation, to buy, sell, pay down, payoff,

withdraw, or otherwise alter the cash flow of the

instrument. The holder of the option can be the bank, the

issuer, or a counterparty. Many instruments contain

embedded options that can alter cash flows and impact the

IRR profile of the institution, including:

• Non-maturity deposits: Depositors have the option to

withdraw funds at any time.

• Callable bonds: The issuer has the option to redeem

all or part of a bond before maturity (based on

contractual call dates).

• Structured notes: Options can vary by the type of

instrument and may include step-up features, interest

rate caps and floors, and cash flow waterfall triggers.

• Wholesale borrowings: Lenders may have a call

option (requiring banks to repay borrowings), or

borrowing banks may have a put option (allowing

them to prepay borrowings).

• Derivatives: Derivative owners may hold an option to

purchase additional securities or to exercise an

existing derivative contract.

• Mortgage loans: Borrowers may have the option to

partially or fully prepay the loan.

• Mortgage-backed securities (MBS): Borrowers’

options to prepay individual mortgage loans included

in an MBS loan pool can shorten the life of a tranche

of loans within a security.

Embedded options can create various risks, such as

contraction risk, extension risk, and negative convexity.

Contraction risk increases when rates decline and

borrowers can refinance at a lower rate, forcing the bank to

reinvest those funds at a lower rate. Extension risk

increases when rates rise and borrowers become less likely

to prepay loans, thereby locking banks into below-market

returns. Convexity measures the curvature in the

relationship between certain investment prices and yields

and reflects how the duration of an instrument changes as

rates change.

←

RISK MANAGEMENT FRAMEWORK

The IRR management framework sets forth strategies and

risk tolerances as established in the institution’s policies

and procedures that guide the identification, measurement,

management, and control of sensitivity to market risk. The

framework begins with sound corporate governance and

covers strategies, policies, risk controls, measurements,

reporting responsibilities, independent review functions,

and risk mitigation processes.

The formality and sophistication of the IRR management

program should correspond with an institution’s balance

sheet complexity and risk profile. Less complex programs

may be adequate for institutions that maintain basic

balance sheet structures, have moderate exposure to

embedded options, and do not employ complicated

funding or investment strategies. However, all institutions

should clearly document their procedures, and senior

management should actively supervise daily operations.

More complex institutions need more formal, detailed IRR

management programs. In such cases, management should

establish specific controls and produce sound analyses that

address all major risk exposures. Internal controls at

complex institutions should include a more thorough

independent review and validation process for the IRR

models employed, as well as more rigorous requirements

for separation of duties.

At all institutions, management and the board should

understand the IRR implications of their business

activities, products, and strategies, while also considering

their potential impact on market, liquidity, credit, and

operational risks.

RMS Manual of Examination Policies 7.1-3 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

Board Oversight

Effective board oversight is the cornerstone of sound risk

management. The board of directors is responsible for

overseeing the establishment, approval, implementation,

and annual review of IRR management strategies, policies,

procedures, and risk limits. The board should understand

and regularly review reports that detail the level and trend

of the institution’s IRR exposure.

The board or an appropriate board committee should

review sensitivity to market risk information at least

quarterly. The information should be timely and of

sufficient detail to allow the board to assess senior

management’s performance in monitoring and controlling

market risks and to assess management’s compliance with

board-approved policies.

In order to fulfill its responsibilities in this area, the board

is expected to:

• Establish formal risk management policies, strategies,

and risk tolerance levels;

• Define management authorities and responsibilities;

• Communicate its risk management strategies and risk

tolerance levels to all responsible parties;

• Monitor management’s compliance with board-

approved policies;

• Understand the bank’s risk exposures and how those

risks affect enterprise-wide operations and strategic

plans; and

• Provide management with sufficient resources to

measure, monitor, and control IRR.

Senior Management Oversight

Senior management is responsible for ensuring that board-

approved IRR strategies, policies, and procedures are

appropriately executed. Management should ensure that

risk management processes consider the impact that

various risks, including credit, liquidity, and operational

risks could have on IRR.

Management is responsible for maintaining:

• Appropriate policies, procedures, and internal controls

that address IRR management, including limits and

controls that ensure risks stay within board-approved

tolerances;

• Comprehensive systems and standards for measuring

IRR, valuing positions, and assessing performance;

• Adequate procedures for updating IRR measurement

scenarios and documenting key assumptions that drive

IRR analysis; and

• Sufficient reporting processes for informing senior

management and the board of the level of IRR

exposure.

IRR reports should provide sufficient aggregate

information and supporting details to enable senior

management and the board to assess the impact of market

rate changes and the impact of key assumptions in the IRR

model.

The Asset/Liability Committee (ALCO) or a similar senior

management committee should actively monitor the IRR

profile. The committee should have sufficient

representation across major functions (e.g., lending,

investment, and funding activities) that they can directly or

indirectly influence the institution’s IRR exposure.

Policies and Procedures

Policies and procedures should be comprehensive and

govern all material aspects of an institution’s IRR

management process. IRR policies and procedures should:

• Address board and senior management oversight;

• Outline strategies, risk limits, and controls;

• Define general methods used to identify risk;

• Describe the type and frequency of monitoring and

reporting;

• Provide for independent reviews and internal controls;

• Ensure that significant new strategies, products, and

businesses are integrated into the IRR management

process;

• Incorporate the assessment of IRR into institution-

wide risk management procedures so that interrelated

risks are identified and addressed; and

• Provide controls over permissible risk mitigation

activities, such as hedging strategies and instruments,

if applicable.

Interest Rate Risk Strategies

Management should develop IRR strategies that reflect

board-approved risk tolerances and do not expose the bank

to excessive risk. An institution’s risk profile is a function

of the bank’s activities and products. For example, an

institution’s IRR strategy may be to maintain a short-term,

non-complex balance sheet. In order to implement that

strategy, management may hold loans and securities with

short durations and minimal embedded options and fund

the assets with nonmaturity deposits and short-term

borrowings.

Some institutions may conduct borrowing and investment

transactions (leverage strategies) that are separate from the

bank’s core operations. In a typical leverage strategy,

management acquires short- or intermediate-term

Sensitivity to Market Risk (7/18) 7.1-4 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

wholesale funds or borrowings and invests those funds in

longer-term bonds. Prior to implementing a leverage

strategy, management should have the skills to understand,

measure, and manage the risks. Management should be

able to demonstrate a transaction’s effect on the bank’s

risk profile and document that the exposure is within

established risk limits.

Management should measure and document a strategy’s

effect on IRR exposure prior to implementation,

periodically thereafter, and prior to any significant strategy

changes. Institutions should consider stress testing all

prospective strategies and ensure IRR exposures are within

established risk limits.

Risk Limits and Controls

Risk limits should reflect the board’s tolerance of IRR

exposure by restricting the volatility of earnings and

capital for given rate movements and applicable time

horizons. Risk limits should be explicit dollar or

percentage parameters. IRR exposure limits should be

commensurate with the complexity of bank activities,

balance sheet structure, and off-balance sheet items. At a

minimum, limits should be expressed over one and two

year time horizons, correspond to the internal

measurement system’s methodology, and appropriately

address all key IRR risks and their effect on earnings and

capital.

Examiners should carefully evaluate policy guidelines and

board-approved risk limits. Institutions should establish

limits that are neither so high that they are never breached,

nor so low that exceeding the limits is considered routine

and unworthy of action. Effective limits will provide

management sufficient flexibility to respond to changing

economic conditions, yet be stringent enough to prevent

excessive risk-taking.

Policies should be in place to ensure excessive IRR

exposures receive prompt attention. Controls should be

designed to help management identify, evaluate, report,

and address excessive IRR exposures. Policies should

require management to regularly monitor risk levels, and

controls should be altered as needed when economic

conditions change or the board alters its risk tolerance

level. Reports or stress tests that reflect significant IRR

exposure should be promptly reported to the board (or

appropriate board committee), and the board should review

all risk limit exceptions and management’s proposed

actions.

Earnings-based risk limits may include volatility

considerations involving:

• Net interest margin,

• Net interest income,

• Net operating income, and

• Net income.

Capital-based risk limits may include volatility

considerations involving:

• Economic value of equity, and

• Other comprehensive income.

The board should provide staffing resources sufficient to

ensure:

• Effective operation of measurement systems,

• Appropriate analytic expertise,

• Adequate training and staff development, and

• Regular independent reviews.

Risk Monitoring and Reporting

Management should report IRR in an accurate, timely, and

informative manner. At least quarterly, senior

management and the board should review IRR reports.

Institutions that engage in complex or higher risk activities

should assess IRR more frequently. At a minimum, IRR

exposure reports should contain sufficient detail to permit

management and the board to:

• Identify the source and level of IRR;

• Evaluate key assumptions, such as interest rate

forecasts, deposit behaviors, and loan prepayments;

and

• Determine compliance with policies and risk limits.

←

INTEREST RATE RISK ANALYSIS

An effective risk management system must clearly

quantify and timely report risks. Institutions should have

sound IRR measurement procedures and systems that

assess exposures relative to established risk tolerances.

Such systems should be commensurate with the

complexity of the institution. Although management may

rely on third-party IRR models, they should fully

understand the underlying analytics, assumptions, and

methodologies of the models and ensure such systems and

processes are incorporated appropriately in the strategic

(long-term) and tactical (short-term) management of IRR

exposures.

Management should conduct careful due diligence/pre-

acquisition reviews to ensure they understand the IRR

characteristics of new products, strategies, and initiatives.

Management should also consider whether existing

measurement systems can adequately capture new IRR

RMS Manual of Examination Policies 7.1-5 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

exposures. When analyzing whether or not a product or

activity introduces new IRR exposures, management

should consider that changes to an instrument’s maturity,

repricing, or repayment terms can materially affect a

product’s IRR characteristics. Institutions may be able to

run alternative scenarios in their IRR models to test the

effects of new products and initiatives. If an institution is

unable to run alternative scenarios using existing models,

they should use other methods to estimate the risk of new

products, strategies, and initiatives. All institutions should

ensure that the method(s) they use to evaluate new

products and initiatives (running alternative scenarios in

existing models or through other means), adequately

captures potential market risks.

Management should consider earnings and the economic

value of capital when evaluating IRR. Reduced earnings

or losses can harm capital, liquidity, and the institution’s

reputation. Risk-to-earnings measurements are normally

derived from simulation models that estimate potential

earnings variability. Economic value of equity (EVE)

measurements allow for longer-term earnings and capital

analysis. The analysis may be useful for long-term

planning and may also indicate a need for short-term

actions to mitigate IRR exposure. Long term earnings-at-

risk simulations (5 to 7 years) can be a helpful supplement

to EVE measures, but they are not a replacement for EVE

measurements.

←

INTEREST RATE RISK MEASUREMENT

METHODS

Institutions are encouraged to use a variety of

measurement methods to assess their IRR profile.

Regardless of the methods used, a bank’s IRR

measurement system should be sufficient to capture all

material balance sheet items and to quantify exposures to

both earnings and capital. The most common types of IRR

measurement systems are:

• Gap Analysis,

• Duration Analysis,

• Earnings Simulation Analysis,

• Earnings-at-Risk,

• Capital-at-Risk, and

• Economic Value of Equity.

Gap Analysis

Gap analysis is a simple IRR methodology that provides an

easy way to identify repricing gaps. It can also be used to

estimate how changes in rates will affect future income.

However, gap analysis has several weaknesses and is

generally not sufficient as a financial institution’s sole IRR

measurement method. Gap analysis can be a first step in

identifying IRR exposures and may serve as a

reasonableness check for more sophisticated forms of IRR

measurement, particularly in less complex institutions with

simple balance sheets.

Gap analysis helps identify maturity and repricing

mismatches between assets, liabilities, and off-balance

sheet instruments. Gap schedules segregate rate-sensitive

assets (RSA), rate-sensitive liabilities (RSL), and off-

balance sheet instruments according to their repricing

characteristics. Then, the analysis summarizes the

repricing mismatches for defined time horizons.

Additional calculations can then estimate the effect the

repricing mismatches may have on net interest income.

A basic gap ratio is calculated as:

RSA

minus

RSL

Average Earning Assets

Gap analysis may identify periodic, cumulative, or average

mismatches, or it may show the ratio of RSA-RSL divided

by average assets or total assets. However, using those

denominators does not produce a standard gap ratio. They

simply provide other ways of describing the degree of

repricing mismatches.

A bank has a positive gap if the amount of RSAs repricing

in a given period exceeds the amount of RSLs repricing

during the same period. When a bank has a positive gap, it

is said to be asset sensitive. Should market interest rates

decrease, a positive gap indicates that net interest income

would likely also decrease. If rates increase, a positive gap

indicates that net interest income may also increase.

Conversely, a bank has a negative gap when the amount of

RSLs exceeds the amount of RSAs repricing during the

same period. When a bank has a negative gap, it is said to

be liability sensitive, and a decrease in market rates would

likely cause an increase in net interest income. Should

interest rates increase, a negative gap indicates net interest

income may decrease. While the terms asset and liability

sensitive are generally used to describe gap results, they

can also be used to describe the results of other models, or

even the general IRR exposure of a bank.

The gap ratio can be used to calculate the potential impact

on interest income for a given rate change. This is done by

multiplying the gap ratio by the assumed rate change. The

result estimates the change to the net interest margin.

For example, assume a bank has a 15 percent one-year

average gap. If rates decline 2 percent, then the projected

impact is a 30 basis point decline in the net interest margin

(15 percent x 2 percent). This estimate assumes a static

Sensitivity to Market Risk (7/18) 7.1-6 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

balance sheet and an immediate, sustained interest rate

shift.

Gap analysis has several advantages. Specifically, it:

• Identifies repricing mismatches,

• Does not require sophisticated technology,

• Is relatively simple to develop and use, and

• Can provide clear, easily interpreted results.

However, the weaknesses of gap analysis often

overshadow its strengths, particularly for a majority of

financial institutions. For example, gap analysis:

• Generally captures only repricing risk,

• Assumes parallel rate movements in assets and

liabilities,

• Generally does not adequately capture embedded

options or complex instruments,

• May not identify material intra-period repricing risks,

and

• Does not measure changes in the economic value of

capital.

Some gap systems attempt to capture basis, yield curve,

and option risk. Multiple schedules (dynamic or scenario

gap analysis) can show effects from non-parallel yield

curve shifts. Additionally, sensitivity factors may be

applied to account categories. These factors assume that

coupon rates will change by a certain percentage for a

given change in a market index. The market index is

designated as the driver rate (sophisticated systems may

use multiple driver rates). These sensitivity percentages,

also called beta factors, may dramatically change the

results.

Institutions can also use sensitivity factors in their gap

analysis to refine non-maturity deposit assumptions. For

example, management may determine that the cost of

funds for money market deposit accounts (MMDA) will

increase by 75 basis points whenever the six-month

Treasury bill rate increases by one percent. Thus,

management might consider only 75 percent of MMDA

balances as rate sensitive for gap analysis. Management

may expand its analysis by preparing gap schedules that

assume different market rate movements and changing

customer behaviors.

As noted above, gap analysis is generally not suitable as

the sole measurement of IRR for the large majority of

institutions. Only institutions with very simple balance

sheet structures, limited assets and liabilities with

embedded options, and limited derivative instruments and

off-balance sheet items should consider relying solely on

gap analysis for IRR measurements.

Duration Analysis

Duration analysis measures the change in the economic

value of a financial instrument or position that may occur

given a small change in interest rates. It considers the

timing and size of cash flows that occur before the

instrument’s contractual maturity. Additional information

on different types of duration analysis is included below

and in the glossary.

Macaulay duration calculates the weighted average term

to maturity of a security’s cash flows. Duration, stated in

months or years, always:

• Equals maturity for zero-coupon instruments,

• Equals less than maturity for instruments with

payments prior to maturity,

• Declines as time elapses,

• Is lower for amortizing instruments, and

• Is lower for instruments with higher coupons.

Modified duration, calculated from Macaulay duration,

estimates price sensitivity for small interest rate changes.

An instrument’s modified duration represents its

percentage price change given a small change in interest

rates.

Modified duration assumes that interest rate shifts will not

change an instrument’s cash flows. As a result, it does not

estimate price sensitivity with an acceptable level of

precision for instruments with embedded options (e.g.,

callable bonds or mortgages). Institutions with significant

option risk should not rely solely upon modified duration

to measure IRR.

Effective duration estimates price sensitivity more

accurately than modified duration for instruments with

embedded options and is calculated using valuation models

that contain option pricing components. First, the user

must determine the instrument’s current value. Next, the

valuation model assumes an interest rate change (usually

100 basis points) and estimates the instrument’s new value

based on that assumption. The percentage change between

the current and forecasted values represents the

instrument’s effective duration.

All duration measures assume a linear price/yield

relationship. However, that relationship actually is

curvilinear, which means that large shifts in rates have a

greater effect than smaller changes. Therefore, duration

may only accurately estimate price sensitivity for rather

small (up to 100 basis point) interest rate changes.

Convexity-adjusted duration should be used to more

RMS Manual of Examination Policies 7.1-7 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

accurately estimate price sensitivity for larger interest rate

changes (over 100 basis points).

Duration analysis contains significant weaknesses.

Accurate duration calculations require significant analysis

and complex management information systems. Further,

duration only measures value changes accurately for

relatively small interest rate fluctuations. Therefore,

institutions must frequently update duration measures

when interest rates are volatile or when any significant

change occurs in economic conditions, market conditions,

or underlying assumptions.

Earnings Simulation Analysis

Earnings simulation models (such as pro-forma income

statements and balance sheets) estimate the effect of

interest rate changes on net interest income, net income,

and capital for a range of scenarios and exposures.

Historically, comprehensive simulation models (both long-

and short-term) were primarily used by larger, more

complex institutions. Current technology allows less

complex institutions to perform cost effective,

comprehensive simulations of the potential impact of

changes in market rates on earnings and capital.

A simulation model’s accuracy depends on the use of

accurate assumptions and data. Like any model,

inaccurate data or unreasonable assumptions lead to

inaccurate or unreasonable results.

A key aspect of IRR simulation modeling involves

selecting an appropriate time horizon(s) for assessing IRR

exposures. Simulations can be performed over any period

and are often used to analyze multiple horizons identifying

short-, intermediate-, and long-term risks. When using

earnings simulation models, IRR exposures are often more

accurate when projected over at least a two-year period.

Using a two-year time frame better captures the full impact

of important transactions, tactics, and strategies, which

may be hidden by only viewing projections over shorter

time horizons. Management should be encouraged to

measure earnings at risk for each one-year period over

their simulation horizon to better understand how risks

evolve over time. For example, if the bank runs a two year

simulation, one- and two-year simulation reports should be

generated.

Longer-term earnings simulations of up to five to seven

years may be recommended for institutions with material

holdings of products with embedded options. Such

extended simulations can be helpful for IRR analysis and

economic value measurements. It is usually easier for an

extended simulation model to identify when long-term

mismatches occur (e.g., it can show that a bank is liability

sensitive in years two, three, and four, but asset sensitive in

years five, six, and seven), whereas EVE models aggregate

the effect of such mismatches.

Institutions may vary their simulation rate scenarios based

on factors such as pricing strategies, balance sheet

compositions, hedging activities, etc. Simulation may also

measure risks presented by non-parallel yield curve shifts.

Institutions can run static or dynamic simulations. Static

models are based on current exposures and assume a

constant balance sheet with no new growth. The models

can also include replacement-growth assumptions where

replacement growth is used to offset reductions in the

balance sheet during the simulation period.

Dynamic simulation models may assume asset growth,

changes in existing business lines, new business, or

changes in management or customer behaviors. Dynamic

simulation models can be useful for business planning and

budgeting purposes. However, these simulations are

highly dependent on key variables and assumptions that

are difficult to project with accuracy over an extended

period. Also, when management changes simulation

scenarios, it may lose insights on the bank’s current IRR

positions. Dynamic simulations can provide beneficial

information but, due to their complexity and multitude of

assumptions, can be difficult to use effectively and may

mask significant risks.

Projected growth assumptions in dynamic modeling often

alter the balance sheet in a manner that reflects reduced

IRR exposure. For example, if a liability-sensitive bank

assumes significant growth in one-year adjustable rate

mortgages or long-term liabilities and the growth targets

are not met, management may have underestimated

exposures to changing interest rates. Therefore, when

performing dynamic simulations, institutions should also

run static or no-growth simulations to ensure they produce

an accurate, comparative description of the bank’s IRR

exposure.

Economic Value of Equity

Despite their benefits, both static and dynamic earnings

simulations have limitations in quantifying IRR exposure.

As a result, economic value methodologies should also be

used to broaden the assessment of IRR exposures,

particularly to capital.

Economic value methodologies attempt to estimate the

changes in a bank’s economic value of capital caused by

changes in interest rates. A bank’s economic value of

equity represents the present value of the expected cash

flows on assets minus the present value of the expected

cash flows on liabilities, plus or minus the present value of

the expected cash flows on off-balance sheet instruments.

Sensitivity to Market Risk (7/18) 7.1-8 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

Typically, an EVE model projects the value of a bank’s

economic capital for a base-case scenario, and then

compares it to a stress scenario. These models go by

various names and acronyms, such as EVE, MVE (Market

Value of Equity), or NPV (Net Present Value).

In theory, an economic valuation approach has a broader

scope than an earnings approach, since it captures all

anticipated cash flows and is generally more effective in

capturing embedded options. An economic valuation

approach measures all estimated changes to the balance

sheet and earnings, as opposed to gap models and earnings

simulations, which generally measure shorter-term balance

sheet and earnings projections. Economic valuation

methods can be an effective supplement to short-term

measures.

Many institutions can benefit from the use of economic

value methods and should establish EVE risk limits and

integrate economic valuation methods into their IRR

measurement procedures. Because different EVE models

calculate different base-case economic capital values for

the same bank, limits should generally be based on the

change of economic capital rather than absolute levels of

economic capital. Accordingly, examiners should assess

the relative changes in economic value of capital as a key

indication of risk.

Most economic value models use a static approach where

the analysis does not incorporate new business lines and all

financial instruments are held until final payout or

maturity. The analysis shows a snapshot of the risk

inherent in a portfolio or balance sheet. However, this is

not always the case as some models incorporate dynamic

techniques that provide forward-looking estimates of

economic value.

Because EVE estimates the future cash flows of the bank’s

financial instruments, the cash flows can be difficult to

accurately quantify. This can be especially true for non-

maturity deposits since the products generally have

uncertain cash flows and durations. Consequently,

estimating the value of these accounts can be difficult and

requires the use of several assumptions. Management

should be cautious when making EVE assumptions, as

output errors can be more pronounced in long-term

measurements. Examiners should consider the

significance, accuracy, and sensitivity of underlying

assumptions when assessing EVE models.

When modeling complex products with embedded options,

the importance of data aggregation and stratification

should not be overlooked. Complex or structured

securities should be modeled on an individual basis, and

homogenous balance sheet accounts should be aggregated

by common IRR features. For example, loan portfolios,

when possible, should be aggregated by product type,

coupon, maturity, and prepayment volatility. For

adjustable rate portfolios, modeling should include more

IRR attributes, such as coupon reset dates and indexes;

embedded caps and floors; and prepayment penalties.

Despite being different methodologies, earnings simulation

and EVE models generally provide a consistent view of

IRR trends. However, the two approaches may also

generate divergent outcomes. In many cases, earnings

simulation models provide shorter-term results and EVE

models provide a much longer-term risk profile. These

divergent outcomes can result from a variety of factors,

such as the structure of the balance sheet, including the

bank’s derivative positions and off-balance sheet items, the

interest rate environment, the timing of asset/liability

mismatches, the sensitivity of funding sources to interest

rate changes, and the volume of fixed- or floating-rate

assets. Because many versions of each model type are

available, management should ensure that the models used

capture all significant risk factors.

←

STRESS TESTING

Stress testing, which includes both scenario and sensitivity

analysis, is an integral part of IRR management. Scenario

analysis estimates possible outcomes given an event or

series of events, while sensitivity analysis estimates the

impact of change in one or only a few of a model’s

significant parameters.

Management should assess a range of alternative interest

rate scenarios when conducting scenario analyses. The

range should be sufficient to fully identify repricing, basis,

and yield curve risks as well as the risk of embedded

options. In many cases, static interest rate shocks

consisting of parallel shifts in the yield curve of only plus

and minus 200 basis points are not sufficient to adequately

assess IRR exposure. Therefore, management should

regularly assess a wide range of exposures across different

periods, including changes in rates of greater magnitude

(e.g., up and down 300 and 400 basis points). When

conducting stress tests, management should give special

consideration to financial instruments or markets where

concentrations exist, as such positions may be difficult to

unwind or hedge during periods of market stress.

Management should compare stress test results against

approved limits.

Management should ensure their scenarios are rigorous

and consistent with the existing level of rates and the

interest rate cycle. For example, in low-rate environments,

scenarios involving significant declines in market rates can

be deemphasized in favor of increasing the number and

size of alternative rising-rate scenarios. Alternatively,

RMS Manual of Examination Policies 7.1-9 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

there may be instances where more extreme stress tests

would be desirable.

Depending on a bank’s IRR profile, stress scenarios should

include:

• Instantaneous and significant rate changes,

• Substantial rate changes over time,

• Changes in the relationships between key market

rates, and

• Changes in the shape or slope of the yield curve.

Not all financial institutions need to use the full range of

the scenarios discussed above. Non-complex institutions

(for instance, institutions with limited embedded options or

structured products) may be able to justify running fewer

or less intricate scenarios.

Management should run repricing risk scenarios regularly.

When applicable, institutions should also run scenarios for

other IRR risks, such as basis and yield curve risks.

Institutions should assess these risk exposures at least

annually or when the risk profile of a bank changes, for

example, because of acquisitions, significant new products,

or new hedging programs. If a bank shows material

exposure to one of these risks, an appropriate scenario

should be included in monthly or quarterly IRR

monitoring. If an institution has relatively non-complex

exposure to basis, yield curve, or options risk, management

should document that the exposure is minimal. For

example, management may document its assessment with

a short narrative description of what percentage of assets

and liabilities are tied to various indices and a description

of the potential impact of the risks. These reports should

typically be reviewed by the board at least annually.

Sensitivity analysis should be included in stress testing to

help determine which assumptions have the most influence

on a model’s output. By identifying key assumptions,

management, when necessary, can refine the assumptions

to increase the accuracy of their models. The most

significant variables can be tested by keeping all other

variables constant, changing the variable in question, and

comparing the results to the base-case scenario.

Additionally, sensitivity analysis can be used to determine

the conditions under which key business assumptions or

model parameters break down or when IRR may be

exacerbated by other risks or earnings pressures. When

management includes assumptions based on strategic

initiatives, it is imperative that they assess the impact of

not meeting projections. (Refer to Sensitivity Testing -

Key Assumptions for more details.)

←

INTEREST RATE RISK MEASUREMENT

SYSTEMS

The IRR measurement system should be appropriate for

institution’s risk profile. The measurement system should

capture all material sources of IRR and generate

meaningful reports for senior management and the board

of directors. Management should ensure risks are

measured over a relevant range of interest rate changes,

including meaningful stress situations. Further, the

measurement system must be subject to appropriate

internal controls and periodic independent reviews. The

IRR measurement process should be well documented and

administered by individuals with sufficient technical

knowledge.

IRR measurement systems can range from simple methods

to sophisticated programs that include stochastic data

modeling. (Stochastic modeling involves using one or

more random variables in a model.) However, all

measurement systems should use generally accepted

financial concepts and risk measurement techniques and

have an adequate level of transparency. If a third-party

model is used, management should review the adequacy

and comprehensiveness of the vendor’s model-validations

and internal control reviews. Also, management should

consider the capabilities of the software to meet the

institution’s future needs and the adequacy of ongoing

vendor support and training.

A bank’s IRR measurement system is a critical part of its

overall risk management process. Examiners rely heavily

on the output of the measurement systems when assessing

sensitivity to market risk. Accordingly, the review of such

systems and their operation is a crucial element of the

examination process. The review process should address

the following items:

• Capabilities of the measurement system,

• Accuracy of system inputs,

• Reasonableness and documentation of material

assumptions,

• Usefulness of system output/reports, and

• Adequacy of periodic variance analysis.

Measurement System Capabilities

The IRR measurement system should capture and reliably

estimate all material risk exposures. Therefore, the system

should consider all significant balance sheet categories,

income statement items, and risk factors. For example, if

an institution has material holdings of mortgage loans or

mortgage-backed securities, then its measurement system

should be able to adequately incorporate prepayment

Sensitivity to Market Risk (7/18) 7.1-10 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

projections. Likewise, if the bank has a mortgage banking

operation that generates material fee income, its system

should capture the rate sensitivity of this noninterest

income.

When an institution develops an IRR model internally or

considers acquiring a third-party model, management

should assess its suitability by evaluating the model’s

ability to reasonably capture all relevant and material IRR

exposures. Additionally, management should periodically

re-evaluate the adequacy of a model in use as risk

positions, strategies, and activities change.

To effectively use its IRR measurement system,

management must fully understand the system’s

capabilities, limitations, quantitative methodologies, and

use of assumptions.

System Documentation

Both purchased and internally developed systems should

be supported by adequate documentation. System

documentation should provide complete information

regarding the factors discussed above. Management

should be familiar with and retain all pertinent system

documentation. Management should also review and

maintain documentation of changes or upgrades to the

model.

Adequacy of Measurement System Inputs

A model’s accuracy depends on the assumptions and data

used. Like any model, inaccurate data or unreasonable

assumptions will render inaccurate results.

System data should accurately reflect the bank’s current

condition. When evaluating the adequacy of a model,

management should consider the extent to which the

model uses automated versus manual processes; whether

the model has automated interfaces with the bank’s core

systems; and the funds, hardware, staff, and expertise

needed to run and maintain the model.

Examination of the system’s input process should focus on

the procedures for inputting and reconciling system data,

categorizing and aggregating account data, ensuring the

completeness of account data, and assessing the

effectiveness of internal controls and independent reviews.

The internal control process must be comprehensive

enough to ensure that data inputs are accurate and

complete prior to running the system and generating

reports. The bank may input data manually, through data-

extract programs, or a combination of both techniques.

Internal control procedures should be established to ensure

that input data, such as general ledger balances and

contractual terms, are accurately captured. Institutions

should verify system inputs by having experienced

personnel reconcile the balances to the general ledger.

This is often done using automated software that can

identify and report exception items.

In addition to capturing account balances, institutions with

complex balance sheets should use measurement systems

that adequately capture the embedded market risk of all

material on- and off-balance sheet activity. Most

measurement systems allow for the input of the following

contractual terms:

• Current balance,

• Contractual maturities,

• Principal and interest payments and frequencies,

• Coupon rates and repricing frequencies,

• Contractual caps and floors, and

• Contractual optionality (such as security or borrowing

calls).

Account Aggregation

Account aggregation is the process of grouping together

accounts of similar types and cash flow characteristics.

This is an important component of the data input process

as account aggregation improves the measurement

system’s efficiencies. Typically, loans of similar rate,

maturity, and type (e.g., 6 percent, 30 year, residential

loans) are aggregated. Grouping 6 percent, 30 year

residential loans together may be appropriate, but grouping

together 6 percent fixed-rate loans with 6 percent

adjustable-rate loans is not.

The degree of account aggregation will vary from one

institution to another. Institutions should ensure the model

allows for a sufficient separation of accounts with

significantly different cash flow patterns. For example,

models that aggregate information based on Call Report

data may not provide the granularity necessary for

institutions with significant levels of embedded options.

When applicable, institutions should ensure their systems

have the ability to model highly structured instruments and

bank-specific products.

Both contractual and behavioral characteristics should be

considered when determining the cash flow patterns of

accounts to aggregate. The process of determining which

accounts are combined should be transparent, documented,

and periodically reviewed. Furthermore, requests for

changes to existing groups or new account aggregations

should be formalized and documented. Institutions should

maintain documentation disclosing the characteristics of

RMS Manual of Examination Policies 7.1-11 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

aggregated assets and liabilities (including all derivative

instruments), and off-balance sheet items.

Assumptions

Assessing the reasonableness of assumptions is a critical

part of reviewing an IRR measurement system. It is

important that assumptions accurately reflect

management’s expectations regarding interest rates,

customer behaviors, and local and macro-economic

factors. Assumptions are typically derived using a

combination of internal analysis and external sources. All

material assumptions should be regularly updated and

supported with thorough analysis and documentation.

IRR measurement systems rely on assumptions regarding

key parameters, such as:

• Projected interest rates,

• Driver rate relationships,

• Non-maturity deposits, and

• Prepayments.

It is important that material assumptions be updated

regularly to reflect the current market and operating

environment. Furthermore, the process for developing

material assumptions should be formalized and

periodically assessed (at least annually for critical

assumptions). This periodic assessment of the information

and processes used to generate assumptions may prompt

management to reevaluate its assumptions in order to

better reflect current strategies or customer behaviors.

Sensitivity Testing - Key Assumptions

Proper IRR management requires an understanding of

which assumptions have the greatest impact on results.

Through sensitivity testing, management can identify the

assumptions that have the most effect on model results.

Documentation and monitoring should reflect the relative

importance of assumptions. Sensitivity testing can also be

used to identify less material assumptions, where

assumption documentation, monitoring, and testing are

less critical. Sensitivity testing can also be used to identify

weaknesses in the model. For example, if an institution

tested an assumption that was expected to have a critical

impact on the model result, but instead found that it had

little or no influence on the model output, further

investigation would be warranted.

Sensitivity testing should only be applied to one

assumption at a time and should test the effects of both

large and small changes in an assumption on the model’s

overall output. For example, if an institution wanted to

test the sensitivity of non-maturity deposit decay rates, it

could alter its non-maturity deposit beta assumptions

incrementally (up and down) in multiple scenarios (e.g., a

10, 25, and 50 percent increase/decrease from the base-

case assumption). The revised results could then be

compared to the base-case scenario. If a change in the

assumption disproportionately impacts the model, then

management should implement more robust assumption

documentation, monitoring, and testing. Another sound

practice when testing assumptions is to determine how

extreme changes in key assumptions impact results and

whether the results approach approved tolerance levels.

Conducting sensitivity testing on an annual basis is usually

adequate for many institutions. However, more frequent

tests should be performed if concerns are identified.

Institutions should document the results of sensitivity

testing and present the results to management and the

board. The results of sensitivity testing should be

considered when setting various assumptions.

Management should conduct thorough due diligence

before changing key assumptions that can materially alter

model results. Key assumption changes should be

properly documented and reviewed by the board.

Projected interest rate assumptions are a critical part of

measuring IRR and may be generated by internal analysis

or external sources. Internal interest rate forecasts, which

may be derived from implied forward yield curves,

economic analysis, or historical regressions, should be

documented to support the assumptions used in the

analysis. Key rate assumptions that should be considered

include assumptions for general market rates, repricing

rates, replacement interest rates, and discount rates.

Most institutions perform scenario analysis using

deterministic interest rate yield curves. With the

deterministic method, all interest rate scenarios are set by

the user; that is, management selects the interest rate

changes to simulate in the model. The deterministic

method differs from the more complex and sophisticated

stochastic method where multiple scenarios are generated

using random path-dependent variables. (Further

discussion of deterministic and stochastic methods may be

found in the glossary.)

Analysis should be performed using a base-case interest

rate scenario, as well as low-probability/high-risk

scenarios, so that management can better estimate the

impact to earnings and capital levels in stressed interest

rate scenarios. The base-case interest rate scenario should

be consistent with other forecasts used in the bank’s

overall planning process and should remain reasonably

consistent across reporting periods. Any changes in the

source of interest rate forecasts between reporting periods

should be justified and documented.

Sensitivity to Market Risk (7/18) 7.1-12 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

Driver rates are used extensively in most income

simulation and EVE models. The models capture the

relationship between primary market interest rates (driver

rates) and the rates of bank products. While there may be

no direct connection between bank rates and the driver

rate, the driver rate is chosen as a proxy for management’s

reaction to market changes. This frees management from

needing to set rates explicitly for each loan or deposit type

for each projected scenario. In most cases, bank rates are

set to move in relation to the driver rate. The move may

be referred to as a spread (when a specified number of

basis points are added to or subtracted from a driver rate),

or as a beta factor (when based on a percentage change in a

driver rate). For example, management might specify that

the rate paid on MMDAs will increase 75 basis points if

the yield on one-year Treasury bills increases 100 basis

points. By designating this relationship, pricing on all

products linked to the driver rate will change to reflect the

relationship built into the model. More complex systems

may use a variety of driver rates tailored for different

products. While most systems maintain static rate

relationships, more sophisticated systems can alter

relationships for different interest rate environments.

Spread or beta assumptions should be based on an analysis

of the relationship between the product (e.g., MMDA) and

the driver rate (e.g., federal funds rate). To determine the

spread or beta, management can perform correlation or

regression analysis to quantify the historical relationship

between the product and driver rates.

Correlation analysis may also be used to determine the

level of basis risk when instruments are tied to different

indices. For instance, if an institution enters into a

leveraging strategy that uses borrowed funds tied to

LIBOR to invest in U.S. Treasury securities, correlation

analysis can be performed to determine how closely the

related rates move together. Less correlated instruments

present greater basis risk.

Non-maturity deposit (NMD) rate sensitivity is typically

one of the most critical and most difficult assumptions that

management makes when measuring IRR exposure. The

potential actions of management and customers need to be

considered. Just as customers have control over the level

and location of their deposit accounts, management has

broad control over the rates paid on these accounts. In

setting rates, management must take into account a wide

array of factors, including local and national competition,

the bank’s funding needs, and the relative costs of

alternative funding sources.

The assumptions modeled for NMDs should reflect both

aspects of this relationship: management’s control over

rates and customers’ control over their funds.

Consideration should be given not only to historical

correlation analysis, but also to management’s intentions

regarding future rate movements. If the measurement

system has the capacity to reflect different assumptions for

rising and falling rates, management should establish rate

sensitivity assumptions for both scenarios.

Non-maturity deposits present a unique problem in EVE

modeling because they lack contractual maturity dates.

Generally an asset or liability must have a maturity date in

order to be valued under present value methods.

Therefore, in order to successfully model these accounts,

an EVE model must use management’s assumptions

regarding the maturity of the accounts. The most common

of these assumptions is the decay rate assumption. The

decay rate reflects the amount of nonmaturity (and other)

deposits that may be withdrawn or accounts closed in a

given rate environment.

Management should use NMD assumptions that reflect

institution-specific factors and avoid overreliance on

industry estimates or default assumptions contained in off-

the-shelf IRR models. Some institutions have difficultly

measuring decay rates on NMDs due to limited historical

data, acquisitions, mergers, or a lack of technical expertise.

Industry averages provide approximations, but are often

not the most accurate estimates because they are not

tailored to the bank’s products, pricing strategies, market,

and experience. However, management can use industry

estimates as a starting point until they develop adequate

data sets. Industry estimates can also serve as a

benchmarking tool to test the reasonableness of internal

assumptions. Management should consider modeling

different decay rates under various rate scenarios and,

when appropriate, should consider engaging third parties

to assist in determining NMD assumptions. Examiners

should recognize that NMD decay rate are often imprecise,

yet significant factors in IRR analysis.

Assumptions regarding NMDs are particularly critical in

market environments in which customer behaviors may be

atypical, or in which institutions are subject to heightened

competition for such deposits. Generally, rate-sensitive

and higher-cost deposits, such as brokered and Internet

deposits, reflect higher decay rates than other types of

deposits. Also, institutions experiencing or projecting

lower capital levels that may trigger brokered and high

interest rate deposit restrictions should adjust deposit

assumptions accordingly.

Prepayment assumptions are important considerations

when measuring optionality risk. Prepayment risk (or

conversely, extension risk) on loans and mortgage-related

securities are highly influenced by the direction of interest

rates. Prepayment assumptions may also be affected by

factors such as loan size, geographic area, credit score, and

fixed versus variable rates. It is critical that assumptions

RMS Manual of Examination Policies 7.1-13 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

be reasonable for each rate scenario measured. For

example, in an increasing rate environment, prepayment

assumptions should typically reflect lower prepayments

than in a declining rate environment.

Financial institutions may actively track internal

prepayment data or obtain prepayment statistics from

external sources. Management should consider the

reliability and applicability of external data and be

cognizant that market stress, externalities, or a change in

the institution’s condition may influence customer

behaviors.

Management should ensure that assumptions are

appropriate given the characteristics of the institution’s

various portfolios (i.e., prepayment speeds for a portfolio

of five percent loans would likely differ from a portfolio of

eight percent loans). In addition, proper aggregation of the

assets is necessary before applying assumptions.

Documentation and support of all significant assumptions,

including projected rates, spreads, customer behaviors, and

NMD rates should be maintained and available for

examiner review. Some measurement systems have only

limited ability to change model assumptions, in which case

documentation may be limited. Even in those cases, an

analysis of the applicability of the embedded assumptions

to the subject bank should be performed and maintained.

More complex systems entail a vast array of assumptions,

and thorough documentation of every assumption cannot

be realistically expected. However, management should

thoroughly support and document assumptions related to

the most significant institution or model risks.

Measurement System Reports

Many measurement systems are capable of providing

summary reports detailing key model assumptions.

Examiners should review a copy of these reports when

analyzing a measurement system.

Most asset/liability management systems offer an array of

summary reports (such as a chart of accounts and account

attribute reports) that aid management in reviewing

measurement system assumptions. These reports may also

provide information regarding the contractual terms and

parameters that have been entered into the system for

various account types and financial instruments.

If an institution is unable to provide assumption

summaries, examiners should determine whether the

absence of the report is due to measurement system

limitations or bank personnel’s lack of familiarity with

system capabilities. Typically, measurement system user

manuals will provide a list of reports that may be

generated by the system.

Assumption summary reports are an important tool that

management and examiners can use to ensure that

reasonable assumptions have been entered into the

measurement system. The reports can also be useful to

examiners when management does not maintain adequate

documentation of current assumptions. For example, when

assumption summary reports are regularly produced and

retained, examiners can compare current assumptions

against historical assumption reports.

To ensure proper controls over significant assumption

changes, management should establish procedures for

reviewing the reasonableness of assumption changes and

for approving those changes before they occur.

Measurement System Results

After data and assumptions have been input, the IRR

measurement system performs calculations. The

calculations measure the IRR in the bank’s assets,

liabilities, and off-balance sheet items. The measurement

system should generate summary reports that highlight the

bank’s sensitivity to changes in market rates given various

interest rate scenarios. These reports typically indicate the

change in net income or net interest income and/or

economic value of equity. Some systems may also provide

a gap report highlighting asset/liability mismatches over

various time horizons. More detailed reports may be

available on some systems that can be used to test the

reasonableness, consistency, and accuracy of the output.

They may also assist the examiner in identifying or

verifying the system’s underlying assumptions.

Management should have formalized procedures in place

for reviewing measurement system results and reporting to

the board or a board committee. Reports provided to the

board and senior management should be clear, concise,

timely, and informative in order to assist the board and

senior management in making decisions. The results of

the measurement system should also highlight deviations

from board-approved IRR exposure limits. Examiners

should review follow-up actions and communication

relevant to any material breaches in board-approved limits.

Examiners should also review the presentations or analyses

provided to senior management, board members, and the

ALCO, as well as any relevant meeting minutes.

Variance Analysis

Variance analysis (also known as back-testing) can provide

valuable insights into the accuracy and reasonableness of

IRR models and is an integral part of the control process

for IRR management. Variance analysis involves

identifying material differences between actual and

forecasted income statement and balance sheet amounts

Sensitivity to Market Risk (7/18) 7.1-14 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

and ascertaining the causes of the differences. Variances

can be readily identified by direct comparison of the

financial statements for a particular forecast period, or by

using key financial indicators, such as net interest margin,

cost of funds, or asset-yield comparisons.

Variance analysis can help management understand the

primary reasons for material differences between projected

and actual results. It can also provide a means to improve

the precision of the IRR measurement system. Periodic

variance analysis helps assure management and the board

that the system is accomplishing its primary goal of

providing meaningful information on the level of IRR.

Variance analysis provides an opportunity for a deeper

understanding of both the system and its results.

Variance analysis should be done periodically and no less

frequently than annually. Further, management should

document their analysis, highlighting any material

variances, the primary cause of identified variances, and

any proposed or implemented corrective actions.

Variances resulting from errors can be broken down into

three major components: input, modeling, or assumption

errors. When conducting variance analysis, management

should attempt to pinpoint the cause of all material

variances. Mathematical flaws, while relatively rare in

widely available purchased systems, can occur. Other

types of modeling errors can be caused by inaccurate data

input, user unfamiliarity with the model, over-aggregation

of account types, or the use of a model with insufficient

capabilities.

Data errors can be minimized by strong internal controls

and may be identified through selective transaction testing.

Many models can compare the results of historical IRR

simulations with actual financial results. Significant

variances can help management identify, and subsequently

correct, identified issues with the model setup, such as

inappropriate account aggregations or the failure to include

key account characteristics.

Assumption Variance Analysis

All IRR measurement systems rely heavily on a series of

assumptions, and assessing their reasonableness is critical

to ensuring the integrity of the measurement system

results. Just as actual financial results can be expected to

vary from forecasts, the assumptions that form the basis of

that forecast can be expected to vary from actual events.

Institutions should have formalized procedures for

periodically identifying material differences between

assumed and realized values. Formal procedures help

identify the key reasons for variances. Even if material

financial variances are absent, the model’s significant

assumptions should be compared to actual performance.

Compensating differences may have masked important

variances. For example, an institution with a large

mortgage portfolio may find that actual prepayment speeds

were significantly higher than projected, but new loan

production replaced the run-off. In this case, there may

only be an immaterial variance in the ending loan balance,

but a significant variance in projected vs. actual

prepayments.

Given the large number of assumptions inherent in most

measurement systems, a thorough review of every

assumption during each measurement cycle is unrealistic.

However, key assumptions should be checked against

actual behaviors on a regular basis. Key assumptions

include those dealing with interest rate movements, driver

rates, non-maturity deposits, prepayment speeds, and

account aggregations. Variance analysis should be used to

identify the differences attributable to rate assumptions and

other factors in order to better understand how those

factors influenced modeled results.

Driver rate variances occur when the expected correlation

between a bank rate and its driver rate does not act as

predicted. Variance analysis is used to determine the

significance of the difference and should address whether

the difference is due to an inaccurate correlation between

the subject and driver rate, or due to inappropriate spreads

or beta factors. Ideally, the relationship between subject

and driver rates should be documented, and the

relationship should factor in historical correlations and

management’s intentions regarding future movements.

Non-maturity deposit assumptions may cause significant

variances. If the measurement system forecast an

increasing net interest margin in a rising rate environment,

while the actual margin declined, the cause may involve

NMD assumptions. Many models treat NMD rates as very

insensitive to yield curve changes, while actual practices

are to manage the rates more actively. This can lead to

model measurements that show the bank as asset sensitive

or neutral, when past performance shows it to be liability

sensitive. Periodic variance analysis may identify this

discrepancy and allow management to more effectively use

the IRR measurement tool. Note: Examiners should

recognize that models are forward looking; therefore the

usefulness of historical variance analysis may be limited.

Prepayment speed variances occur when actual

prepayments do not mirror those projected. Variances are

not uncommon as the cash flows are difficult to model and

predict; however, management should monitor

prepayments and revise related assumptions if material

variances occur.

Inappropriate account aggregation c

an also lead to

significant variances. For example, when comparing

RMS Manual of Examination Policies 7.1-15 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

actual and modeled loan interest income, an institution

may find that the model overestimated income in a falling

rate environment because real estate loans with

significantly different prepayment characteristics were

aggregated together.

Many models measure static IRR, that is, what would

happen to the current balance sheet if only interest rates

changed. Other models incorporate management

projections about asset and liability growth and changes in

product mix. Variance analysis in the latter instance is

complicated by the need to segregate variances due to

balance sheet changes from those caused by rate

movements.

←

OTHER RISK FACTORS TO CONSIDER

Although IRR is the principal market risk taken by most

financial institutions, other activities can significantly

increase (or reduce) a bank’s exposure and sensitivity to

market risk.

Foreign exchange activities expose institutions to the

price (exchange rate) risk that results from volatile

currency markets. Exchange rates depend upon a variety

of global and local factors that are difficult to predict,

including interest rates, economic performance, central

bank actions, and political developments.

Commodity activities involve using commodity contracts

(including futures and options) to speculate or hedge.

Commodity prices depend upon many factors and are very

difficult to forecast.

Generally, institutions should only use foreign exchange or

commodity activities to hedge or control specific market

risks. Management, independent of the broker/dealer,

should demonstrate expertise commensurate with the

activities undertaken. In addition, management should

produce documented analysis that clearly details the

effectiveness of all foreign exchange and commodity

hedging activities. The analysis should be prepared at

least quarterly and presented to the board for its review.

Note: Typical commodity hedging activities are

significantly different from speculative commodity

activities.

Equity trading and investing creates market risk

exposure because changes in equity prices can adversely

affect earnings and capital. The board and management

have a responsibility to identify, measure, monitor, and

control trading risks. Management should carefully

monitor all equity investments, regularly evaluate the

resulting market risk exposure, and provide timely reports

to the board.

Foreign exchange, commodities, and equity trading

requires a high level of technical and managerial expertise.

The risk management and measurement systems needed to

operate them effectively are likewise highly sophisticated

and require rigorous monitoring and testing. Foreign

exchange, commodity, or equity speculation, absent the

necessary controls and sufficient capital, might be

considered an unsuitable practice. When necessary,

contact legal counsel or capital markets specialists in your

region for additional guidance.

Interest Rate Risk Mitigation

Institutions can use several measures to mitigate IRR

exposures. If risk measures fall outside approved tolerance

guidelines and trigger corrective steps (which should be

guided by approved policies), management might alter

their balance sheet or engage in hedging activities.

Hedging strategies often involve using complex derivative

instruments and are not suitable for institutions lacking

technical expertise. When any IRR mitigation strategy is

considered, management should also consider other risks,

such as credit, liquidity, and operational risks.

When implementing IRR mitigation techniques, the board

and management should ensure that policies and approved

strategies address:

• Analysis of market, liquidity, credit, and operating

risks;

• Qualifications of personnel involved in implementing

and monitoring hedging strategies;

• Permissible strategies and types of derivative

contracts;

• Authority levels and titles of individuals approved to

initiate hedging transactions and related authority

limits;

• Risk limits for hedging activities such as position

limits (gross and net), maturity parameters, and

counterparty credit guidelines;

• Monitoring requirements for hedging activities,

including ensuring activities fall within approved

limits and management lines of authority; and

• Controls for ensuring management’s compliance with

technical accounting guidance that covers hedging

activities.

Institutions should not use derivative instruments for

hedging (whether or not hedge accounting is applied),

unless the board and senior management fully understand

the institution’s strategy and the potential risks and

benefits. Relying on outside consultants to assist with a

hedging strategy does not absolve the board and senior

management of their responsibility to understand and

Sensitivity to Market Risk (7/18) 7.1-16 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

oversee the risks of the activities. Hedging strategies

should be designed to limit downside earnings exposure or

manage income or EVE volatility. Activities conducted

solely to generate additional income should not be

considered hedging.

Altering the balance sheet is the most common method

institutions use to modify their IRR position. However,

this strategy may take time to implement and often cannot

quickly correct significant exposures. For example, if a

bank is liability sensitive and therefore exposed to rising

interest rates, management may decide to reduce their

retention of 30-year fixed-rate mortgages. Strategies may

include increased sales (possibly for securitization) of

longer-term mortgage products or pricing longer-term

mortgages above market rates in order to reduce the

volume of new loan originations. While this strategy may

reduce IRR over time, this method can be slow in

correcting material IRR imbalances and may not effect a

timely reduction in risk exposures.

Institutions may also attempt to address exposures to rising

interest rates by increasing longer-term deposit or

borrowing levels. However, several factors may hinder the

success of such strategies. There may be significant

competition or limited demand for longer-term time

deposits, and access to longer-term wholesale funding may

be limited or offered on unfavorable terms. Additionally,

embedded options (e.g., calls and step-up dates) in

wholesale funding sources can present measurement

challenges, and the cost of such funding can make this

approach prohibitive unless there is a clear productive use

for the funds.

Cash flow matching and duration matching are two

typical hedging strategies. The goal of these strategies is

to change a bank’s IRR exposure to meet specific cash

flow or duration targets. These strategies can be

accomplished by altering the balance sheet composition or

through the use of derivatives.

Some institutions refer to cash flow matching as matched

funding. The bank matches the terms (rate or maturity) of

funding and assets so that cash flows will reprice or mature

simultaneously and interest rate changes will not

significantly influence net cash flow. Cash flow matching

can be difficult for small institutions due to the wide range

of cash flows in most financial assets.

With a duration matching strategy, management may

attempt to match the duration of a pool of assets with the

duration of a pool of liabilities. The use of interest rate

derivatives or options might also be used to modify or

offset the duration of an existing pool of assets or

liabilities. The goal is to match the effective durations of

the pools in order to limit the net changes in fair values of

the pools, rather than matching the specific cash flows.

Duration matching is not a perfect strategy and may result

in imperfect hedging from a cash flow perspective and can

cause exposure to different kinds of risk (such as yield

curve and basis risk).

Derivative instruments are available to hedge IRR. These

instruments include, but are not limited to, swaps,

amortizing swaps, basis swaps, futures, forwards, caps,

options, floor options, and collars. The most common

derivatives used to hedge IRR are swaps and forwards. In

a pay-fixed swap transaction, a stream of fixed interest

payments from a commercial loan may be contractually

exchanged for a stream of floating-rate payments. This

swap effectively shortens the duration of the commercial

loan portfolio by reducing the asset/liability mismatch and

improves profitability in a rising-rate environment.

Conversely, the bank could lengthen the effective duration

of its floating-rate deposits by entering into a swap where a

floating-rate stream of payments is exchanged for a fixed-

rate payment stream.

Institutions that use hedging activities should understand

the true impact of a hedge (whether it actually decreases

risks), and understand its impact on earnings and capital.

All derivatives require fair value accounting adjustments,

which may result in earnings and capital volatility. While

management may utilize hedges to reduce certain risks in

their portfolio, analysis of the hedges should consider the

impact of related accounting adjustments on earnings and

capital.

Each institution using derivatives should establish an

effective process for managing related risks. The level of

formality in this process should be commensurate with the

activities involved and the level of risk approved by senior

management and the board.

←

INTERNAL CONTROLS

Establishing and maintaining an effective system of

internal controls and independent reviews is critical to the

risk management process and the general safety and

soundness of the bank. Institutions should have adequate

internal controls to ensure the integrity of their IRR

management process. These controls should promote

reliable financial reporting and compliance with internal

policies and relevant regulations. Internal control policies

and procedures should address appropriate approval

processes, adherence to exposure limits, reconciliations,

reporting, reviews, and other mechanisms designed to

provide a reasonable assurance that the bank’s IRR

management objectives are achieved. Internal control

policies and procedures should clearly define management

authorities and responsibilities and identify the individuals

RMS Manual of Examination Policies 7.1-17 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

and committees responsible for managing sensitivity to

market risk.

A sound control environment should also ensure adequate

separation of duties in key elements of the risk

management process to avoid potential conflicts of

interest. Institutions should have clearly defined duties

that are sufficiently independent from position-taking

functions of the bank. Additionally, IRR exposures should

be reported directly to senior management and the board of

directors. The nature and scope of such safeguards should

reflect the type and structure of the bank, the volume and

complexity of IRR incurred by the bank, and the

complexity of its transactions and commitments. More

complex institutions should have an independent unit

responsible for the design and administration of the bank’s

IRR measurement, monitoring, and control functions.

Independent Reviews

Regular independent reviews of its IRR management

process are an important element of a bank’s internal

control system. Internal reviews of the IRR measurement

system should include assessments of the assumptions,

parameters, and methodologies used. Such reviews should

seek to understand, test, and document the current

measurement process, evaluate the system’s accuracy, and

recommend solutions to any identified weaknesses. The

independent review should be tailored to the type and

complexity of an institution’s activities and encompass the

standards and desirable scope discussed below.

Regardless of the depth of the independent review, the

findings of the review should be reported to the board no

less frequently than annually, along with a summary of the

bank’s IRR measurement techniques and management

practices.

Independent Review Standards

The purpose of an independent review is to ensure that the

IRR measurement and management processes are sound.

Regardless of whether the review is performed by internal

staff or external entities, it is important these parties be

independent of any operational responsibility for the

measurement and management processes. They should not

perform any of the routine internal control functions such

as reconciling data inputs, developing assumptions, or

performing variance analysis.

Independent reviews should be performed at least

annually. The scope, responsibility, and authority for the

reviews should be clearly documented and encompass all

material aspects of the measurement process. The scope of

the independent review should generally be defined by the

internal audit staff and approved by the audit committee.

However, subject to board approval, it is acceptable for

another department of the bank, separate from the group

that measures IRR, to define, perform, and document the

independent review. A bank’s review processes should

meet the following minimum standards:

• Independence - Parties performing the independent

review should not be involved in the day-to-day IRR

measurement/management process. Institutions may

use internal staff, an outsourcing arrangement, or a

combination of the two to independently review the

measurement system. Management may find that the

internal audit department, or other staff independent of

the measurement system, has the knowledge and skills

to perform certain aspects of the review while using

external resources for other areas. When the

assessment of the measurement system is outsourced,

senior management and the board should ensure that

the procedures used meet the same standards required

of a satisfactory internal review.

• Skills and Knowledge - Senior management and the

board must ensure that individuals performing the

independent review have the knowledge and skills to

competently assess the measurement system and its

control environment.

• Transparency - The procedures used in the

independent review of the measurement system should

be clearly documented, and work papers should be

available to management, auditors, and examiners for

review. Senior management should ensure that they

have access to work papers even when external parties

perform the review.

• Communication of Results - Procedures should be

established for reporting independent review findings

at least annually to the board or board-delegated

committee.

Scope of Independent Review

Independent reviews provide a way to assess the adequacy

of a bank’s IRR measurement system. The level and depth

of the independent reviews should be commensurate with

the bank’s risks and activities. More complex institutions

should have a more rigorous independent review process.

Less complex institutions may rely upon less formal

reviews. At a minimum, each institution should have

procedures in place to independently review the input

process, assumptions used, and system output reports.

System-input reviews should evaluate the adequacy and

appropriateness of:

• The knowledge and skills of individuals responsible

for input to the measurement system;

• The reconciliation of the measurement system’s data

Sensitivity to Market Risk (7/18) 7.1-18 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

to the bank’s general ledger;

• The rules and methods of account aggregation used in

the measurement system;

• The accuracy of contractual terms captured within the

measurement system; and

• The source, completeness, accuracy, and procedures

for external data feeds.

Assumption reviews should evaluate the following issues:

• The process of developing assumptions for all

material asset, liability, and off-balance sheet

exposures;

• The process for reviewing and approving key

assumptions;

• The periodic review of assumptions for relevance,

applicability, and reasonableness; and

• The completeness of assumption analysis and its

supporting documentation.

System output and reporting assessments should include

coverage of the following:

• Inclusion of a sufficiently broad range of potential rate

scenarios,

• Accuracy of the IRR measurement and assurance that

all material exposures are captured,

• Timeliness and frequency of reporting to management

and the board,

• Compliance with operating policies and approved risk

limits,

• Performance and documentation of variance analyses

(back-testing), and

• Translation of model output into understandable

management reports that support decision making.

Theoretical and Mathematical Validations

The degree to which calculations in an IRR model should

be validated depends on the complexity of an institution’s

activities and IRR model. The complexity of many

measurement systems demands specialized knowledge and

skills to verify the mathematical equations. Less complex

institutions using simpler, vendor-supplied IRR models

can satisfy some, but not all, validation requirements with

independent attestation reports from the vendor.

Management should periodically discuss with vendors

what validation and internal control process assessments

have been conducted. The vendor should provide

documentation showing a credible, independent third party

has performed such assessments. Vendors should be able

to provide appropriate testing results to show their product

works as expected. They should also clearly indicate the

model’s limitations, assumptions, and where the product’s

use may be problematic. Such disclosures, exclusive of

confidential or proprietary information, should contain

useful insights regarding a model’s functionality and

outputs. However, a certification or validation report from

a vendor is only one component of a bank’s independent

review and should not be used as a substitute for an overall

validation review. Management is still responsible for any

aspect of the process under their control, such as data

input, assumption changes, etc.

As part of the validation process, management should

ensure that the software and mathematics of the IRR model

function as intended. Many community institutions use

largely standardized, vendor-provided models. In such

cases, the validations provided by vendors can be used to

support the accuracy of the model. For models that are

customized to an individual institution or in situations

where vendors are unable or unwilling to provide

appropriate certifications or validations, management is

responsible for validating the accuracy of the model’s

mathematics and soundness of the software.

Additionally, vendor models may be customized by an

institution for its particular circumstances. Management

should document and justify the institution’s customization

choices as part of the validation process. If vendors

provide input data or assumptions, their relevance to the

bank’s situation should be evaluated and approved.

Institutions should obtain information regarding the data

(e.g., vendor-derived assumptions) used to develop the

model and assess whether the data is representative of the

institution’s situation.

Complex institutions or those with significant IRR

exposures may need to perform more in-depth validation

procedures of the underlying mathematics. Validation

practices could include constructing a similar model to test

assumptions and outcomes or using an existing, well-

validated benchmark model, which is often a less costly

alternative. The benchmark model should have theoretical

underpinnings, methodologies, and inputs that are very

close to those used in the model being validated. More

complex institutions have used benchmarking effectively

to identify model errors that could distort IRR

measurements. The depth and extent of the validation

process should be consistent with the degree of risk

exposures.

Model certifications and validations commissioned by

vendors can be a useful part of an institution’s efforts to

evaluate the model’s development and conceptual

soundness. Although many vendors offer services for

process verification, benchmarking, or back-testing, the

services are usually separate engagements. Each

institution should ensure these engagements meet its

RMS Manual of Examination Policies 7.1-19 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

internal policy requirements for validations and

independent reviews.

←

EVALUATING SENSITIVITY TO

MARKET RISK

The sensitivity to market risk component reflects the

degree to which changes in interest rates, foreign exchange

rates, commodity prices, or equity prices can adversely

affect a financial institution’s earnings or economic

capital. When evaluating this component, consideration

should be given to: management’s ability to identify,

measure, monitor, and control market risk; the institution’s

size; the nature and complexity of its activities; and the

adequacy of its capital and earnings in relation to its level

of market risk exposure.

For many institutions, the primary source of market risk

arises from nontrading positions and their sensitivity to

changes in interest rates. In some larger institutions,

foreign operations can be a significant source of market

risk. For some institutions, trading activities are a major

source of market risk.

Market risk is rated based upon, but not limited to, an

assessment of the following evaluation factors:

• The sensitivity of the financial institution’s earnings

or the economic value of its capital to adverse changes

in interest rates, foreign exchanges rates, commodity

prices, or equity prices.·

• The ability of management to identify, measure,

monitor, and control exposure to market risk given the

institution’s size, complexity, and risk profile.

• The nature and complexity of interest rate risk

exposure arising from nontrading positions.

• Where appropriate, the nature and complexity of

market risk exposure arising from trading and foreign

operations.

Ratings

1. A rating of 1 indicates that market risk sensitivity is

well controlled and that there is minimal potential that

the earnings performance or capital position will be

adversely affected. Risk management practices are

strong for the size, sophistication, and market risk

accepted by the institution. The level of earnings and

capital provide substantial support for the degree of

market risk taken by the institution.

2. A rating of 2 indicates that market risk sensitivity is

adequately controlled and that there is only moderate

potential that the earnings performance or capital

position will be adversely affected. Risk management

practices are satisfactory for the size, sophistication,

and market risk accepted by the institution. The level

of earnings and capital provide adequate support for

the degree of market risk taken by the institution.

3. A rating of 3 indicates that control of market risk

sensitivity needs improvement or that there is

significant potential that the earnings performance or

capital position will be adversely affected. Risk

management practices need to be improved given the

size, sophistication, and level of market risk accepted

by the institution. The level of earnings and capital

may not adequately support the degree of market risk

taken by the institution.

4. A rating of 4 indicates that control of market risk

sensitivity is unacceptable or that there is high

potential that the earnings performance or capital

position will be adversely affected. Risk management

practices are deficient for the size, sophistication, and

level of market risk accepted by the institution. The

level of earnings and capital provide inadequate

support for the degree of market risk taken by the

institution.

5. A rating of 5 indicates that control of market risk

sensitivity is unacceptable or that the level of market

risk taken by the institution is an imminent threat to its

viability. Risk management practices are wholly

inadequate for the size, sophistication, and level of

market risk accepted by the institution.

Examination Standards and Goals

The following documents provide additional guidance for

managing IRR:

• Joint Agency Policy Statement on Interest Rate Risk,

• Interagency Advisory on Interest Rate Risk

Management, and

• Interagency Advisory on Interest Rate Risk

Management Frequently Asked Questions.

Interagency Policy Statement on Interest Rate

Risk

In 1996, the FDIC and the other Federal banking

regulators adopted the Sensitivity to Market Risk

component of the Uniform Financial Institutions Rating

System and issued a Joint Agency Policy Statement on

IRR (Policy Statement). The Policy Statement identifies

the key elements of sound IRR management and describes

prudent principles and practices for each of these elements.

It emphasizes the importance of adequate oversight by a

Sensitivity to Market Risk (7/18) 7.1-20 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

bank’s board of directors and senior management as well

as the importance of comprehensive risk management

processes. The Policy Statement also describes the critical

IRR-related factors that affect the Agencies’ evaluation of

an institution’s capital adequacy

Interagency Advisory-Interest Rate Risk

Management

In January 2010, the Agencies issued updated guidance to

clarify supervisory expectations for IRR management set

forth in the 1996 Policy Statement. The Interagency

Advisory on Interest Rate Risk Management (Advisory)

re-emphasizes the importance of effective corporate

governance, policies and procedures, risk measurement

and monitoring systems, stress testing, and internal

controls related to IRR exposures. The Advisory indicates

financial institutions should manage IRR commensurate

with their complexity, risk profile, business model, and

scope of operations. Additionally, the Advisory highlights

that effective IRR management involves not only the

identification and measurement of IRR, but also

appropriate risk mitigation strategies that may be used to

control IRR if exposure levels warrant corrective steps.

In January 2012, the agencies published supplemental

guidance addressing Frequently Asked Questions (FAQs)

on the 2010 Advisory. The FAQs provides additional

clarification on topics such as determining model

appropriateness; defining meaningful stress scenarios;

analyzing yield curve, basis, and option risk, as well as

using no-growth measurement scenarios. The FAQs also

describe effective procedures for model validations and

calculation of non-maturity deposit decay assumptions.

←

EXAMINATION PROCESS

FDIC examination procedures follow a risk-focused

framework that incorporates the guidelines outlined in the

1996 Policy Statement and the 2010 Advisory (including

the FAQs guidance) to efficiently allocate examination

resources. The scope of an examination should consider a

bank’s IRR exposure relative to earnings and capital, the

complexity of on- and off-balance sheet exposures, and the

strength of risk management processes.

Examiners can identify material exposures and risks by

reviewing the following items (most of which are available

during off-site analysis):

• Prior examination findings,

• Interest Rate Risk Standard Analysis (IRRSA),

• Net interest margin and net operating income trends,

• Board or committee minutes,

• Bank IRR analysis,

• Independent review or audit findings,

• Related bank policies and procedures,

• Balance sheet and account data,

• Strategic and business plans,

• Product pricing guidelines, and

• Derivatives activities.

Citing Examination Deficiencies

Material weaknesses in risk management processes, or

high levels of IRR exposure relative to capital, require

corrective action. Such actions may include

recommendations or directives to:

• Raise additional capital;

• Reduce levels of IRR exposure;

• Strengthen IRR management expertise;

• Improve IRR management information and

measurement systems; or

• Take other measures or combination of actions,

depending on the facts and circumstances of the

individual bank.

If an examiner determines that IRR weaknesses warrant

the listing of a contravention of regulatory guidance in the

Report of Examination, the 1996 Policy Statement should

be cited as the source guidance. Examiners may reference

the Advisory or the FAQs document in supporting

comments. A contravention of the interagency guidelines

detailed in Appendix A of Part 364 may also be warranted

for institutions with seriously deficient IRR programs.

Pursuant to Appendix A (II.E.) of Part 364, an institution

should:

• Manage interest rate risk in a manner that is

appropriate to the size of the institution and the

complexity of its assets and liabilities; and

• Provide for periodic reporting to management and the

board of directors regarding interest rate risk with

adequate information for management and the board

of directors to assess the level of risk.

Note: Accepting a reasonable degree of IRR is a

fundamental part of banking that significantly affects

profitability and shareholder values. Although risks must

be properly managed, exceptions to established IRR

policies and limits occasionally occur. Examiners should

not automatically criticize relatively minor exceptions to

established policies or internal limits if an institution has

appropriate, formal processes for monitoring, reviewing,

and approving exceptions.

RMS Manual of Examination Policies 7.1-21 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

Additionally, examiners are reminded that, if weaknesses

in a model or its assumptions are identified that render its

results unreliable, report comments supporting the

assigned rating should not rely on (or, at a minimum,

should qualify any use of) the resulting data.

←

MARKET RISK GLOSSARY

Deterministic Rate Scenarios

Deterministic modeling techniques allow management to

specify the direction, amount, and timing of future interest

rates in order to measure the potential impact the changes

may have on earnings and capital. The following items are

examples of commonly used deterministic interest rate

scenarios:

• Rate Shock Scenario – In this scenario, rate changes

are immediate and sustained. For example, in a plus

300 basis point scenario, the full effect of the rate

increase would be administered in the first period

measured and remain in effect for all periods.

• Rate Ramp Scenario – In this scenario, rate changes

are applied gradually over the measured period. For

example, when measuring the effects of a 300 basis

point rate increase during a 12-month period, rates

would be increased 25 basis points each month.

• Stair Step Scenario – In this scenario, rate changes

are administered at less frequent intervals over the

measured period. For instance, in a 300 basis point

increasing rate environment measured over a two-year

time period, rates may be increased 50 basis points

each quarter of the first year and 25 basis points each

quarter of the second year.

Non-parallel Yield Curve Shifts

A shift in the yield curve in which yields do not change by

the same number of basis points for every maturity. When

running various interest rate scenarios, management may

set non-parallel shifts in a manner similar to deterministic

rate scenarios (rate shock, rate ramp, or stair step). The

scenarios often have a pivot point on the yield curve from

which longer-term and shorter-term rates change in

different amounts.

Static Models

Static simulation models are based on current exposures

and assume a constant, no-growth balance sheet. In order

to simulate no growth in balance sheet accounts, some

static models assume that all principal cash flows from a

particular account are reinvested back into that same

account. This assumption is sometimes referred to as

replacement growth.

Dynamic Models

Dynamic simulation models rely on detailed assumptions

regarding changes in existing business lines, new business,

and changes in management and customer behavior. The

assumptions change the existing balance sheet to reflect

expected business changes.

Stochastic Models

Stochastic modeling consists of the modeling of an

uncertain variable over time using a random selection

process. It recognizes that market variables, such as

interest rates, exhibit a general trend (drift) and some

degree of volatility around that trend. Stochastic models

provide a framework for the evaluation of the impact of

embedded options in financial instruments.

Constraints are usually imposed so that the model is

representative of current market conditions. For example,

if Treasury securities are priced using interest rate paths, a

constraint may be imposed so that the average present

value derived from all the paths must equal the observed

market price of the Treasury securities. In such a case, the

model can also be classified as a Stochastic No Arbitrage

Model.

Monte Carlo Simulation

A Monte Carlo simulation randomly generates a large

sample set of values from a reasonable population of

variables such as an interest rate. The stochastic model

provides a framework for the evolution of the variable, and

a Monte Carlo simulation is an application of that

stochastic model. The randomness in games of chance is

similar to how Monte Carlo simulation selects values at

random to simulate a model. When you turn a roulette

wheel, you know that one number within a range of

numbers will come up, but you do not know which number

will come up for any particular turn. The same concept

applies with a Monte Carlo simulation where the variables

(e.g., interest rates, security prices) have a known range of

values but an uncertain value for any particular time.

Monte Carlo simulations can take into account returns,

volatility, correlations, and other factors. Monte Carlo

programs can generate millions of different scenarios by

randomly changing a component for each run or iteration.

Monte Carlo simulation allows the banker to simulate

thousands of market-like scenarios and learn the

probability of a particular outcome or a range of outcomes.

Assume that the investment portfolio is run through 20,000

Sensitivity to Market Risk (7/18) 7.1-22 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

simulations, projecting 20,000 separate scenarios over a

two-year period, and acceptable results occur 16,000

times. This means that there is an 80 percent probability

that the portfolio will perform at an acceptable level. Like

any financial model, the results are sensitive to underlying

assumptions. The number of runs or simulations is also

important. For example, a Monte Carlo model with only

500 iterations captures fewer possible scenarios than one

that runs 50,000 iterations.

Spread Types

• Static Spread – Basis points, that when added to a set

of implied forward rates, discounts the cash flows of

an instrument back to its observed market value. For

an instrument without embedded optionality, the static

spread is the best measure of return in excess of the

risk-free rates provided by that instrument. For

instruments with embedded optionality, it may be

useful to calculate a static spread only as a starting

point for comparison with a more appropriate mark-

to-market spread measure, such as the option adjusted

spread.

• Option Adjusted Spread (OAS) – Basis points, that

when added to a set of interest rates discounts the cash

flows of an instrument back to its observed market

value. This measure only applies to instruments with

embedded optionality. The static spread applies to

instruments without embedded optionality. For

example, consider a mortgage-backed security, which

typically contains an embedded prepayment option.

Assume the static spread is 75 basis points. The OAS

would be less than the static spread of 75 basis points

because the volatility of interest rates reflected in an

OAS framework assigns more value to the borrower’s

prepayment option, thus reducing the value to the

MBS investor.

• OAS Process – In a stochastic valuation model, the

average value generated by all the interest rate paths

must equal the currently observed price of the

security. The initial computation in the model is

based on an assumed spread. The security value

derived is compared to the observed.

Duration Calculations

Macaulay duration calculates the weighted average term

to maturity of a security’s cash flows. Assume a bond

with three years remaining to maturity, bearing a 5 percent

coupon rate paid annually, when a 10 percent yield is

required.

Modified duration, calculated from Macaulay duration,

estimates price sensitivity for small interest rate changes.

The following formula can be used to estimate the

percentage change in a bond’s price:

Δ % = −Modified Duration x Δ Yield x 100

Note: The minus sign recognizes the inverse relationship

of price and yield.

For a 100 basis point change in rates, the estimated change

in price is equal to the modified duration. In other words,

using a modified duration of 2.59 percent, the price of a

bond would change approximately 2.6 percent for every

100 basis point change in rates. If rates changed by only

50 basis points, the bond would change approximately 1.3

percent.

Δ% = Modified Duration x Δ Yield x 100

= 2.59% x 50bp x 100

= 2.59% x .5

= 1.295%

The following formula can be used to estimate the dollar

change in price:

Δ$ = minus Price x Modified Duration x Δ Yield x 100

If the price of the bond had been $875.66, then its

approximate change in value (price), if rates changed by

50bp, would be ($875.66) x 1.295% = ($11.34).

If rates fell, the estimated value would be $887.00, while if

rates rose the estimated value would fall to $864.32.

Macaulay Duration Calculation

3 year bond, 5% coupon, 10% yield

Year Payment PV x T PVxT

1 $50 $45.5 x 1 = $45.5

2 $50 $41.3 x 2 = $82.6

3 $1,050

$788.9 x 3 = $2,366.7

Total $875.7 $2,494.8

T = Time period payment is received

Macaulay Duration: 2,494.8 / 875.7 = 2.85 years

Modified Duration Calculation

3 year bond, 5% coupon, 10% yield

Macaulay Duration = 2.85 years

Macaulay Duration

1 + (Yield / n)

= 2.85 / 1.10

n = coupons per year

Modified Duration = 2.59%

RMS Manual of Examination Policies 7.1-23 Sensitivity to Market Risk (7/18)

Federal Deposit Insurance Corporation

SENSITIVITY TO MARKET RISK Section 7.1

Duration-based price forecasts are generally precise when

used with small rate changes (1 to 5 basis points).

However, the accuracy of the forecasts decline when larger

rates changes (especially 100 basis points or more) are

involved. The reason for the declining accuracy of price

forecasts relates to the non-linear relationship between

prices and yields (a.k.a., convexity).

Convexity

Option-free financial instruments display positive

convexity. When rates decline, a positively convexed

instrument’s price increases at an increasing rate. When

rates rise, a positively convexed instrument’s price

decreases at a decreasing rate.

Negative convexity causes the duration of a security to

lengthen when rates rise and shorten when rates fall.

Instruments that contain embedded options demonstrate

negative convexity. When rates decline, a negatively

convexed instrument’s price increases at a decreasing rate.

When rates rise, the price of a negatively convexed

instrument will decline at an increasing rate.

For example, the value of the treasury security changes

relatively less in value in comparison to the sample

mortgage security, which declines more significantly.

However, as yields decrease, the treasury security gains

value at an increasing rate, while the mortgage security

gains only modestly. As interest rates decline, the

likelihood increases that borrowers will refinance (exercise

prepayment option). Therefore, the value of a mortgage

security does not increase at the same rate or magnitude as

a decline in interest rates.

Effective Duration and Effective Convexity

Effective duration and effective convexity are used to

calculate the price sensitivity of bonds with embedded

options. The calculations provide an approximate price

change of a bond given a parallel yield curve shift.

Measures of modified duration and convexity do not

provide accurate calculations of price sensitivity for bonds

with embedded options. Effective duration and convexity

provide a more accurate view of price sensitivity since the

measures allow for cash flows to change due to a change in

yield. Formula:

Effective Duration = (V

- V

)/(2V

x ΔY)

Effective Convexity = (V

+ V

- 2V

)/(2V

x ΔY)²

Where, ΔY = Change in market interest rate used to

calculate new values:

= Price if yield is increased by Change Y

= Price if yield is decreased by Change Y

= Initial price per $100 of par value

Assume: a three-year callable bond’s current market value

is $98.60 (V

); that interest rates are projected to change

by 100 basis points (Y); that the price of this bond given a

100 basis point increase in rates is $96.75 (V

); and that

the price of this bond given a 100 basis point decrease in

rates is $99.98 (V

To calculate effective duration and convexity:

Effective Duration =

(99.98 – 96.75)/(2(98.60)(.01)) = 1.64

Effective Convexity =

96.75 + 99.98 – 2(98.60)÷(2(98.60)(.01))² = -23.83

If we assume interest rates increase 100 basis points, the

approximate price change due to effective duration is the

following:

Percentage Price Change = -Effective Duration x Yield

Change

Percentage Change in Price = -1.64 x .01 = -1.64%

The approximate price change due to effective convexity is

the following:

½ x Effective Convexity x (Yield Change)²

½ x -23.83 x (0.01)² x 100 = -0.12%

Thus this bond’s price would be expected to decrease by

about 1.76 percent given a 100 bps rise in rates:

Effective

Duration

= -1.64%

Effective

Convexity

= -0.12%

-1.76%

Sensitivity to Market Risk (7/18) 7.1-24 RMS Manual of Examination Policies

Federal Deposit Insurance Corporation