The Evolution of ALM Risk Management Tools

June 2012Enterprise Risk Solutions

Robert J. Wyle, CFASenior Director, ALM

2

Outline

1. Defining Market Risk

2. Defining Asset and Liability Management (ALM)

3. The Evolution of ALM Tools

4. The Expanding Frontier of ALM

3

DEFINING MARKET RISK

Market Risk Defined

Risks pertaining to interest-rate and equity related instruments

Foreign exchange risk and commodities risk through the bank

The risk of adverse changes in market values over a liquidation period

What Is Market Risk?

5

Trading Book

Banking Book

RISK MEASUREMENT

RISK MEASUREMENT

INTERNAL CONTROLS

SOURCES OF

MARKET RISK

RISK MANAGEMENT

- Board and Senior Management Oversight

- Policies, Procedures and Limits

- Risk Measurement, Monitoring and Information Systems

- Internal Controls and Audit

MODELS USED

Earnings-at-Risk = Short-term

Economic-Value-at-Risk = Long-term

MODELS USED

Value-at-Risk

- Variance/Co-Variance

- Historical Simulation

- Monte-Carlo Simulation

RISK FACTORS

- INTEREST RATE

> Repricing Risk

> Yield-Curve Risk

> Basis Risk

> Options Risk

- EXCHANGE RATE

- COMMODITY

- EQUITY

This Schematic Shows How Market Risk (I.e., Risk Factors) Influences a Financial Institution. Note That the Trading and Banking Books are Each Modeled and Managed Separately. This is the Usual

Environment in Banking Organizations.

6

DEFINING ALM

7

Defining ALM

In its broadest sense, ALM is the financial risk management of any financial institution.

Risk Dimensions of ALM

» Policy Setting

» Structuring the Bank’s Repricing and Maturity Schedules

» Capital Management

» Liquidity Risk Management

» Internal Profitability Measurements

» Contingency Planning: Analyzing the Impact of External Shocks and how the Bank will Respond to those Shocks

8

The Goal of ALM

ALM

Risk

Volatility of

Cash Flows

Loss of Market Value

Opportunity

Forecasts

Strategy

Return

Mission =

Ensure Safety & Soundness + Maximize Risk Adj. Return

9

The ALM ProcessRisk

Reprise

Subjective ObjectiveChoices of Tasks ofRisk Management Risk Management

Define Risk Policy Measure Current Risk ExposureTarget Accounts Across Individual Accounts andRate Forecast Balance Sheet as a wholeProbability of Rate OutcomesSet Risk Limits

Measure Risk / Retrun Trade-OffHedging, restructuring analysis

Choose Determine Efficient Portfolios Most Subjectively Desirable Identify Efficient Combinations of Assets & Mix of Assets & Liabilities Liabilities

Subjective ObjectiveChoices of Tasks ofRisk Management Risk Management

Define Risk Policy Measure Current Risk ExposureTarget Accounts Across Individual Accounts andRate Forecast Balance Sheet as a wholeProbability of Rate OutcomesSet Risk Limits

Measure Risk / Retrun Trade-OffHedging, restructuring analysis

Choose Determine Efficient Portfolios Most Subjectively Desirable Identify Efficient Combinations of Assets & Mix of Assets & Liabilities Liabilities

Source: Measuring and Managing Interest Rate Risk: A Guide to Asset/Liability Models Used in Banks and Thrifts

Morgan Stanley Fixed Income Research, October 1984

10

The ALCO

Manage Risk + Efficiently Deploy Capital

ALCO

FINANCIAL

ALM MODELOPERATIONAL STRATEGIC

• Financial• Total balance sheet management• Funding• Interest rate risk• Currency risk• Derivatives Instruments• Strategy

• Operational• Organizational structure• IT• Data Flow• ALM Process

• Strategic• Policies• Capital Allocation

11

IRR Measurement Evolution

Gap Analysis

Beta Gap; Crude

Simulations

Strong Simulations; Static Economic-

Value

Multi-path Probabilistic distributions of

earnings and value

Late 1960’s

Indicators

1970’s

Estimates

1980’s

Estimates and Measures

1990’s +

Advanced Measures

12

A Brief History of ALM1970’s» Focus on Forecasting NII

» Little IRR Management

Early 1980’s» IRR management focus on gap, duration, and simple simulations.

» Rise of inter-departmental ALCO

mid 1980’s» Formal ALM, IRR management becomes a “unit” of the bank

Late 1980’s – Early 1990’s» ALM gradually incorporated into strategic planning

» Focus expands to capital adequacy and prudent leverage

» Plain vanilla and then complex derivatives

mid – late 1990’s» ALM increasingly important in reducing performance volatility

» Stochastic valuation gains ground

» Tools grow in sophistication: customer behaviour modelling

2000’s» ALM is integrated with credit risk management, resulting in Enterprise Risk Management (ERM)

» ALM increasingly embraces economic value as the primary focus

» Liquidity Risk Management increases in importance

13

ALM RISK MANAGEMENT TOOLS

14

Risk Management Tools

1. GAP Analysis

2. Net Interest Income Simulation (NII)

3. Standard Market Value Sensitivity Measures» Duration and Convexity

» Option Adjusted Valuation

4. Volatility Based Risk Measures» VAR

» EAR

15

GAP Analysis

» Gap analysis is an asset/liability management tool used to measure interest rate risk, make funding decisions, and allocate capital along the yield curve.

» Gap is simply the post-hedge difference between rate sensitive assets and rate sensitive liabilities, bucketed into the sooner of reprice, maturity, or expected call date.

» When periodic gap is zero, net interest income is hedged against changes in interest rates. However, when there is a positive gap, earnings decline as interest rates decrease and rise as interest rates increase.

» Gap is particularly useful for balance sheets that have little optionality.

16

7/28/2009 16:35 FEDERAL HOME LOAN BANK OF NEW YORK

ASSET/LIABILITY REPRICINGS

(Amounts in $ Billions)

STAT DATE: 8/31/2009

DURATION 17.89 YEARS:

Mar-10 Sep-10 Sep-12 Sep-14

OVERNIGHT Sep-09 Oct-09 Nov-09 Dec-09 Jan-10 Feb-10 Aug-10 Aug-12 Aug-14 AND BEYOND W.A.

Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. Amt. Rte. TOTALS Rates

ASSETS

FF/Resale 447 4.73% 447 4.73%

Term Inv 540 4.45% 686 4.85% 362 4.95% 408 5.12% 563 5.25% 773 5.37% 0 0.00% 0 0.00% 0 0.00% 310 5.44% 3,642 5.05%

Adj. MBS 878 5.49% 878 5.49%

MBS Sec. 29 7.30% 29 7.35% 27 7.42% 27 7.41% 23 7.20% 22 7.14% 120 7.13% 662 6.67% 684 6.85% 1,280 6.67% 2,904 6.77%

Total Invest 447 4.73% 1,447 5.14% 715 4.95% 390 5.13% 435 5.26% 586 5.32% 795 5.42% 120 7.13% 662 6.67% 684 6.85% 1,590 6.43% 7,870 5.72%

ARC/Var Adv 265 5.20% 342 4.48% 443 4.74% 463 5.03% 50 4.88% 31 5.22% 102 5.27% 0 0.00% 1,694 4.88%

Shrt Trm Adv 770 4.82% 4,443 4.88% 732 4.93% 663 5.07% 52 5.25% 14 5.34% 12 5.46% 52 5.56% 6,738 4.91%

Lng Trm Adv 170 4.79% 156 6.36% 121 6.43% 197 6.15% 210 5.07% 140 4.52% 1,186 5.36% 1,939 5.82% 514 5.80% 329 6.26% 4,961 5.68%

Callable Adv 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 25 5.00% 25 5.00%

Total Advs 1,034 4.91% 4,954 4.85% 1,330 5.03% 1,247 5.19% 299 5.78% 255 5.10% 254 4.87% 1,238 5.37% 1,939 5.82% 514 5.80% 354 6.17% 13,419 5.19%

FSLIC,AID,DDA 1 4.44% 80 4.76% 80 4.99% 120 5.10% 0 8.98% 0 8.01% 0 8.43% 1 8.23% 3 8.16% 2 8.19% 5 8.32% 291 5.09%

Ttl Earn Assets 1,482 4.86% 6,481 4.91% 2,125 5.01% 1,756 5.17% 734 5.47% 841 5.26% 1,050 5.29% 1,359 5.53% 2,629 5.98% 1,201 6.40% 1,923 6.47% 21,580 5.38%

Non Earn Assets 402

Total Assets 1,482 4.86% 6,481 4.91% 2,125 5.01% 1,756 5.17% 734 5.47% 841 5.26% 1,050 5.29% 1,359 5.53% 2,629 5.98% 1,201 6.40% 1,923 6.47% 21,982 5.28%

LIABILITIES

DDA Deposits 370 4.44% 370 4.44%

ON & Trm Dp 1,538 4.51% 114 4.51% 70 4.73% 70 4.70% 8 4.03% 6 3.90% 8 4.42% 17 5.10% 1,832 4.52%

Disc. note 2,088 4.74% 396 4.71% 75 4.95% 568 4.99% 420 5.13% 414 5.07% 207 5.33% 4,168 4.88%

Adj. Bonds 702 4.30% 380 4.55% 545 4.76% 0 0.00% 0 0.00% 0 0.00% 0 1,627 4.51%

Callable Bonds 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 25 4.42% 0 0.00% 0 0.00% 25 4.42%

Reg Bonds 50 6.64% 105 5.20% 70 6.44% 114 8.11% 175 8.03% 245 7.63% 1,878 5.77% 3,564 6.00% 411 7.10% 0 0.00% 6,612 6.15%

Fix Der Dbt 100 3.85% 0 0.00% 0 0.00% 0 0.00% 75 4.69% 155 3.86% 1,392 5.07% 2,447 5.44% 1,010 5.97% 175 6.16% 5,353 5.38%

Total Bonds 852 4.38% 485 4.69% 615 4.95% 114 8.11% 250 7.03% 400 6.17% 3,269 5.47% 6,036 5.77% 1,421 6.30% 175 6.16% 13,617 5.65%

REPOS 125 3.95% 63 4.74% 0 0.00% 0 0.00% 0 0.00% 0 0.00% 188 4.22%

Ttl Cost Liab. 1,908 4.49% 3,179 4.61% 1,014 4.70% 760 4.93% 690 5.49% 676 5.82% 822 5.60% 3,493 5.46% 6,036 5.77% 1,421 6.30% 175 6.16% 20,174 5.35%

Non Cost Liab. 454

Total Liabilities 1,908 4.49% 3,179 4.61% 1,014 4.70% 760 4.93% 690 5.49% 676 5.82% 822 5.60% 3,493 5.46% 6,036 5.77% 1,421 6.30% 175 6.16% 20,628 5.23%

Total Equity 1,353

HEDGES

Pay Swaps 2,553 4.80% 785 4.78% 949 5.07% 30 5.07% 150 5.28% 225 5.32% 0 0.00% 15 6.07% 0 0.00% 0 0.00% 4,707 4.90%

Rec Swaps 15 4.67% 30 8.71% 15 8.52% 0 0.00% 150 9.00% 150 9.13% 1,955 6.05% 2,337 6.40% 55 10.52% 0 0.00% 4,707 6.49%

HEDGE ADJUSTED ASSET/LIABILITY FLOWS

ASSETS 1,482 4.86% 6,496 4.91% 2,155 5.06% 1,771 5.20% 734 5.47% 991 5.82% 1,200 5.77% 3,314 5.83% 4,966 6.18% 1,256 6.58% 1,923 6.47% 26,287 5.58%

LIABS. 1,908 4.49% 5,732 4.69% 1,799 4.74% 1,709 5.01% 720 5.47% 826 5.72% 1,047 5.54% 3,493 5.46% 6,051 5.77% 1,421 6.30% 175 6.16% 24,881 5.27%

PRE-HEDGED GAPS

Periodic Gap -426 0.36% 3,302 0.30% 1,111 0.30% 996 0.24% 43 -0.02% 165 -0.57% 227 -0.31% -2,134 0.06% -3,407 0.22% -220 0.11% 1,748 0.31% 1,406

Cum. Gap -426 2,876 3,987 4,983 5,027 5,192 5,419 3,285 -122 -343 1,406

POST-HEDGED GAPS

Periodic Gap -426 0.36% 764 0.22% 356 0.32% 62 0.19% 13 0.00% 165 0.10% 152 0.23% -179 0.37% -1,085 0.42% -165 0.29% 1,748 0.31% 1,406 0.31%

Cum. Gap -426 338 694 756 770 935 1,087 908 -177 -343 1,406

Cumulative Gap Excluding O/N

*Spread is different from Return on Assets Report due to gross up of both Assets and Liabilities by interest rate swaps. Estimated Gross Margin is 0.40%

8/31/2009

17

Gap Strengths

» Easy and Intuitive to Understand

» Development Costs are Small

» Can Easily Set Risk-Limit Policies

18

Gap Weaknesses

» Sizeable mismatches can be hidden in buckets as short as one month.

» Fixation on plugging Gaps to zero restricts ALM choices because many different non-zero Gap combinations immunize NII as well.

» Cannot measure risk associated with options sensitive to interest rate risk such as prepayment options or deposit intangibles.

» Gap does not provide a single index number quantifying the risk exposure of a target account.

» Assumes interest rates change by the same amount for all assets and liabilities.

» Cash flows of interest are ignored.

» Administered non-market accounts such as prime or money markets?

» Cannot manage more than one target account simultaneously.

19

Asset/Liability Repricings

-1,000,000

-500,000

0

500,000

1,000,000

1,500,000

2,000,000

20

NII Simulation: The Brute Force Approach

» A computer simulation model starts with the current balance sheet, including detailed maturity or repricing schedules and the associated rates and yields of those balances, and forecasts the income statements, balance sheets, and cash flow schedules for a series of future time periods, typically 12 to 36 months.

» This is accomplished by literally simulating the repricings, maturities, rollovers, and new business originations for all balance sheet activities of the bank!

» To generate a plausible set of financial statements, assumptions must be made about a number of important issues, including target balances, maturity schedules for new business, yield curve behavior, non-yield curve rate assumptions, and pricing assumptions for new business.

21

Net Interest Income Sensitivity Analysis+3.00% +2.00% +1.00% Base -1.00% -2.00% -3.00%

HFS Portfolio 178,560 162,560 146,560 130,560 114,560 98,560 82,560

Investment Securities 53,384 52,758 52,131 51,505 50,879 50,252 49,626

Mortgage Backed Securities 284,649 275,080 264,715 252,192 237,042 219,480 201,044

Residential Loans 625,980 611,801 592,547 563,991 510,149 432,001 376,180

Commercial Mortgages 365,879 342,567 319,258 295,714 270,377 247,222 224,094

Consumer Loans 262,678 251,508 240,328 229,120 217,908 206,678 195,460

Business Loans 104,970 97,971 90,955 83,934 76,888 69,872 62,877

Total Interest Income 1,876,099 1,794,244 1,706,494 1,607,016 1,477,804 1,324,065 1,191,841

Deposit Expense 728,224 679,052 603,002 544,298 468,162 446,370 381,753

Borrowing Expense 595,110 527,611 456,727 383,032 299,256 213,908 152,459

Total Interest Expense 1,323,334 1,206,664 1,059,728 927,331 767,418 660,278 534,212

Net Interest Income 552,765 587,581 646,766 679,685 710,385 663,787 657,628

Provision for Losses - - - - - - -

Servicing Hedges Receive - - - - - - -

Servicing Hedges Pay 32,000 32,000 32,000 32,000 32,000 32,000 32,000

Non interest Income - - - - - - -

Total Non Interest Income 32,000 32,000 32,000 32,000 32,000 32,000 32,000

Total Non Interest Expense 573,860 573,860 573,860 573,860 573,860 573,860 573,860

Income before taxes 10,905 45,721 104,906 137,825 168,525 121,927 115,768

Income Taxes 4,144 17,374 39,864 52,374 64,040 46,332 43,992

Net Income Before Extraordinary Items 6,761 28,347 65,042 85,452 104,486 75,595 71,776

Extraordinary Items 127,390 140,619 163,110 175,619 187,285 169,578 167,238

Net Income 134,151 168,966 228,151 261,071 291,771 245,172 239,014

% Change

Interest Income 17% 12% 6% -8% -18% -26%

Interest Expense 43% 30% 14% -17% -29% -42%

Net Interest Income -19% -14% -5% 5% -2% -3%

-20.00%

-15.00%

-10.00%

-5.00%

0.00%

5.00%

10.00%

-300 -200 -100 +100 +200 +300

Basis Points Rate Change (Parallel Shock)

Cha

nge

in N

II Dec-00

Jun-01

Dec-01

Limits

Limit Excess; Approved by ALCO

NII Sensitivity

Net Interest Income at Risk

23

NII Simulation Strengths

» Net interest Income simulation models seek to produce their results in a dynamic or forward-looking manner whereas market value and gap models produce their results statically.

» Since simulation models are both forward looking and are interactive, they require greater emphasis on assumptions and managerial behavior.

» Therefore, simulations are unique in that they help managers anticipate future events, perform assumption sensitivity analysis, and provide a means by which managers may test the effect of different external shocks and strategies on income.

24

NII Simulation Weaknesses

» The software, hardware, and personnel requirements necessary to run an ALM model are costly.

» Simulations depend on assumptions and data analyses that place strenuous demands on the operator. Therefore, the simulation results are only as good as the analyst operating the model.

» Simulation models bog managers down in oceans of detail.

» Since simulation solves problems by trial and error, a thorough examination of current risks can be clumsy, time consuming, and labor intensive.

» ALM models can be black boxes. The internal structure of models may not reflect the bank or thrift being modeled. In addition, econometric models and relationships may become invalid with time.

25

Standard Market Value Sensitivity Measures

Market Value of Portfolio Equity (MVPE)» The market value of assets minus the market value liabilities.

Duration: Generic Description of the sensitivity of a bond’s price to a change in yield.

» Macaulay Duration: The weighted average of the time periods over which cash flows accrue to bondholders (using the percentage of the cash flows as weights) which occur at each payment time as the weighting scheme.

» Modified Duration: Duration measure in which it is assumed that yield changes do not effect the expected cash flows.

» Effective Duration: Sensitivity measure in which recognition is given to the fact that yield changes may change the expected cash flows (correlated risks).

Convexity: The rate at which duration changes due to changes in interest rates.

26

Convexity

» Duration not constant over time

» Convexity adjusts for interest rate sensitivity -‘curvature’ of price/yield relationship

» Relevant for larger moves.

Price

Duration Actual Price

p*

Tangent Line at y*

y* Yield

27

Optionality: Behaviour Modelling

Where Contractual Terms May Be Varied By Custom or Implication

» Prepayment Due To Unscheduled, Part Or Full, Principle Repayments

» The Variability and Lack of Sensitivity of Non Maturity Liabilities in Terms of:

– Maturity

– Changes in Balance of Account

– Coupon or Interest Rate Repricing, or Rate Repricing Lag To Market Rates, Or The Rate Off-set Due To High Account Servicing Cost

» Call Options, Put Options

» Caps, Floors

» Changing Credit Card Balances

28

Option Adjusted Valuation

How Much Additional Risk am I really undertaking because of embedded optionality and how does it cost?» The option adjusted value (OAV) is the probability weighted market value of

all of the simulated income streams.

29

What is Option Adjusted Valuation?

» OAV is “beyond the option” in the sense that it is the expected value across a large number of possible outcomes rather than just one path.

» This market value is option adjusted because it incorporates market volatility and therefore, the changing market value of embedded options.

» Static valuation is the outcome of a single scenario where many are possible!!

30

Term Structure Modeling

What is likely to happen to interest rates?» Stochastic generation of interest rates allows the user to effectively forecast

the future shape and behavior of the term structure of interest rates.

-2.0% -1.5% -1.0% -0.5% 0.0% 0.5% 1.0% 1.5%-10%

0%

10%

20%

30%

40%

50%

60%

70%

Actual refinancing vs. S-like curve: 5/1 ARMs

Observations

Model

Refi Spread

Refi CPR

31

Term Structure Modeling

-2.00%

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

0 4 8 12 16 20 24 72 120

168

216

264

312

360

32

Effective Duration

Effective Duration Recognizes that Changes in Yield will Change the Cash Flows of Instruments with Embedded Options

Price

Duration Actual Price

Positive Convexity

Negative Convexity

Yield

Δi Δi

V0 = initial price

V- = price if yield changes by -y

V+ = price if yield changes by +yΔi = change in yield

De =V- - V+

2(V0)(Δi )

33

Effective Convexity

Effective Convexity Recognizes that Changes in Yield will Change the Cash Flows of Instruments with Embedded Options

V0 = initial price

V- = price if yield changes by -y

V+ = price if yield changes by +yΔi = change in yield

Ce =V- - 2 * V0 + V+

V0 * (Δi) 2 * 100

EVEExposures

-60.00%

-50.00%

-40.00%

-30.00%

-20.00%

-10.00%

0.00%

10.00%

-300 -200 -100 +100 +200 +300

Parallel Change in Rates

% C

hang

e in

EV

E

Dec-00

Jun-01

Dec-01

Limits

35

Duration Strengths / Weaknesses

Strengths

» Shows magnitude and timing of cash flows.

» Provides a single exposure number to manage against

» Identifies which transactions drive exposures.

» Easily accommodates unusual security types and correlated interest rate risks.

» Quantifies more than one target account at a time

Weaknesses

» Assumes all interest rates change in equal amounts

» Only effective for small rate changes (convexity).

» Does not capture future business volumes, managerial decisions...etc.

VaR is maximum amount of money that may be lost on a portfolio over a given period of time, with a level of confidence

VaRWhat is Value at Risk (VaR)?

Methods:

Historical simulation

Variance-Covariance approach

Monte-Carlo simulation

ProfitLoss

Confidence Level 99%

VaR Strengths and Weaknesses

» Provides “common” denominator upon which to manage risk

» Attaches probability to magnitude of loss

» Allows for decomposition of risks

» Provides “common” denominator upon which to manage risk

» Attaches probability to magnitude of loss

» Allows for decomposition of risks

» Susceptible to assumptions» Provides “likely” picture, but not

extreme event results» Computational and resource

requirements can be high

» Susceptible to assumptions» Provides “likely” picture, but not

extreme event results» Computational and resource

requirements can be high

Strengths Weaknesses

Quarterly Variance

3.1%

15.3%

11.7%

0.5%

0.0%

69.4%

.

Semi-Annual Variance

2.5%

11.2%

0.5%0.0%6.1%

79.8%

Interest Rates Prepayment Error Deposits Retention

Volatility Assumption Mortgage Spread COFI Rates

Risk Decomposition

Monthly Variance

3.1%

16.6%

0.4%

28.5%

0.1%

51.3%

Quarterly Variance

13.60%

68.62%

17.77%

Monthly Variance10.85%

81.60%

7.55%

Semi-Annual Variance

15.87%

57.39%

26.74%

Short Rate Curve Slope Mixed Effect

Risk Decomposition

40

What is EAR?

Earnings at risk (EAR) is the maximum decline in earnings that can occur over a given period of time, with a level of confidence.

41

Target Account Score Card

1 is best, 3 is least

Maturity Gap Simulation

Duration Gap

1. Risk Measurement Accuracy 3 2 12. Risk in Several Target Accounts 3/2 3/2 13. Flexible Asset/Liability Choices 3 2 14. Comprehensive Treatment of Securities 3 2 15. Correlated Risks 3 2 16. Ability to Hedge Incrementally 3 2 17. Risk of to be Booked Positions 3/2 1 3/28. Risk Measurement of Individual Accounts 3/2 3/2 19. Flexible Display of Results 3 1 2

10. Reveal Assumptions Made X X X11. Distinction Between Book and Market Values X X X

Score Card on ALM Tools

Source: Measuring and Managing Interest Rate Risk: A Guide to Asset/Liability Models Used in Banks and Thrifts

Morgan Stanley Fixed Income Research, October 1984

42

Ranking ALM Tools as the Basis for Decision Making

Target Accounts: Proxies for measuring and controlling the tradeoff between risk and return» Market Value of Portfolio Equity

» Net Interest Income

Minimizing risk in one category causes increased risk in one or the other category!

43

Possible Interest Rate Risk Strategies

Sensitivity Type: Earnings or Cash Flows Stock Price or Market Value1. Liability Sensitive Decreases Falls Drastically2. Fixed Earnings Fixed Falls3. "Hybrid" Bank Small Increase Small Decrease4. Stable Stock Price Increases Stable5. Asset Sensitive Large Increase Small Increase

Effects of a Rise in Interest Rates

Safety Zone

Source: Financial Risk Management in Banking

Uyemura, ©1993, Bank Administration Institute Foundation

Variety of Metrics Used to Quantify Risk By Exposure Type

13%

38%

13%

13%

13%

88%

100%

63%

88%

88%

88%

0% 20% 40% 60% 80% 100%

Management ActionTriggers

Stop Loss Limits

VaR

Net Interest IncomeSimulation

Convexity

Duration

Yes No

n = 8

45

How Banks Quantify IRR – Advanced Analytics

» 94% of a total population of 16 banks calculate and report NII exposure using deterministic rather than stochastic models. Therefore, minority of industry participants use stochastic income modeling despite their availability through common ALM systems.

– Most management teams do not perceive a favorable cost/benefit to stochastic income modeling

– Limited regulatory attention

– Many industry participants reported longer duration assets with embedded optionality – thereby limiting the usefulness of stochastic modeling

» 3 of 16 institutions calculate NII exposure using stochastic methods for internal comparative purposes only (results not formally reported).– Option adjusted EaR

– Multi-factor EAR

– EaR hedge Analysis

» 14 of 15 who do not use stochastic interest rate modeling perform non-parallel interest rate shocks.

» Many banks use deterministic NII modeling to satisfy regulatory requirements.

» VaR limit and compliance appears to be more prevalent amongst “market value” focused firms and are not common with “earnings focused” ones.

46

THE EXPANDING FRONTIER OF ALM

Current Environment

Lessons Learned Current Challenges

Need for effective firm-wide risk identification and analysis.

Review and update risk management policies, practices and governance structures

Improvement in prospective and contingency measures

Establishing firm-wide risk tolerances

Consistent application of independent and rigorous valuation practices across the firm.

Price and Value are two distinct things

“Risk” is more complicated than “Price”

Pricing should emphasize a MTM discipline

Place reasonable prices on products within HFI banking books, not just AFS and trading positions

Develop ALM/BSM “independent” sources of pricing

Consider pricing in your stress-scenarios

Effective management of funding liquidity, capital and the balance sheet.

FTP charge for liquidity

Appropriate contingent liquidity risk management

Treasury functions aligned with businesses

Informative and responsive risk measurement and management reporting and practices.

Risk metrics based one adaptive assumptions

Different perspectives on risk exposures

Stress testing not severe enough

The industry and regulatory response to the market dislocations that began in 2007 have signaled renewed interest in ALM across numerous financial disciplines. The acknowledgment of industry weaknesses and an atmosphere of very strong regulatory reform has signaled the incentive for change.

• Measure & Consolidate BS Exposure

• Establish Centralized Reporting

• Leverage Risk Mgt and BS Efficiencies

• Balance & Communicate Accounting vs. Economic Risk

• Transfer Pricing

How Risk Management is Changing» Governance: Greater emphasis on ERM principles - Movement away from “silo” based

risk management and the linking risk to capital

» Risk Assessment: Asset/Liability management needs to be more prospective in order to identify risks sooner

» Risk Quantification and Aggregation:– More disciplined valuation practices across the firm

– Convergence of market and credit risk

– Proliferation of the Enterprise Risk Management Platform

– Stress Testing – more realistic fat tail events and more holistic practices

» Risk Monitoring and Reporting:– More responsive risk management reporting practices

– Wider range of risk metrics based on different underlying assumptions

» Risk Control and Optimization:– Effective management of funding, liquidity, capital, and capital management

» Transfer pricing

» Better Liquidity risk management practices

» More efficient capital management

» Risk adjusted performance measurement

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Traditional ALM Is Not Enough Anymore

» ALM is too often equated to IRR, and only IRR. It’s far more than measuring IRR (Earnings & EVE)

» The full scope about ALM is about the totality of the financial risk management of a bank. That means:- ALM = Governance + Risk Assessment + Risk Quantification + Monitoring

and Reporting + Risk Control and Optimization or ERM- Financial risks need to be modeled using instrument-level cash flows- Requires the joint modeling of financial risk across the taxonomy of risks

» Sound balance sheet management means always striving to maximize value creation and minimize value destruction» This requires a view across the taxonomy of risk types» This is an on-going process» Requires a good valuation discipline, not just an earnings focus

Traditional ALM – Interest Rate risk and

earnings/value scenario analysis

Phased Evolution

Modeling the earnings impact of:• Delinquency• Non-accrual• Default• Recovery

Modeling the credit capital of:• Current position inherent

risk• Pro-forma credit capital• ALLL forecasting using the

above two items

Modeling the transitions of credit:

Tying rating transitions to market spreads (CreditMetrics™ approach)

MTM (i.e., a “fair value” approach)

Instrument level pricing of credit-default products

Sensitivity analysis and reporting around current and forecasted credit spreads

CDO and CMBS pricing modules

Linking prepayment models and credit (i.e., hazard-rate) models at transaction level

Credit Risk and ALM

Phase 1

Phase 2

Phase 3

Phase 1

Phase 2

Phase 3

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Conclusion

“Banks that wish to remain competitive must keep up with the latest developments in risk measurement and management…One of the most important sound practices for a banking organization is the tying of risk exposure to capital…by more clearly defining risk exposures and identifying the causes and controls for their losses, bank management can more effectively integrate decisions about risk-taking into their strategic and tactical decision-making.”

- Governor Bies, U.S. Federal Reserve, March 29, 2006