Articles by kenli

LO 37.1: Describe the three lines of defense in the Basel model for operational risk governance.
The Basel Committee on Banking Supervision defines operational risk as the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. The committee states that the definition excludes strategic and reputational risks but includes legal risks. Operational risk is inherent in banking activities. Risks range from those arising from national disasters, such as hurricanes, to the risk of fraud. The committee intends to improve operational risk management throughout the banking system.
Sound operational risk management practices cover governance, the risk management environment, and the role of disclosure. Operational risk management must be fully integrated into the overall risk management processes of the bank.
The three common lines of defense employed by firms to control operational risks are: 1. Business line management. Business line management is the first line of defense.
Banks now, more than ever, have multiple lines of business, all with varying degrees of operational risk. Risks must be identified and managed within the various products, activities, and processes of the bank.
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Topic 37 Cross Reference to GARP Assigned Reading – Basel Committee on Banking Supervision
2. An independent operational risk management function. This is the second line of
defense and is discussed in the next section.
3. Independent reviews of operational risks and risk management. The review may
be conducted internally with personnel independent of the process under review or externally.
C o r po r a t e O pe r a t io n a l Ris k Fu n c t i o n (CORF)
The banks specific business lines monitor, measure, report, and manage operational and other risks. The corporate operational risk function (CORF), also known as the corporate operational risk management function, is a functionally independent group that complements the business lines risk management operations. The CORF is responsible for designing, implementing, and maintaining the banks operational risk framework. Responsibilities of the CORF may include: Measurement of operational risks. Establishing reporting processes for operational risks. Establishing risk committees to measure and monitor operational risks. Reporting operational risk issues to the board of directors. In general, the CORF must assess and challenge each business lines contributions to risk measurement, management, and reporting processes.
Larger, more complex banking institutions will typically have a more formalized approach to the implementation of the lines of defense against operational risks, including the implementation of the CORF. For example, a large bank may have a fully staffed group skilled specifically in operational risk management, while a smaller bank may simply fold operational risk management into the broader risk management function of the bank.
Pr in c ipl e s o f O pe r a t io n a l Ris k Ma n a g e me n t

LO 36.8: Com pare predatory lending and borrowing.
Predatory lending results in the borrower becoming worse off after the loan than before. This may happen because the rates are deceptively high, the appraisals are inflated allowing the borrower to extract equity and then cannot refinance, and prepayment penalties are extreme, steering borrowers unnecessarily to subprime products and similar ruses. Predatory lending may also include outright fraudulent activity in addition to deception.
Predatory borrowing is misrepresentation in the mortgage application from the borrower side. The temptation is driven by increasing housing prices whereby the borrower feels that he cannot catch up with housing prices. Therefore, lying on the mortgage application allows the borrower to the buy the house with the expectation that continued appreciation will allow a favorable refinancing. The fraud may be perpetrated by the buyer alone or in concert with lawyers, broker, and appraisers.
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Topic 36 Cross Reference to GARP Assigned Reading – Ashcroft & Schuermann
K e y C o n c e p t s
LO 36.1
The recent past has witnessed about 73% of subprime mortgages securitized.
LO 36.2
Frictions involve the borrower, originator, arranger, asset manager, investor, and rating agency. The frictions are based on adverse selection and moral hazard problems.
Ultimately, the lack of due diligence on the asset manager and arranger led to even looser underwriting standards. The credit rating agencies issued ratings that lacked this key information.
LO 36.3
Subprime mortgages are mainly hybrid arms (2/28 and 3/27) where the term denotes fixed and floating, respectively. Hence, the borrower retains the vast majority of the interest rate risk.
The capital structure of a pool places the safest securities on top (senior notes), junior securities in the middle (mezzanine) and riskiest on the bottom (equity).
Subordination, excess spread, and shifting interest provide protection for the senior tranches.
LO 36.4
Credit ratings are determined by the amount of collateralization in the structure. If the projected cash flows are insufficient to warrant a desired rating, the originator can supply additional enhancement.
LO 36.3
Credit ratings for ABSs are more complex than corporate ratings because of the underlying portfolio nature and correlation between assets, dependence on economic forecasts, and static nature of the collateral pool.
LO 36.6
Credit ratings are designed to rate through-the-cycle so that there are not excessive upgrades (downgrades) during housing booms (busts). However, changing required enhancements amplify the impact on housing markets by reducing credit in down markets and increasing credit in up markets for the lowest rated borrowers.
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Topic 36 Cross Reference to GARP Assigned Reading – Ashcroft & Schuermann
LO 36.7
Rating agencies collectively monitor approximately 10,000 mortgage pools. Its impractical to monitor each pool on a monthly basis in detail, so annual reviews are preferred.
LO 36.8
Predatory lending is when the borrowers welfare is reduced after undertaking the loan. The key characteristic is that the borrower has entered into an agreement with unfavorable terms. Predatory borrowing is when the borrower knowingly misrepresents his financial condition to secure a loan that he otherwise would not qualify for.
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Topic 36 Cross Reference to GARP Assigned Reading – Ashcroft & Schuermann
C o n c e p t C h e c k e r s
1.
2.
3.
4.
3.
Which of the following is not a friction in the subprime securitization market? A. Investor and rating agency. B. Servicer and mortgagor. C. Mortgagor and arranger. D. Asset manager and investor.
Which of the following frictions represents an adverse selection problem? A. Investor and mortgagor. B. Originator and arranger. C. Servicer and rating agency. D. Servicer and mortgagor.
Which of the following statements about subprime mortgages is true? Subprime mortgages: A. are typically fixed rate obligations. B. often use the 2/28 or 3/27 hybrid structure. C. force the lender to bear most of the interest rate risk. D. are simpler to analyze than corporate bonds.
Which of the following is true about predatory lending and predatory borrowing? A. Both underprovide credit. B. Both overprovide credit. C. Predatory lending underprovides credit and predatory borrowing overprovides
credit.
D. Predatory lending overprovides credit and predatory borrowing underprovides
credit.
Which of the following subprime characteristics provide direct protection for senior tranches? A. Subordination, excess spread, and shifting interest. B. Subordination, prepayments, and shifting interest. C. Overcollateralization, excess spread, and timing of losses. D. Overcollateralization, excess spread, and prepayments.
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Topic 36 Cross Reference to GARP Assigned Reading – Ashcroft & Schuermann
C o n c e p t C h e c k e r An s w e r s
1. C The mortgagor and arranger have no direct contact so there is no friction.
2. B The originator has better information about the quality of the borrowers so the arranger
is subject to an adverse selection problem. That is, if the originator keeps the high quality mortgages, the arranger will receive lemons.
3. B Most subprimes are 2/28 or 3/27 structures where the fixed component is for two or three
years. Hence, the remainder of the term (27 or 28 years) is variable and bears the majority of the interest rate risk.
4. B Predatory borrowing is when the borrower misrepresents themselves to obtain credit they
otherwise would be denied. Predatory lending is providing credit that is welfare decreasing and should not be provided.
5. A Subordination, excess spread, and shifting interest provide protection for senior tranches.
Overcollateralization also provides protection for senior tranches. Timing of losses impacts excess spreads. Prepayments can accelerate or decelerate the cash flows to senior tranches.
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S e l f -Te s t : C r e d i t R i s k M e a s u r e m e n t a n d M a n a g e m e n t
10 Questions: 30 M inutes
1.
2.
3.
A firm is experiencing financial difficulties. Using a contingent claims approach, which of the following best describes the valuation of their senior and subordinated debt? A. Both the senior debt and subordinated debt have positive exposures to debt
maturity, firm volatility, and interest rates (i.e., the debt value increases as these factors increase).
B. The senior debt has negative exposures to debt maturity, firm volatility, and
interest rates (i.e., the senior debt value decreases as these factors increase). The subordinated debt has positive exposures to debt maturity, firm volatility, and interest rates (i.e., the subordinated debt value increases as these factors increase).
C. The senior debt has positive exposures to debt maturity, firm volatility, and
interest rates (i.e., the senior debt value increases as these factors increase). The subordinated debt has negative exposures to debt maturity, firm volatility, and interest rates (i.e., the subordinated debt value decreases as these factors increase).
D. Both the senior debt and subordinated debt have negative exposures to debt
maturity, firm volatility, and interest rates (i.e., the debt value decreases as these factors increase).
Suppose a portfolio has a value of $ 1,000,000 with 50 independent credit positions. Each of the credits has a default probability of 2% and a recovery rate of 0%. The credit portfolio has a default correlation equal to 0. The number of defaults is binomially distributed and the 95th percentile of the number of defaults is 3. What is the credit value at risk at the 95% confidence level for this credit portfolio? A. $20,000. B. $40,000. C. $60,000. D. $980,000. Continuously increasing default probability (while holding default correlation constant) will most likely have what effect on the credit VaR of mezzanine and equity tranches? Equitv VaR Increase A. B. Increase C. Decrease D. Decrease
Mezzanine VaR Increase then decrease Decrease then increase Increase then decrease Decrease then increase
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Book 2 Self-Test: Credit Risk Measurement and Management
4.
5.
6 .
7.
Which of the following statements regarding counterparty risk and lending risk is correct? A. For an interest-rate swap, counterparty risk exists because default may occur at
the end of the contract term.
B. With counterparty risk, there is uncertainty as to which counterparty will have a
negative mark-to-market value.
C. Lending risk involves bilateral risks. D. With lending risk, the principal amount at risk is known with absolute certainty
at the outset.
Netting refers to the combining of cash flows from different contracts with a counterparty into a single net amount. This method of mitigating counterparty risk has enabled explosive growth in credit exposures. Which of the following statements is incorrect regarding the advantages and disadvantages of netting? A. Netted exposures can be volatile, which may result in difficulty in controlling
exposure.
B. Netting removes risks by executing a reverse position with a counterparty,
removing both default and operational risk, but not market risk.
C. Without netting, entities trading with insolvent or troubled counterparties
would be motivated to cease trading and terminate existing contracts.
D. By offsetting exposures with parties managing net positions only, netting reduces
risk and improves operational efficiency.
Counterparty Y is attempting to transfer posted collateral to another counterparty as collateral through a process of rehypothecation. Assuming that Counterparty X pledges collateral to Counterparty Y, and then Counterparty Y rehypothecates this collateral to Counterparty Z, what will happen if Counterparty Z defaults? A. Counterparty X will receive its original collateral back from Counterparty Z. B. Counterparty Y will have a liability to Counterparty X for not returning its
collateral.
C. Counterparty Y will profit from not receiving the collateral from Counterparty
Z given that a credit event has occurred.
D. Counterparty Y will accept a haircut on the value of the pledged collateral in
order to reclaim a portion of the collateral.
Teresa Harrison, a junior portfolio manager, is considering the purchase of super senior tranches for her client portfolios. The typical client is fairly conservative and concerned more with downside risk than upside potential. Harrison based her recommendation on the following observations:
Senior tranches have large attachment points and hence a low probability of Senior tranches have large attachment points and hence a low probability of credit losses.
Mezzanine tranches represent the first loss piece of the capital structure.
Synthetic CD Os have standardized tranche widths similar to index tranches.
How many of these observations support Harrisons view of tranches? A. 0. 1. B. C. 2. D. 3.
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Book 2 Self-Test: Credit Risk Measurement and Management
8.
9.
A portfolio consists of two bonds, Bonds A and B. The credit VaR for the portfolio is defined as the maximum loss due to defaults at a confidence level of 98% over a one-year horizon. The probability of joint default of the two bonds is 1.32%, and the default correlation is 33%. The bond value, default probability, and recovery rate are USD 1.2 million, 4%, and 60%, respectively for Bond A, and USD $800,000, 3%, and 35%, respectively for Bond B. What is the expected credit loss for the portfolio? A. $45,200. B. $15,820. C. $42,800. D. $26,400.
High Flying Hedge Fund will enter into a $100 million total return swap on the S&P 500 Index as the index receiver (i.e., total return receiver). The counterparty (i.e., total return payer) will receive 1-year LIBOR + 400bp. The contract will last two years and will exchange cash flows annually.

Current LIBOR = 3%. Current S&P 500 value = 2,000. S&P 500 in one year = 2,200. S&P 500 in two years = 1,760.
Given this information, what are the cash flows to High Flying in one year and in two years, respectively? Assume LIBOR remains flat. Year 1 Year
A. +3 million B. +3 million C. + 13 million D. + 13 million
2 Years
-13 million -27 million -13 million -27 million
10.
Five tranches of auto loan asset-backed securities (ABSs) are issued with a face value of $6,000,000 and pay an average coupon of 5.2 %. The value of the auto loans is $6,800,000, and they have an average interest rate of 5.4%. The fee for servicing the ABS is 0.2%. Which of the following credit enhancements are involved with this transaction? A. Excess spread. B. Margin step-up. C. Subordinating note classes. D. Overcollateralization.
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S e l f -Te s t A n s w e r s : C r e d i t R i s k M e a s u r e m e n t a n d M a n a g e m e n t
1. B
If a firm is in financial distress, the subordinated debt behaves more like equity and a call option. It will increase in value as time to maturity increases, volatility increases, and interest rates increase. The senior debt will have negative exposures to these factors.
If the firm is not in distress, both the senior debt and subordinated debt have negative exposures to these factors because the subordinated debt behaves more like senior debt than equity. In this case, choice D would be correct.
(See Topic 20)
2. B The loss given default is $60,000 [3 x ($1,000,000 / 50)]. The expected loss is equal to the
portfolio value times it and is $20,000 (0.02 x $1,000,000). The credit VaR is defined as the quantile of the credit loss less the expected loss of the portfolio. At the 95% confidence level, the credit VaR is equal to $40,000 ($60,000 minus the expected loss of $20,000).
(See Topic 22)
3. C
Increasing the probability of default decreases equity VaR as defaults are more likely, and the equity tranche will suffer writedowns. However, the writedowns are bounded by the thin level of subordination so the variation in losses becomes smaller. Mezzanine tranches behave more like senior bonds at low default levels (increasing VaR) but more like the equity tranche at higher default levels (decreasing VaR).
(See Topic 23)
4. B With counterparty risk, there is uncertainty regarding which counterparty will have a
negative MtM value. For an interest-rate swap, there is no counterparty risk at the end of the contract term because all payments required by the contract would have been made by then. With lending risk, only one party (unilateral) takes on risk. In addition, the principal amount at risk is known only with reasonable certainty at the outset because changes in interest rates, for example, will lead to some uncertainty.
(See Topic 24)
5. B
If an entity wishes to exit a less liquid OTC trade with one counterparty by entering into an offsetting position with another counterparty, the entity will remove market risk; however, it will be exposed to counterparty and operational risk. Netting removes these risks through executing a reverse position with the initial counterparty, removing both market and counterparty risk.
(See Topic 25)
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Book 2 Self-Test Answers: Credit Risk Measurement and Management
6. B
In rehypothecation, party X may pledge collateral to party Y and party Y may rehypothecate this collateral to party Z. If party Z defaults, then party Y will not only have a loss from not receiving the collateral from party Z, it will also have a liability to party X for not returning its collateral.
(See Topic 26)
7. B Only recommendation 1 is correct. Senior tranches have a low probability of default because their attachment points are much higher in the capital structure. Equity tranches represent the first loss position. Index tranches, not synthetic CDOs, have standardized tranche widths.
(See Topic 29)
8. A The joint expected credit loss is the sum of the two individual expected credit losses.
EL
= PD x exposure x LGD
ELgondA = $1 >200,000 x 0.04 x 0.40 = $19,200
ELfiondB = $800,000 x 0.05 x 0.65 = $26,000
Total EL = $45,200
Note that expected credit loss does not depend on the correlation between the bonds.
(See Topic 32)
9. B Over the next year, the S&P 500 Index will increase by 10%. Hence, the index receiver
(High Flying) will receive $10 million from the index payer and will pay $7 million (LIBOR = 3% + 400bp) to the counterparty. Therefore, the net cash flow will be +$3 million to High Flying.
Between years 1 and 2, the S&P 500 Index will drop 20%. Now, High Flying as the total return receiver must pay 20% to the counterparty in addition to the 7% floating rate. Hence, the total outflow from High Flying to the counterparty is $27 million.
(See Topic 34)
10. D This ABS is supported by overcollateralization because the value of the asset pool is greater
than the value of the securities. There is no excess spread involved because there is no difference between the cash inflows from the underlying assets and the cash outflows in the form of interest payments on the ABS issues.
(See Topic 35)
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F o r m u l a s
Topic 16
expected loss: PD x LGD x EAD
Topic 18
Credit Risk Measurement and Management
exposure at default: EAD = drawn amount + (limit – drawn amount) x loan equivalency factor p o r t f o l i o marginal risk contribution: (3j = ———– p o r t f o l i o
U
L
economic value added: EVA = (RARORAC Ke) x economic capital
risk-adjusted return on risk-adjusted capital:
RARORAC =
spread + fees EL cost of capital cost of operations
economic capital
defaulted]: ^
names
Topic 19
probability of default: PD^
where: PD = probability of default defaulted = number of issuer names that have defaulted in the applicable time horizon names = number of issuers k = time horizon
i=t+k
cumulative probability of default: p y ) c u m u l a t i v e _
_ i =
defaulted j t – – – – – – – – – – – – – – – – – – names
marginal probability of default: pDargina^ = PD c u m u l a t i v e
t+ k
PDjc u m u l a t i v e
annualized default rate: discrete: ADRt = 1 1/(1 PD]:c u m u l a t i v e
i
continuous: ADRt =
In 1 PDj:c u m u l a t i v e
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ln(I-) ln(V.\) -|iT
\
Book 2 Formulas
Merton model PD: PD = N
ffA Vt
where: In = the natural logarithm F = debt face value VA = firm asset value (market value of equity and net debt) 1 = expected return in the risky world 1 T = time to maturity remaining oA = volatility (standard deviation of asset values) N = cumulated normal distribution operator
distance to default: DtD
ln(VA) ln(F) +
‘risky
M V
/

“other payouts”
\
/
In V In F
A
Altmans Z-score: Z = 1.21×1 + 1.40×2 + 3.30×3 + 0.6×4 + 0.999×5
where: x1 = working capital / total assets x2 = accrued capital reserves / total assets x3 = EBIT / total assets x4 = equity market value / face value of term debt x5 = sales / total assets TV: LOGIT model: LOGIT(Tq) = log— – 1 TV:
Topic 20
credit spread =
1
(cid:31)
where: (T – t) = remaining maturity = current value of debt D F = face value of debt = risk-free rate
r
f
vulnerable option = [(1 PD) x c] + (PD x RR x c)
= value of the option without default
where: c PD = probability of default RR = recovery rate
Topic 21
cumulative PD: 1 e
default probability: \ T RR 1 RR
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Book 2 Formulas
Topic 22
correlation with default probabilities: p12
7ti2 – ^ 2
Topic 27
7n + n (n -l)p
netting factor = where: n = number of exposures p = average correlation
Topic 29
risk-neutral default probability = liquidity premium + default risk premium +
real-world default probability
cumulative default probability: F(u) = 1 exp
spread recovery 1 recovery
x u
number of defaults = n
X% recovery / 1 recovery /
Topic 30
m
credit value adjustment: CVA = LGD x ^ x E E (q ) x PD (t^ j, q )
i= l
where: LGD = loss given default or how much of the exposure one expects to lose in the event
of a counterparty default; equal to 1 minus the recovery rate (1 RR)
EE PD
= discount expected exposure for future dates = marginal default probability
CVA as a spread:
CVA(t,T)
CDS p r e m i u m (t>T)
X CDSx EPE
where: CDSpremium(t, T) = unit premium value of a credit default swap XCDS
= CDS premium at maturity date T; this amount can be thought of as
a credit spread
EPE
= expected positive exposure that is the average of the expected
exposure over a preset time period, typically from the present to the maturity date of the transaction
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Book 2 Formulas
bilateral credit value adjustment: BCVA = CVA + DVA
CVA = +L G D C x
EE(t;) x PDC (t;_i, t;)
m
i= l m
DVA = LGDj x NEE(t;) x PDj (tH , t;)
i= l
where: NEE = negative expected exposure (EE from the counterpartys perspective)
BCVA as spread:
BCVA(t,T)
C D S premium (* T )
X g DS x EPE – X f DS x ENE
p r \ r where : X j 3 = the institution5 s own CDS spread ENE = expected negative exposure (the opposite of EPE)
Topic 32
r
N
loan portfolio expected loss: EL = X PD i x EAD; x LGD}
i= l
N
deriatives portfolio expected loss: EL = Z PD i x (EPEj x a ) x LGDj
i= i
Topic 35 weighted average life (WAL): WAL =
(a / 365) x PF(t)
constant prepayment rate: CPR = 1 (1SM M )12
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U s in g t h e C u m u l a t iv e Z-Ta b l e
Probability Example
Assume that the annual earnings per share (EPS) for a large sample of firms is normally distributed with a mean of $5.00 and a standard deviation of $1.50. What is the approximate probability of an observed EPS value falling between $3.00 and $7.25?
If EPS = x = $7.25, then z = (x – p)/a = ($7.25 – $5.00)/$1.50 = +1.50
If EPS = x = $3.00, then z = (x – p)/a = ($3.00 – $5.00)/$1.50 = -1.33
For z-value of 1.50: Use the row headed 1.5 and the column headed 0 to find the value 0.9332. This represents the area under the curve to the left of the critical value 1.50.
For z-value of1.33: Use the row headed 1.3 and the column headed 3 to find the value 0.9082. This represents the area under the curve to the left of the critical value +1.33. The area to the left o f1.33 is 1 0.9082 = 0.0918.
The area between these critical values is 0.9332 0.0918 = 0.8414, or 84.14%.
Hypothesis Testing One-Tailed Test Example
A sample of a stocks returns on 36 non-consecutive days results in a mean return of 2.0%. Assume the population standard deviation is 20.0%. Can we say with 95% confidence that the mean return is greater than 0%?
H q: p < 0.0%, Ha : p > 0.0%. The test statistic = ^-statistic = = (2.0 – 0.0) / ( 20.0 / 6) = 0.60.
The significance level = 1.0 0.95 = 0.05, or 5%.
Since this is a one-tailed test with an alpha of 0.05, we need to find the value 0.95 in the cumulative stable. The closest value is 0.9505, with a corresponding critical .z-value of 1.65. Since the test statistic is less than the critical value, we fail to reject H Q.
Hypothesis Testing Two-Tailed Test Example
Using the same assumptions as before, suppose that the analyst now wants to determine if he can say with 99% confidence that the stocks return is not equal to 0.0%.
H q: p = 0.0%, Ha : p ^ 0.0%. The test statistic (.z-value) = (2.0 0.0) / (20.0 / 6) = 0.60. The significance level = 1.0 0.99 = 0.01, or 1%.
Since this is a two-tailed test with an alpha of 0.01, there is a 0.005 rejection region in both tails. Thus, we need to find the value 0.995 (1.0 0.005) in the table. The closest value is 0.9951, which corresponds to a critical .z-value of 2.58. Since the test statistic is less than the critical value, we fail to reject H Q and conclude that the stocks return equals 0.0%.
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C u m u l a t iv e Ta b l e P(Z < z) = N(z) for z > 0 P(Z < -z) = 1 - N(z) z 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3 0 0.5000 0.5398 0.5793 0.6179 0.6554 0.6915 0.7257 0.7580 0.7881 0.8159 0.8413 0.8643 0.8849 0.9032 0.9192 0.9332 0.9452 0.9554 0.9641 0.9713 0.9772 0.9821 0.9861 0.9893 0.9918 0.9938 0.9953 0.9965 0.9974 0.9981 0.01 0.5040 0.5438 0.5832 0.6217 0.6591 0.6950 0.7291 0.7611 0.7910 0.8186 0.8438 0.8665 0.8869 0.9049 0.9207 0.9345 0.9463 0.9564 0.9649 0.9719 0.9778 0.9826 0.9864 0.9896 0.9920 0.994 0.9955 0.9966 0.9975 0.9982 0.02 0.5080 0.5478 0.5871 0.6255 0.6628 0.6985 0.7324 0.7642 0.7939 0.8212 0.8461 0.8686 0.8888 0.9066 0.9222 0.9357 0.9474 0.9573 0.9656 0.9726 0.9783 0.983 0.9868 0.9898 0.9922 0.9941 0.9956 0.9967 0.9976 0.9982 0.03 0.5120 0.5517 0.5910 0.6293 0.6664 0.7019 0.7357 0.7673 0.7967 0.8238 0.8485 0.8708 0.8907 0.9082 0.9236 0.937 0.9484 0.9582 0.9664 0.9732 0.9788 0.9834 0.9871 0.9901 0.9925 0.9943 0.9957 0.9968 0.9977 0.9983 0.04 0.5160 0.5557 0.5948 0.6331 0.6700 0.7054 0.7389 0.7704 0.7995 0.8264 0.8508 0.8729 0.8925 0.9099 0.9251 0.9382 0.9495 0.9591 0.9671 0.9738 0.9793 0.9838 0.9875 0.9904 0.9927 0.9945 0.9959 0.9969 0.9977 0.9984 0.05 0.5199 0.5596 0.5987 0.6368 0.6736 0.7088 0.7422 0.7734 0.8023 0.8289 0.8531 0.8749 0.8944 0.9115 0.9265 0.9394 0.9505 0.9599 0.9678 0.9744 0.9798 0.9842 0.9878 0.9906 0.9929 0.9946 0.9960 0.9970 0.9978 0.9984 0.06 0.5239 0.5636 0.6026 0.6406 0.6772 0.7123 0.7454 0.7764 0.8051 0.8315 0.8554 0.8770 0.8962 0.9131 0.9279 0.9406 0.9515 0.9608 0.9686 0.9750 0.9803 0.9846 0.9881 0.9909 0.9931 0.9948 0.9961 0.9971 0.9979 0.9985 0.07 0.5279 0.5675 0.6064 0.6443 0.6808 0.7157 0.7486 0.7794 0.8078 0.8340 0.8577 0.8790 0.8980 0.9147 0.9292 0.9418 0.9525 0.9616 0.9693 0.9756 0.9808 0.985 0.9884 0.9911 0.9932 0.9949 0.9962 0.9972 0.9979 0.9985 0.08 0.5319 0.5714 0.6103 0.6480 0.6844 0.7190 0.7517 0.7823 0.8106 0.8365 0.8599 0.8810 0.8997 0.9162 0.9306 0.9429 0.9535 0.9625 0.9699 0.9761 0.9812 0.9854 0.9887 0.9913 0.9934 0.9951 0.9963 0.9973 0.9980 0.9986 0.09 0.5359 0.5753 0.6141 0.6517 0.6879 0.7224 0.7549 0.7852 0.8133 0.8389 0.8621 0.8830 0.9015 0.9177 0.9319 0.9441 0.9545 0.9633 0.9706 0.9767 0.9817 0.9857 0.989 0.9916 0.9936 0.9952 0.9964 0.9974 0.9981 0.9986 0.9987 0.9987 0.9987 0.9988 0.9988 0.9989 0.9989 0.9989 0.9990 0.9990 2018 Kaplan, Inc. Page 321 A l t e r n a t iv e .Z-Ta b l e P(Z < z) = N(z) for z > 0 P(Z < -z) = 1 - N(z) z 0.0 0.1 0.2 0.3 0.4 0.3 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3.0 0.00 0.0000 0.0398 0.0793 0.1179 0.1554 0.1915 0.2257 0.2580 0.2881 0.3159 0.3413 0.3643 0.3849 0.4032 0.4192 0.4332 0.4452 0.4554 0.4641 0.4713 0.4772 0.4821 0.4861 0.4893 0.4918 0.4939 0.4953 0.4965 0.4974 0.4981 0.01 0.0040 0.0438 0.0832 0.1217 0.1591 0.1950 0.2291 0.2611 0.2910 0.3186 0.3438 0.3665 0.3869 0.4049 0.4207 0.4345 0.4463 0.4564 0.4649 0.4719 0.4778 0.4826 0.4864 0.4896 0.4920 0.4940 0.4955 0.4966 0.4975 0.4982 0.02 0.0080 0.0478 0.0871 0.1255 0.1628 0.1985 0.2324 0.2642 0.2939 0.3212 0.3461 0.3686 0.3888 0.4066 0.4222 0.4357 0.4474 0.4573 0.4656 0.4726 0.4783 0.4830 0.4868 0.4898 0.4922 0.4941 0.4956 0.4967 0.4976 0.4982 0.03 0.0120 0.0517 0.0910 0.1293 0.1664 0.2019 0.2357 0.2673 0.2967 0.3238 0.3485 0.3708 0.3907 0.4082 0.4236 0.4370 0.4484 0.4582 0.4664 0.4732 0.4788 0.4834 0.4871 0.4901 0.4925 0.4943 0.4957 0.4968 0.4977 0.4983 0.04 0.0160 0.0557 0.0948 0.1331 0.1700 0.2054 0.2389 0.2704 0.2995 0.3264 0.3508 0.3729 0.3925 0.4099 0.4251 0.4382 0.4495 0.4591 0.4671 0.4738 0.4793 0.4838 0.4875 0.4904 0.4927 0.4945 0.4959 0.4969 0.4977 0.4984 0.05 0.0199 0.0596 0.0987 0.1368 0.1736 0.2088 0.2422 0.2734 0.3023 0.3289 0.3531 0.3749 0.3944 0.4115 0.4265 0.4394 0.4505 0.4599 0.4678 0.4744 0.4798 0.4842 0.4878 0.4906 0.4929 0.4946 0.4960 0.4970 0.4978 0.4984 0.06 0.0239 0.0636 0.1026 0.1406 0.1772 0.2123 0.2454 0.2764 0.3051 0.3315 0.3554 0.3770 0.3962 0.4131 0.4279 0.4406 0.4515 0.4608 0.4686 0.4750 0.4803 0.4846 0.4881 0.4909 0.4931 0.4948 0.4961 0.4971 0.4979 0.4985 0.07 0.0279 0.0675 0.1064 0.1443 0.1808 0.2157 0.2486 0.2794 0.3078 0.3340 0.3577 0.3790 0.3980 0.4147 0.4292 0.4418 0.4525 0.4616 0.4693 0.4756 0.4808 0.4850 0.4884 0.4911 0.4932 0.4949 0.4962 0.4972 0.4979 0.4985 0.08 0.0319 0.0714 0.1103 0.1480 0.1844 0.2190 0.2517 0.2823 0.3106 0.3356 0.3599 0.3810 0.3997 0.4162 0.4306 0.4429 0.4535 0.4625 0.4699 0.4761 0.4812 0.4854 0.4887 0.4913 0.4934 0.4951 0.4963 0.4973 0.4980 0.4986 0.09 0.0359 0.0753 0.1141 0.1517 0.1879 0.2224 0.2549 0.2852 0.3133 0.3389 0.3621 0.3830 0.4015 0.4177 0.4319 0.4441 0.4545 0.4633 0.4706 0.4767 0.4817 0.4857 0.4890 0.4916 0.4936 0.4952 0.4964 0.4974 0.4981 0.4986 0.4987 0.4987 0.4987 0.4988 0.4988 0.4989 0.4989 0.4989 0.4990 0.4990 Page 322 2018 Kaplan, Inc. 2018 Kaplan, Inc. Page 323 collateralized debt obligation 213, 273 collateralized loan obligation 274 collateralized mortgage obligations 122 collateral management 161 collateral volatility 184 concentration risk 31 constant prepayment rate 293 consumer credit analyst 15 Consumer Financial Protection Act 256 corporate credit analyst 16 corporate credit risk 255 counterparty credit analyst 16 counterparty risk 143, 242 covered bonds 122 credit 1 credit analysts at rating agencies 16 credit bureau scores 256 credit card debt 289 credit crunch 275, 296 credit default put 80 credit default swap 81, 144, 210, 270 credit derivatives 269 credit enhancement 124, 287 credit events 80 credit exposure 146 credit exposure metrics 173 CreditGrades 208 credit-linked note 272 CreditMetrics 76 credit migration 146 credit modeling analyst 16 CreditPortfolioView 79 credit quality 162 credit rating agencies 127, 282, 296 credit ratings 28 credit risk 1, 28, 254 CreditRisk+ 75 credit risk mitigation 267 credit risk model 31 credit scoring models 256 credit spread curve 211 credit support amount 162 credit support annex (CSA) 161 credit value adjustment (CVA) 148, 200, 219, 243 credit value at risk 109 cross-product netting 147 cumulative accuracy profile 258 bility to repay 256 absolute prepayment speed 289 acceleration clause 154 accuracy rati o 258 additional termination events 156 adverse selection 200, 302 Altmans Z-score 45 amortizing structure 284 annualized default rate 41 annual report 22 asset-backed credit-linked notes 272 asset-backed securities 123 asset valuation risk 255 asset value correlation 31 auditors report 22 auto loans 289 A a ank credit function 268 bank examiners 16 bank failure 9 bank insolvency 9 Bernoulli trial 92 bifurcations 200 bilateral CVA 224, 246 bilateral netting 155 binomial distribution 92 bond insurance 267 break clause 157 business risks 254 B b alibration 46 canonical correlation method 52 capital value adjustment (KVA) 201 cash flow simulation model 52 cash waterfall 283 central counterparty (CCP) 148, 195 close-out 147 close-out clauses 155 close-out netting 153 cluster analysis 49 collateral agreements 163 collateral disputes 163 collateralization 147, 148, 161, 267 c c In d e x fixed-income analysts 16 foreign exchange forwards 144 foreign exchange risk 168 funding liquidity risk 167 funding value adjustment (FVA) 200 G Geske compound option model 70 aircut 164, 165 hazard rate 93 hazard rate curves 97 hedging 148 heuristic methods 53 hierarchical clustering 49 high-quality counterparties 147 historical data approach 207 H h mplied correlation 135 incremental CVA 222 independent amount 162 index tranches 212 initial margin 162,164,186 interest-rate risks 255 internal credit enhancement 124 investment selection 17 ISDA Master Agreement 153 i-spread 90 issuer 281 I i MV model 78, 208 K K egal and operational efficiency 200 lending risk 143 linear discriminant analysis 45 liquidity 200 liquidity premium 206 liquidity risk 29, 167 loan syndication 267 loan-to-value (LTV) ratio 254, 257 logistic regression models 48 LOGIT model 48 loss coverage ratio 306 loss curve 289 loss given default 8, 29, 74, 146 loss mutualization 200 L l cumulative probability of default 41, 205 current exposure 242 custodian 282 customer relationship cycle 259 cutoff scores 46, 257 D debt service coverage ratio 290 debt-to-income ratio 257 debt value adjustment (DVA) 224, 248 decision support system 54 default correlation 31 default management 200 default probability 146 default ratio 289 default risk 28, 29, 168 default risk premium 206 delinquency ratio 289 delivery squeeze 210 derivative product company (DPC) 194 derivatives players 145 distance to default 44, 208 divisive clustering 50 conomic capital 32 economic value added 33 effective EE 175 effective EPE 175 eigenvalue 50 equity-based approaches 208 equity piece 283 equity tranche 123, 283, 304 excess spread 124, 285, 288, 304 expected exposure 173, 184, 243 expected loss 8, 30, 245 expected mark to market 173 expected positive exposure 174, 243 experts-based approach 39 expert system 53 exponential distribution 93 exposure at default 8, 30 exposure risk 28, 30 external credit enhancement 124 E e actor analysis 51 FICO score 257 financial guarantor 282, 286 financial obligation 2 first-loss piece 283 first-to-default put 271 F f Book 2 Index Page 324 2018 Kaplan, Inc. Book 2 Index ualified mortgages 256 qualitative credit analysis techniques 4 qualitative skills 21 quantitative credit analysis techniques 5 quantitative skills 21 Q q ating agency 17 real-world default probabilities 206 reassignment 267 recovery 146 recovery rate 209 recovery risk 28, 29 recovery swaps 209 reduced form model 43 rehypothecation 165 remargin period 183,186 replacement cost 146 repos 144 reputation risks 254 research skills 21 reset agreement 156 retail banking 254 retail credit risk 255 revolving structures 285 right-way risk 231 risk-adjusted return on capital 33 risk-adjusted return on risk-adjusted capital 33 risk-based pricing 260 RiskCalc model 46 risk management 17 risk-neutral approach 208 risk-neutral default probabilities 206 risk-neutral parameter 186 rounding 164, 165, 186 R r primary research 17 principal component analysis 50 probability of default 29, 40, 74 procyclicality 200 Public Securities Association 293 put-call parity 67 corecard 258 secondary research 17 securities financing transactions 144 securitization 128, 265, 281 senior debt 71 senior tranches 123 settlement risk 2 shadow banking system 296 shifting interest 304 s s arginal CVA 222 marginal probability of default 41, 205 marginal VaR 32 margin step-up 288 margin value adjustment (MVA) 201 market risk 167 marking to market 146, 267 master trust structure 285 maximum PFE 174 MBS performance tools 290 Merton model 44, 63, 208 mezzanine tranche 124 migration matrix 40 migration risk 29 minimum transfer amount 164, 165, 186 monoline insurance company 194 monthly payment rate 289 moral hazard 200, 301 mortgage credit assessment 257 mortgage pass-through securities 122 multilateral netting 155,199 M m ame lending 4 negative expected exposure 248 negative exposure 175 netting 148, 181, 267 netting effectiveness 156 netting factor 182 neural network 54 novation 196 numerical approach 39, 53 N n ne-way CSA 166 operational risk 167, 254 originate-to-distribute model 265, 268 originator 127, 273, 281 OTC derivatives 144 overcollateralization 124, 164, 283, 288 o o ayment netting 153 peak exposure 242 performance triggers 304 Poisson random variable 93 pooled model 257 pool insurance 288 portfolio credit VaR 114 potential future exposure 173, 177, 184 predatory borrowing 306 predatory lending 306 P p 2018 Kaplan, Inc. Page 325 nderwriter 127 unexpected loss 30 unilateral CVA 246 U u aluation agent 162 value at risk 31, 176 varimax method 52 Vasicek model 72 vulnerable option 82 V v alkaway feature 147,157 waterfall structure 124 weighted average coupon 291 weighted average life 292 weighted average maturity 291 wrong-way risk 179, 231, 243 w w ield spread 90 Y y Z-score cut-off 46 z-spread 90 Book 2 Index single-factor model 111 single monthly mortality (SMM) 293 single-tranche CDO 275 sovereign risk ratings 4 special purpose vehicle 193, 273, 281, 284 spread01 91 spread conventions 90 spread risk 29, 100 statistical-based classification 39 stressed CVA 247 stressed expected loss 245 structural approach 43 structured credit products 123 structured finance securities 213 structured investment vehicles 266 structuring agent 282 subordinate debt 71 subordinating note classes 288 subordination 304 substitution 165 super-senior tranche 212 synthetic CDO 213, 275 systemically important financial institutions (SIFIs) 193 termination 267 termination features 156 threshold 162, 164, 186 total return swap 81, 272 trade compression 157 tranches 273, 283 transparency 199 true sale 281 trustee 282 two-way CSA 166 Page 326 2018 Kaplan, Inc. Notes Notes Notes R e q u i r e d D i s c l a i m e r s : C F A I n s t i t u t e d o e s n o t e n d o r s e , p r o m o t e , o r w a r r a n t t h e a c c u r a c y o r q u a l i t y o f t h e p r o d u c t s o r s e r v i c e s o f f e r e d b y K a p l a n . C F A I n s t i t u t e , C F A , a n d C h a r t e r e d F i n a n c i a l A n a ly s t a r e t r a d e m a r k s o w n e d b y C F A I n s t i t u t e . C e r t i f i e d F i n a n c i a l P l a n n e r B o a r d o f S t a n d a r d s I n c . o w n s t h e c e r t i f i c a t i o n m a r k s C F P , C E R T I F I E D F I N A N C I A L P L A N N E R , a n d f e d e r a l l y r e g i s t e r e d C F P ( w it h f l a m e d e s i g n ) i n t h e U . S . , w h i c h i t a w a r d s t o i n d i v i d u a l s w h o s u c c e s s f u l l y c o m p l e t e i n i t i a l a n d o n g o i n g c e r t i f i c a t i o n r e q u i r e m e n t s . K a p l a n d o e s n o t c e r t i f y i n d i v i d u a l s t o u s e t h e C F P , C E R T I F I E D F I N A N C I A L P L A N N E R 1" , a n d C F P ( w it h f l a m e d e s i g n ) c e r t i f i c a t i o n m a r k s . C F P c e r t i f i c a t i o n is g r a n t e d o n l y b y C e r t i f i e d F i n a n c i a l P l a n n e r B o a r d o f S t a n d a r d s I n c . t o t h o s e p e r s o n s w h o , i n a d d i t i o n t o c o m p l e t i n g a n e d u c a t i o n a l r e q u i r e m e n t s u c h a s t h i s C F P B o a r d - R e g i s t e r e d P r o g r a m , h a v e m e t i t s e t h i c s , e x p e r i e n c e , a n d e x a m i n a t i o n r e q u i r e m e n t s . K a p l a n i s a r e v ie w c o u r s e p r o v i d e r f o r t h e C F P C e r t i f i c a t i o n E x a m i n a t i o n a d m i n i s t e r e d b y C e r t i f i e d F i n a n c i a l P l a n n e r B o a r d o f S t a n d a r d s I n c . C F P B o a r d d o e s n o t e n d o r s e a n y r e v ie w c o u r s e o r r e c e i v e f i n a n c i a l r e m u n e r a t i o n f r o m r e v ie w c o u r s e p r o v i d e r s . G A R P d o e s n o t e n d o r s e , p r o m o t e , r e v ie w , o r w a r r a n t t h e a c c u r a c y o f t h e p r o d u c t s o r s e r v i c e s o f f e r e d b y K a p l a n o f F R M r e l a t e d i n f o r m a t i o n , n o r d o e s i t e n d o r s e a n y p a s s r a t e s c l a i m e d b y t h e p r o v i d e r . F u r t h e r , G A R P i s n o t r e s p o n s i b l e f o r a n y f e e s o r c o s t s p a i d b y t h e u s e r t o K a p l a n , n o r is G A R P r e s p o n s i b l e f o r a n y f e e s o r c o s t s o f a n y p e r s o n o r e n t i t y p r o v i d i n g a n y s e r v i c e s t o K a p l a n . F R M , G A R P , a n d G l o b a l A s s o c i a t i o n o f R i s k P r o f e s s i o n a l s a r e t r a d e m a r k s o w n e d b y t h e G l o b a l A s s o c i a t i o n o f R i s k P r o f e s s i o n a l s , I n c . C A I A A d o e s n o t e n d o r s e , p r o m o t e , r e v ie w o r w a r r a n t t h e a c c u r a c y o f t h e p r o d u c t s o r s e r v i c e s o f f e r e d b y K a p l a n , n o r d o e s i t e n d o r s e a n y p a s s r a t e s c l a i m e d b y t h e p r o v i d e r . C A I A A i s n o t r e s p o n s i b l e f o r a n y f e e s o r c o s t s p a i d b y t h e u s e r t o K a p l a n n o r is C A I A A r e s p o n s i b l e f o r a n y f e e s o r c o s t s o f a n y p e r s o n o r e n t i t y p r o v i d i n g a n y s e r v i c e s t o K a p l a n . G A I A , C A I A A s s o c i a t i o n , C h a r t e r e d A l t e r n a t i v e I n v e s t m e n t A n a l y s t , a n d C h a r t e r e d A l t e r n a t i v e I n v e s t m e n t A n a l y s t A s s o c i a t i o n a r e s e r v i c e m a r k s a n d t r a d e m a r k s o w n e d b y C H A R T E R E D A L T E R N A T I V E I N V E S T M E N T A N A L Y S T A S S O C I A T I O N , I N C . , a M a s s a c h u s e t t s n o n - p r o f i t c o r p o r a t i o n w i t h i t s p r i n c i p a l p l a c e o f b u s i n e s s a t A m h e r s t , M a s s a c h u s e t t s , a n d a r e u s e d b y p e r m i s s i o n . 2018 SchweserNotes TM FRM Exam Prep Part Operational and Integrated Risk Management eBook 3 K A P L A N ') S C H W E S E R Getting Started FRM Exam Part II Welcome As the VP of Advanced Designations at Kaplan Schweser, I am pleased to have the opportunity to help you prepare for the 2018 FRM Exam. Getting an early start on your study program is important for you to sufficiently prepare, practice, and perform on exam day. Proper planning will allow you to set aside enough time to master the learning objectives in the Part II curriculum. Now that you've received your SchweserNotes, here's how to get started: Step 1: Access Your Online Tools Visit www.schweser.com/frm and log in to your online account using the button located in the top navigation bar. After logging in, select the appropriate part and proceed to the dashboard where you can access your online products.
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Create a study plan with the Schweser Study Calendar (located on the Schweser dashboard). Then view the Candidate Resource Library on-demand videos for an introduction to core concepts.
Step 3: Prepare and Practice
Read your SchweserNotes
Our clear, concise study notes will help you prepare for the exam. At the end of each reading, you can answer the Concept Checker questions for better understanding of the curriculum.
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Attend our Live Online Weekly Class or review the on-demand archives as often as you like. Our expert faculty will guide you through the FRM curriculum with a structured approach to help you prepare for the exam. (See our instruction packages to the right. Visit www.schweser.com/frm to order.)
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Derek Burkett, CFA, FRM, CAIA VP, Advanced Designations, Kaplan Schweser
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FRM Pa r t II Bo o k 3: O pe r a t i o n a l a n d In t e g r a t e d Ri s k Ma n a g e me n t
Re a d in g A s s ig n me n t s a n d Le a r n in g O b j e c t iv e s
O pe r a t io n a l a n d In t e g r a t e d Ris k Ma n a g e me n t
37: Principles for the Sound Management of Operational Risk 38: Enterprise Risk Management: Theory and Practice 39: Observations on Developments in Risk Appetite Frameworks and IT
Infrastructure
40: Information Risk and Data Quality Management 41: OpRisk Data and Governance 42: External Loss Data 43: Capital Modeling 44: Standardized Measurement Approach for Operational Risk 45: Parametric Approaches (II): Extreme Value 46: Validating Rating Models 47: Model Risk 48: Risk Capital Attribution and Risk-Adjusted Performance Measurement 49: Range of Practices and Issues in Economic Capital Frameworks 50: Capital Planning at Large Bank Holding Companies: Supervisory
Expectations and Range of Current Practice
51: Repurchase Agreements and Financing 52: Estimating Liquidity Risks 53: Assessing the Quality of Risk Measures 54: Liquidity and Leverage 55: The Failure Mechanics of Dealer Banks 56: Stress Testing Banks 57: Guidance on Managing Outsourcing Risk 58: Basel I, Basel II, and Solvency II 59: Basel II.5, Basel III, and Other Post-Crisis Changes 60: Fundamental Review of the Trading Book 61: Sound Management of Risks Related to Money Laundering
and Financing of Terrorism
Se l f -Te s t : O pe r a t io n a l a n d In t e g r a t e d Ris k Ma n a g e me n t
Fo r mu l a s
In d e x
v
1 15
25 35 43 61 73 86 96 104 116 128 146
164 178 192 206 216 237 248 259 267 290 307
316
332
338
343
2018 Kaplan, Inc.
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FRM 2018 PART II BOOK 3: OPERATIONAL AND INTEGRATED RISK MANAGEMENT 2018 Kaplan, Inc. All rights reserved. Published in 2018 by Kaplan, Inc. Printed in the United States of America. ISBN: 978-1-4754-7033-8
Required Disclaimer: GARP does not endorse, promote, review, or warrant the accuracy of the products or services offered by Kaplan of FRM related information, nor does it endorse any pass rates claimed by the provider. Further, GARP is not responsible for any fees or costs paid by the user to Kaplan, nor is GARP responsible for any fees or costs of any person or entity providing any services to Kaplan. FRM, GARP, and Global Association of Risk Professionals are trademarks owned by the Global Association of Risk Professionals, Inc. These materials may not be copied without written permission from the author. The unauthorized duplication of these notes is a violation of global copyright laws. Your assistance in pursuing potential violators of this law is greatly appreciated. Disclaimer: The SchweserNotes should be used in conjunction with the original readings as set forth by GARP. The information contained in these books is based on the original readings and is believed to be accurate. However, their accuracy cannot be guaranteed nor is any warranty conveyed as to your ultimate exam success.
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2018 Kaplan, Inc.
Re a d i n g A ssi g n me n t s a n d Le a r n i n g O b j e c t i v e s
The following material is a review o f the Operational and Integrated Risk Management principles designed to address the learning objectives set forth by the Global Association o f Risk Professionals.
Re a d in g A s s ig n me n t s
37. Principles for the Sound Management of Operational Risk, (Basel Committee on
Banking Supervision Publication, June 2011).
(page 1)
38. Brian Nocco and Rene Stulz, Enterprise Risk Management: Theory and Practice,
Journal of Applied Corporate Finance 18, No. 4 (2006): 8-20.
(page 15)
39. Observations on Developments in Risk Appetite Frameworks and IT Infrastructure, (page 23)
Senior Supervisors Group, December 2010.
Anthony Tarantino and Deborah Cernauskas, Risk Management in Finance: Six Sigma and Other Next Generation Techniques (Hoboken, NJ: John Wiley & Sons, 2009).
40. Information Risk and Data Quality Management, Chapter 3
(page 33)
Marcelo G. Cruz, Gareth W. Peters, and Pavel V. Shevchenko, Fundamental Aspects o f Operational Risk and Insurance Analytics: A Handbook o f Operational Risk (Hoboken, NJ: John Wiley & Sons, 2015).
41. OpRisk Data and Governance, Chapter 2
(page 43)
Philippa X. Girling, Operational Risk Management: A Complete Guide to a Successful Operational Risk Framework (Hoboken, NJ: John Wiley & Sons, 2013).
42. External Loss Data, Chapter 8
43. Capital Modeling, Chapter 12
(page 61)
(page 73)
44. Standardized Measurement Approach for Operational RiskConsultative Document,
(Basel Committee on Banking Supervision Publication, March 2016).
(page 86)
Kevin Dowd, Measuring Market Risk, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2005).
45. Parametric Approaches (II): Extreme Value, Chapter 7
(page 96)
Giacomo De Laurentis, Renato Maino, and Luca Molteni, Developing, Validating and Using Internal Ratings (Hoboken, NJ: John Wiley & Sons, 2010).
46. Validating Rating Models, Chapter 5
(page 104)
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Michel Crouhy, Dan Galai and Robert Mark, The Essentials o f Risk Management, 2nd Edition (New York, NY: McGraw-Hill, 2014).
47. Model Risk, Chapter 13
48. Risk Capital Attribution and Risk-Adjusted Performance Measurement,
Chapter 17
(page 116)
(page 128)
49. Range of Practices and Issues in Economic Capital Frameworks, (Basel Committee on
Banking Supervision Publication, March 2009).
(page 146)
30. Capital Planning at Large Bank Holding Companies: Supervisory Expectations
and Range of Current Practice, Board of Governors of the Federal Reserve System, August 2013.
(page 164)
Bruce Tuckman and Angel Serrat, Fixed Income Securities: Tools for Today s Markets, 3rd Edition (Hoboken, NJ: John Wiley & Sons, 2011)
51. Repurchase Agreements and Financing, Chapter 12
(page 178)
Kevin Dowd, Measuring Market Risk, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2005).
52. Estimating Liquidity Risks, Chapter 14
(page 192)
Allan Malz, Financial Risk Management: Models, History, and Institutions (Hoboken, NJ: John Wiley & Sons, 2011).
53. Assessing the Quality of Risk Measures, Chapter 11
54. Liquidity and Leverage, Chapter 12
(page 206)
(page 216)
55. Darrell Duffie, 2010. The Failure Mechanics of Dealer Banks, Journal of Economic
Perspectives 24:1, 5172.
56. Til Schuermann, Stress Testing Banks, prepared for the Committee on Capital Market (page 248)
Regulation, Wharton Financial Institutions Center (April 2012).
(page 237)
(page 259)
57: Guidance on Managing Outsourcing Risk, Board of Governors of the Federal Reserve
System, December 2013.
John C. Hull, Risk Management and Financial Institutions, 4th Edition (Hoboken, NJ: John Wiley & Sons, 2015).
58. Basel I, Basel II, and Solvency II, Chapter 15
(page 267)
59. Basel II.5, Basel III, and Other Post-Crisis Changes, Chapter 16
60. Fundamental Review of the Trading Book, Chapter 17
(page 290)
(page 307)
61. Sound Management of Risks Related to Money Laundering and Financing of
Terrorism, (Basel Committee on Banking Supervision, June 2017).
(page 316)
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Le a r n in g O b j e c t iv e s
37. Principles for the Sound Management of Operational Risk
After completing this reading, you should be able to: 1. Describe the three lines of defense in the Basel model for operational risk
2. Summarize the fundamental principles of operational risk management as suggested
governance, (page 1)
by the Basel committee, (page 2)
3. Explain guidelines for strong governance of operational risk, and evaluate the role
of the board of directors and senior management in implementing an effective operational risk framework, (page 3)
4. Describe tools and processes that can be used to identify and assess operational risk,
(page 7)
3. Describe features of an effective control environment and identify specific controls
that should be in place to address operational risk, (page 7)
6. Explain the Basel Committees suggestions for managing technology risk and
outsourcing risk, (page 8)
38. Enterprise Risk Management: Theory and Practice After completing this reading, you should be able to: 1. Define enterprise risk management (ERM) and explain how implementing ERM
practices and policies can create shareholder value, both at the macro and the micro level, (page 13)
2. Explain how a company can determine its optimal amount of risk through the use
of credit rating targets, (page 17)
3. Describe the development and implementation of an ERM system, as well as
challenges to the implementation of an ERM system, (page 17)
4. Describe the role of and issues with correlation in risk aggregation, and describe
typical properties of a firms market risk, credit risk, and operational risk distributions, (page 18)
5. Distinguish between regulatory and economic capital, and explain the use of
economic capital in the corporate decision making process, (page 19)
39. Observations on Developments in Risk Appetite Frameworks and IT Infrastructure
After completing this reading, you should be able to: 1. Describe the concept of a risk appetite framework (RAF), identify the elements
of an RAF, and explain the benefits to a firm of having a well-developed RAF. (page 25)
2. Describe best practices for a firms Chief Risk Officer (CRO), Chief Executive
Officer (CEO), and its board of directors in the development and implementation of an effective RAF. (page 26)
3. Explain the role of an RAF in managing the risk of individual business lines within a firm, and describe best practices for monitoring a firms risk profile for adherence to the RAF. (page 27)
4. Explain the benefits to a firm from having a robust risk data infrastructure, and
describe key elements of an effective IT risk management policy at a firm, (page 28)
5. Describe factors that can lead to poor or fragmented IT infrastructure at an
6. Explain the challenges and best practices related to data aggregation at an
organization, (page 29)
organization, (page 30)
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40. Information Risk and Data Quality Management
After completing this reading, you should be able to: 1. 2. Explain how a firm can set expectations for its data quality and describe some key
Identify the most common issues that result in data errors, (page 36)
dimensions of data quality used in this process, (page 36)
3. Describe the operational data governance process, including the use of scorecards in
managing information risk, (page 38)
41. OpRisk Data and Governance
After completing this reading, you should be able to: 1. Describe the seven Basel II event risk categories and identify examples of
operational risk events in each category, (page 43)
2. Summarize the process of collecting and reporting internal operational loss data, including the selection of thresholds, the timeframe for recoveries, and reporting expected operational losses, (page 46)
3. Explain the use of a Risk Control Self-Assessment (RCSA) and key risk indicators
(KRIs) in identifying, controlling, and assessing operational risk exposures. (page 48)
4. Describe and assess the use of scenario analysis in managing operational risk, and identify biases and challenges that can arise when using scenario analysis, (page 31) 3. Compare the typical operational risk profiles of firms in different financial sectors,
(page 53)
6. Explain the role of operational risk governance and explain how a firms
organizational structure can impact risk governance, (page 56)
42. External Loss Data
After completing this reading, you should be able to: 1. Explain the motivations for using external operational loss data and common
sources of external data, (page 61)
2. Explain ways in which data from different external sources may differ, (page 64) 3. Describe the challenges that can arise through the use of external data, (page 65) 4. Describe the Societe Generale operational loss event and explain the lessons learned
from the event, (page 66)
43. Capital Modeling
After completing this reading, you should be able to: 1. Compare the basic indicator approach, the standardized approach, and the
alternative standardized approach for calculating the operational risk capital charge, and calculate the Basel operational risk charge using each approach, (page 73)
2. Describe the modeling requirements for a bank to use the Advanced Measurement
3. Describe the loss distribution approach to modeling operational risk capital.
Approach (AMA). (page 78)
(page 79)
4. Explain how frequency and severity distributions of operational losses are obtained,
including commonly used distributions and suitability guidelines for probability distributions, (page 79)
5. Explain how Monte Carlo simulation can be used to generate additional data points
to estimate the 99.9th percentile of an operational loss distribution, (page 81)
6. Explain the use of scenario analysis and the hybrid approach in modeling
operational risk capital, (page 81)
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44. Standardized Measurement Approach for Operational Risk
Book 3 Reading Assignments and Learning Objectives
After completing this reading, you should be able to: 1. Explain the elements of the proposed Standardized Measurement Approach (SMA),
including the business indicator, internal loss multiplier and loss component, and calculate the operational risk capital requirement for a bank using the SMA. (page 86)
2. Compare the SMA to earlier methods of calculating operational risk capital, including the Alternative Measurement Approaches (AMA), and explain the rationale for the proposal to replace them, (page 90)
3. Describe general and specific criteria recommended by the Basel Committee for the
identification, collection, and treatment of operational loss data, (page 91)
43. Parametric Approaches (II): Extreme Value
.After completing this reading, you should be able to: 1. Explain the importance and challenges of extreme values in risk management.
(page 96)
2. Describe extreme value theory (EVT) and its use in risk management, (page 96) 3. Describe the peaks-over-threshold (POT) approach, (page 98) 4. Compare and contrast generalized extreme value and POT. (page 100) 3. Evaluate the tradeoffs involved in setting the threshold level when applying the GP
distribution, (page 98)
6. Explain the importance of multivariate EVT for risk management, (page 100)
46. Validating Rating Models
After completing this reading, you should be able to: 1. Explain the process of model validation and describe best practices for the roles of
internal organizational units in the validation process, (page 104)
2. Compare qualitative and quantitative processes to validate internal ratings, and
describe elements of each process, (page 107)
3. Describe challenges related to data quality and explain steps that can be taken to
validate a models data quality, (page 109)
4. Explain how to validate the calibration and the discriminatory power of a rating
model, (page 111)
47. Model Risk
After completing this reading, you should be able to: 1.
Identify and explain errors in modeling assumptions that can introduce model risk. (page 116)
2. Explain how model risk can arise in the implementation of a model, (page 118) 3. Explain methods and procedures risk managers can use to mitigate model risk.
(page 119)
4. Explain the impact of model risk and poor risk governance in the 2012 London
Whale trading loss and the 1998 collapse of Long Term Capital Management. (page 120)
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48. Risk Capital Attribution and Risk-Adjusted Performance Measurement
After completing this reading, you should be able to: 1. Define, compare, and contrast risk capital, economic capital, and regulatory capital,
and explain methods and motivations for using economic capital approaches to allocate risk capital, (page 128)
2. Describe the RAROC (risk-adjusted return on capital) methodology and its use in
capital budgeting, (page 130)
3. Compute and interpret the RAROC for a project, loan, or loan portfolio, and use
RAROC to compare business unit performance, (page 130)
4. Explain challenges that arise when using RAROC for performance measurement, including choosing a time horizon, measuring default probability, and choosing a confidence level, (page 133)
3. Calculate the hurdle rate and apply this rate in making business decisions using
RAROC. (page 133)
6. Compute the adjusted RAROC for a project to determine its viability, (page 136) 7. Explain challenges in modeling diversification benefits, including aggregating a firms risk capital and allocating economic capital to different business lines. (page 136)
8. Explain best practices in implementing an approach that uses RAROC to allocate
economic capital, (page 138)
49. Range of Practices and Issues in Economic Capital Frameworks
After completing this reading, you should be able to: 1. Within the economic capital implementation framework describe the challenges
that appear in: Defining and calculating risk measures Risk aggregation Validation of models Dependency modeling in credit risk Evaluating counterparty credit risk Assessing interest rate risk in the banking book (page 146)
2. Describe the BIS recommendations that supervisors should consider to make effective use of internal risk measures, such as economic capital, that are not designed for regulatory purposes, (page 156)
3. Explain benefits and impacts of using an economic capital framework within the
following areas: Credit portfolio management Risk based pricing Customer profitability analysis Management incentives (page 157)
capital framework, (page 158)
4. Describe best practices and assess key concerns for the governance of an economic
50. Capital Planning at Large Bank Holding Companies: Supervisory Expectations and
Range of Current Practice .After completing this reading, you should be able to: 1. Describe the Federal Reserves Capital Plan Rule and explain the seven principles of an effective capital adequacy process for bank holding companies (BHCs) subject to the Capital Plan Rule, (page 164)
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2. Describe practices that can result in a strong and effective capital adequacy process
Internal controls, including model review and valuation for a BHC in the following areas: Risk identification
Corporate governance Capital policy, including setting of goals and targets and contingency planning
Estimating losses, revenues, and expenses, including quantitative and qualitative
Stress testing and stress scenario design
methodologies
Assessing the impact of capital adequacy, including risk-weighted asset (RWA)
and balance sheet projections (page 166)
31. Repurchase Agreements and Financing
After completing this reading, you should be able to: 1. Describe the mechanics of repurchase agreements (repos) and calculate the
settlement for a repo transaction, (page 178)
2. Explain common motivations for entering into repos, including their use in cash
management and liquidity management, (page 179)
3. Explain how counterparty risk and liquidity risk can arise through the use of repo
transactions, (page 181)
4. Assess the role of repo transactions in the collapses of Lehman Brothers and Bear
Stearns during the (2007-2009) credit crisis, (page 182)
3. Compare the use of general and special collateral in repo transactions, (page 183) 6. Describe the characteristics of special spreads and explain the typical behavior of
US Treasury special spreads over an auction cycle, (page 185)
7. Calculate the financing advantage of a bond trading special when used in a repo
transaction, (page 186)
52. Estimating Liquidity Risks
After completing this reading, you should be able to: 1. Define liquidity risk and describe factors that influence liquidity, including the bid-
ask spread, (page 192)
2. Differentiate between exogenous and endogenous liquidity, (page 193) 3. Describe the challenges of estimating liquidity-adjusted VaR (LVaR). (page 193) 4. Describe and calculate LVaR using the constant spread approach and the exogenous
spread approach, (page 194)
5. Describe endogenous price approaches to LVaR, their motivation and limitations,
and calculate the elasticity-based liquidity adjustment to VaR. (page 197)
6. Describe liquidity at risk (LaR) and compare it to LVaR and VaR, describe the factors that affect future cash flows, and explain challenges in estimating and modeling LaR. (page 199)
7. Describe approaches to estimate liquidity risk during crisis situations and challenges
which can arise during this process, (page 200)
53. Assessing the Quality of Risk Measures
After completing this reading, you should be able to: 1. Describe ways that errors can be introduced into models, (page 206) 2. Explain how model risk and variability can arise through the implementation of
VaR models and the mapping of risk factors to portfolio positions, (page 207)
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3.
Identify reasons for the failure of the long-equity tranche, short-mezzanine credit trade in 2003 and describe how such modeling errors could have been avoided. (page 209)
4. Explain major defects in model assumptions that led to the underestimation of
systematic risk for residential mortgage backed securities (RMBS) during the 2007 2009 financial downturn, (page 211)
34. Liquidity and Leverage
After completing this reading, you should be able to: 1. Differentiate between sources of liquidity risk, including balance sheet/funding
liquidity risk, systematic funding liquidity risk, and transactions liquidity risk, and explain how each of these risks can arise for financial institutions, (page 216)
2. Summarize the asset-liability management process at a fractional reserve bank,
including the process of liquidity transformation, (page 217)
3. Describe specific liquidity challenges faced by money market mutual funds and by
hedge funds, particularly in stress situations, (page 219)
4. Compare transactions used in the collateral market and explain risks that can arise
through collateral market transactions, (page 220)
5. Describe the relationship between leverage and a firms return profile, calculate the
leverage ratio, and explain the leverage effect, (page 222)
6. Explain the impact on a firms leverage and its balance sheet of the following
transactions: purchasing long equity positions on margin, entering into short sales, and trading in derivatives, (page 224)
7. Explain methods to measure and manage funding liquidity risk and transactions
liquidity risk, (page 228)
8. Calculate the expected transactions cost and the spread risk factor for a transaction, and calculate the liquidity adjustment to VaR for a position to be liquidated over a number of trading days, (page 229)
9. Explain interactions between different types of liquidity risk and explain how
liquidity risk events can increase systemic risk, (page 216)
55. The Failure Mechanics of Dealer Banks
After completing this reading, you should be able to: 1. Describe the major lines of business in which dealer banks operate and the risk
factors they face in each line of business, (page 237) Identify situations that can cause a liquidity crisis at a dealer bank and explain responses that can mitigate these risks, (page 241)
2.
3. Describe policy measures that can alleviate firm-specific and systemic risks related to
large dealer banks, (page 244)
56. Stress Testing Banks
After completing this reading, you should be able to: 1. Describe the historical evolution of the stress testing process and compare methodologies of historical EBA, CCAR and SCAP stress tests, (page 249)
2. Explain challenges in designing stress test scenarios, including the problem of
coherence in modeling risk factors, (page 250)
3. Explain challenges in modeling a banks revenues, losses, and its balance sheet over a
stress test horizon period, (page 251)
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37. Guidance on Managing Outsourcing Risk
Book 3 Reading Assignments and Learning Objectives
After completing this reading, you should be able to: 1. Explain how risks can arise through outsourcing activities to third-party service providers, and describe elements of an effective program to manage outsourcing risk, (page 239)
2. Explain how financial institutions should perform due diligence on third-party
3. Describe topics and provisions that should be addressed in a contract with a third-
service providers, (page 260)
party service provider, (page 261)
58. Basel I, Basel II, and Solvency II
After completing this reading, you should be able to: 1. Explain the motivations for introducing the Basel regulations, including key risk
exposures addressed, and explain the reasons for revisions to Basel regulations over time, (page 267)
2. Explain the calculation of risk-weighted assets and the capital requirement per the
original Basel I guidelines, (page 268)
3. Describe and contrast the major elementsincluding a description of the risks coveredof the two options available for the calculation of market risk capital:

Standardized Measurement Method Internal Models Approach (page 271)
4. Calculate VaR and the capital charge using the internal models approach, and
explain the guidelines for backtesting VaR. (page 272)
5. Describe and contrast the major elements of the three options available for the
Standardized Approach calculation of credit risk capital:
Foundation IRB Approach Advanced IRB Approach (page 274)
6. Describe and contrast the major elements of the three options available for the
calculation of operational risk capital: basic indicator approach, standardized approach, and the Advanced Measurement Approach, (page 280)
7. Describe the key elements of the three pillars of Basel II: minimum capital
requirements, supervisory review, and market discipline, (page 280)
8. Define in the context of Basel II and calculate the worst-case default rate (WCDR).
(page 274)
9. Differentiate between solvency capital requirements (SCR) and minimum capital requirements (MCR) in the Solvency II framework, and describe the repercussions to an insurance company for breaching the SCR and MCR. (page 282)
10. Compare the standardized approach and the Internal Models Approach for
calculating the SCR in Solvency II. (page 282)
59. Basel II.5, Basel III, and Other Post-Crisis Changes After completing this reading, you should be able to: 1. Describe and calculate the stressed VaR measure introduced in Basel 2.5, and
calculate the market risk capital charge, (page 290)
2. Explain the process of calculating the incremental risk capital charge for positions
held in a banks trading book, (page 292)
3. Describe the comprehensive risk measure (CRM) for positions that are sensitive to
correlations between default risks, (page 292)
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4. Define in the context of Basel III and calculate where appropriate.
Tier 1 capital and its components Tier 2 capital and its components Required Tier 1 equity capital, total Tier 1 capital, and total capital (page 294) 3. Describe the motivations for and calculate the capital conservation buffer and the
countercyclical buffer introduced in Basel III. (page 293)
6. Describe and calculate ratios intended to improve the management of liquidity risk, including the required leverage ratio, the liquidity coverage ratio, and the net stable funding ratio, (page 296)
7. Describe the mechanics of contingent convertible bonds (CoCos) and explain the
motivations for banks to issue them, (page 299)
8. Explain the major changes to the US financial market regulations as a result of
Dodd-Frank, (page 300)
60. Fundamental Review of the Trading Book
After completing this reading, you should be able to: 1. Describe the proposed changes to the Basel market risk capital calculation and
the motivations for these changes, and calculate the market risk capital under this method, (page 307)
2. Compare the various liquidity horizons proposed by the Fundamental Review of the Trading Book (FRTB) for different asset classes and explain how a bank can calculate its expected shortfall using the various horizons, (page 309)
3. Explain proposed modifications to Basel regulations in the following areas:
Classification of positions in the trading book compared to the banking book Treatment of credit spread and jump-to-default risk, including the incremental
default risk charge (page 311)
61. Sound Management of Risks Related to Money Laundering and Financing
of Terrorism After completing this reading, you should be able to: 1. Explain best practices recommended by the Basel Committee for the assessment,
management, mitigation, and monitoring of money laundering and financial terrorism (ML/FT) risks, (page 316)
2. Describe recommended practices for the acceptance, verification, and identification
of customers at a bank, (page 318)
3. Explain practices for managing ML/FT risks in a group-wide and cross-border
context, and describe the roles and responsibilities of supervisors in managing these risks, (page 320)
4. Explain policies and procedures a bank should use to manage ML/FT risks in
situations where it uses a third party to perform customer due diligence and when engaging in correspondent banking, (page 322)
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The following is a review of the Operational and Integrated Risk Management principles designed to address the learning objectives set forth by GARP. This topic is also covered in:
Pr i n c i pl e s f o r t h e So u n d Ma n a g e me n t o f O pe r a t i o n a l Ri s k
Topic 37
Ex a m Fo c u s
This is a descriptive topic that addresses the principles of sound operational risk management as proposed by the Basel Committee on Banking Supervision. The committee describes a three lines of defense approach, which includes business line management, independent operational risk management, and independent reviews. The committee suggests that a bank should have a corporate operational risk function (CORF) that is commensurate with the size and complexity of the banking organization. For the exam, understand the 11 principles of operational risk management as outlined by the Basel Committee. Know the specific responsibilities of the board of directors and senior managers as they relate to the 11 principles of operational risk management. Be able to explain the critical components of the banks operational risk management framework documentation, and know the features of an effective control environment. Lastly, understand the committees recommendations for managing technology and outsourcing risk.
O pe r a t io n a l Ris k G o v e r n a n c e

LO 36.7: Explain the implications o f the subprime mortgage meltdown on portfolio management.
Currently, the rating agencies collectively monitor approximately 10,000 mortgage pools. It would be impractical to monitor each pool on a monthly basis in detail. It is current practice to annually review each individual pool. An important performance measure used during this review is the loss coverage ratio (LCR), defined as: (current credit enhancement for tranche) / (estimated unrealized losses). An example of a credit enhancement is excess spread. If the LCR is breached (i.e., falls below what is acceptable), a full review is warranted.
P r e d a t o r y L e n d i n g a n d B o r r o w i n g

LO 36.6: Describe the relationship between the credit ratings cycle and the housing cycle.
The goal of the rating system is to rate through-the-cycle, meaning that there should not be excessive upgrades (downgrades) if the housing market heats up (slows down). A problem may arise if the agency assigns, say, an AAA rating during a boom period. As the housing market slows down, the probability of default increases and the security has migrated to AA even though the agency has not made a public pronouncement. The problem is further exacerbated if new deals are based on the credit enhancements from the AAA rating in the boom period.
As economic conditions change, it is expected to see some upgrades or downgrades in mortgage-backed securities. However, the effect may amplify up and down markets. For example, in a downward trending market, additional enhancements are needed to maintain the highest ratings. This crowds out the credit available for lower rated borrowers increasing the required loan rate or raising qualification standards. The opposite is true for housing upturns freeing up credit for lower rated borrowers.
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Topic 36 Cross Reference to GARP Assigned Reading – Ashcroft & Schuermann
Cash Flow Analysis o f Excess Spread
In the ratings process it is necessary to simulate the cash flows of the structure to forecast the degree of excess spread used for credit enhancement. As you can imagine, the forecasts are complex and depend on several interrelated factors including credit enhancement, timing of losses, prepayment rates, interest rates, trigger events, weighted average loan rate decrease, prepayment penalties, pre-funding accounts, and hedging instruments. The more important factors are discussed as follows.
First, the credit enhancement identifies the amount of collateral that can be impaired before the tranche suffers an economic loss. The timing of losses is also important because as losses accumulate, less excess spread will be available. A more conservative approach would front-load the losses. Prepayments will directly impact the excess spread. Prepayments may be voluntary (refinance, sales) or involuntary (default) so the prepayment assumption directly impacts the cash flow analysis. Prepayments typically follow the CPR (conditional prepayment rate) convention. However, it is important to note that hybrids will have higher than predicted defaults on or about the reset date due to the sudden change in rates and financial condition of the subprime borrower. A more conservative view would accelerate prepayments reducing further interest collections. Finally, the path of interest rates introduces uncertainty into the projected cash flow stream. Interest rates determine the adjustments (i.e., cash inflows), and influence refinancing.

LO 36.3: Explain the im plications o f credit ratings on the emergence o f subprime related m ortgage backed securities.
Assigning credit ratings for securitized assets presents additional challenges. Credit ratings for subprime securities, and more generally asset-backed securities (ABS), differ from corporate ratings in several important ways. First, corporate bond ratings are based on the firm-specific characteristics of the issuer where as ABS is a claim on a portfolio. Hence, systematic risk and degree of correlation between assets is important in the latter but not the former. ABS represents claims on a static pool and cannot infuse additional capital or restructure as a corporation can. In addition, the forecasts for ABS incorporate future economic conditions since the cash flow stream is tied to the macro environment. Finally, while corporates and ABSs with the same rating may indicate similar default probabilities, the ABS will exhibit much wider variation in losses.

LO 36.4: Describe the credit ratings process with respect to subprime mortgage backed securities.
A credit rating is defined as an opinion on the creditworthiness of the specific bond issue. Note that the assigned rating is specific to the security and in no way a reflection on the originator. The ratings represent an unconditional view of the rating agency as they rate through-the-cycle.
The rating process involves two steps: (1) estimation of loss distribution and (2) simulation of the cash flows. Once the estimates are obtained, the agency indicates the level of credit enhancement necessary to achieve the desired rating. If the projected rating is too low, the originator can provide additional enhancement to raise the rating.

LO 36.3: Describe the characteristics o f the subprime mortgage market, including the creditworthiness o f the typical borrower and the features and performance o f a subprim e loan.
Subprime borrowers have a history of either default or strong indicators of possible future default. Past incidents include 30- or 60-day delinquencies, judgments, foreclosures, repossessions, charge-offs, or bankruptcy filings. Low FICO scores (660 or below) or a high debt service ratio of 30% or more are likely indicators of future default.
The vast majority of subprime loans are adjustable rate mortgages. The loan offers a teaser rate for a short period of time, and then adjusts each year relative to a floating rate index (usually LIBOR). The 2- and 3-year teaser rates are called 2/28 and 3/27 hybrid arms denoting the fixed and floating terms, respectively (e.g., fixed term is 2 years, floating term is 28 years). Since the majority of the term of the mortgage is floating, the borrower is bearing the interest rate risk in contrast to a traditional fixed rate mortgage where the lender bears the interest rate risk.
The performance of subprime pools indicates defaults and foreclosures way above historical levels. As a point of reference, the authors of the assigned reading analyze a New Century pool originating in May 2006 and estimate a 23% cumulative default rate through August 2007.
Securitized pools incorporate structures to provide protection to investors from losses in the collateral including subordination, excess spread, shifting interest, performance triggers, and interest rate swaps.
Subordination involves creating tranches of differing priority levels. Losses are applied first to the most subordinated tranche, the equity tranche. The equity tranche is usually created from overcollateralization (i.e., assets in excess of face value). If the losses exceed the size of this tranche then losses will reach the next highest subordinated level called the mezzanine. Credit ratings on mezzanine debt typically vary from AA to B. In this fashion, the most senior tranche is protected by all the junior tranches and offers the lowest return.
Mortgages pools are typically constructed so that the weighted average coupon (less servicing, hedging, and other expenses) exceeds the weighted average payout. The difference is called the excess spread which is paid to equity tranche investors when available. Thus, the excess spread protects all tranches.
Under shifting interest, the senior investors receive all principal in the pool while the mezzanine investors receive only interest. The senior holders may receive the principal for a set period of time (lockout period) or until a cutoff ratio is reached.
Performance triggers denote the release of overcollateralizion which is applied from the bottom of the capital structure up.
Since the first few years of the pool are fixed, the pool faces interest rate risk. As protection, interest rate swaps are used where the pool will pay a fixed rate and receive a floating rate.
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T h e C r e d i t R a t i n g s P r o c e s s

LO 36.8).
Friction 3: Arranger and third-parties. The arranger of the pool of mortgages will possess
better information about the borrower than third parties including rating agencies, asset managers, and warehouse lenders. The adverse selection problem gives the arranger the opportunity to retain the higher quality mortgages and securitize the lower quality mortgages (i.e., lemons).
The warehouse lender temporarily holds and finances the underlying purchases. As a precaution, the warehouse will fund less than 100% of its estimated collateral value forcing the arranger to retain a equity position on its balance sheet.
The asset portfolio manager purchases the assets for the pool from the arranger. Once again, the arranger has superior information about the creditworthiness of the mortgage pool. To minimize the potential adverse selection problem, the asset manager must use adequate due diligence, use reputable arrangers, and force credit enhancements from the arranger.
Similarly, the rating agencies determine the amount of credit enhancement necessary to achieve the desired credit rating. Thus, the rating agency is dependent on the information provided by the arranger. Typically, the due diligence on the arranger and originator is rushed.
Friction 4:
Servicer and mortgagor. The servicers role is to manage the cash flows of the pool and follow up on delinquencies and foreclosures. A conflict of interest arises for delinquent loans. The homeowner in financial difficulty does not have the incentive to upkeep tax payments, insurance, or maintenance on the
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property. Escrowed funds can minimize this problem but ultimately efficient foreclosure must comply with federal regulations.
Friction 5:
Servicer and third-parties. The servicer faces a moral hazard problem because their (lack of) effort can impact the asset manager and credit rating agencies without directly affecting their own cash flow distribution. In delinquency, the servicer is responsible for the property taxes and insurance premiums. These funds are reimbursable upon foreclosure so there is a temptation to exaggerate the fees and expenses particularly with high recovery rates.
The servicer also has an incentive to keep the problem loan on its books by modifying loan terms rather than foreclose (investor preference). Since most of the costs are unrecoverable (escrow analysis, payment set up, etc.) the property needs to be active to generate any additional funds to the servicer.
It is apparent that the quality of the servicer can directly impact the cash flows of the pool which in turn affects the credit rating. Changes in credit ratings reflect poorly on the agency. Therefore, the credit rating agencies must use due diligence in analyzing the servicer as well as the underlying collateral.
Friction 6:
Asset manager and investor. The investor relies on the asset managers expertise to identify and analyze potential investments. It is difficult for the investor to comprehend the investment strategy and the investor will not be able to observe the effort of the management team (same moral hazard problem as shareholder-manager). Investment mandates and proper benchmarking can mitigate some of the distortion.
Friction 7:
Investor and credit rating agencies. Rating agencies are compensated by the arranger and not the end user, the investor. To the extent that the rating agencies are beholden to the fee structure of the arranger, a conflict of interest arises. In addition, it is very difficult to judge the accuracy of their models particularly with complex products and rapid financial innovation.
Five of these factors are direct contributors to the recent subprime crisis. First, the complexity of the product and naive nature of the borrower led to inappropriate loans (friction 1). Second, managers sought the additional yield from structured mortgage products without fully assessing the associated risks (friction 6). Third, the problem became more expansive as underperforming managers made similar investments with less due diligence on the arranger and originator (friction 3). Fourth, as the asset managers reduced their oversight, it was natural that the arranger would follow suit (friction 2). This left the credit rating agencies as the last line of defense but they operated at a significant informational disadvantage. Finally, the assigned ratings were hopelessly misguided (friction 7).
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LO 36.2: Identify and describe key frictions in subprime mortgage securitization, and assess the relative contribution o f each factor to the subprime mortgage problems.
In general, when two parties do not have the same information (which is usually the case), a sub-optimal outcome results. The two broad classes of information problems we will discuss here are moral hazard and adverse selection. Moral hazard denotes the actions one party may take to the detriment of the other. A classic example is the shareholder-manager relationship where the managers may use their position for personal gain rather than for
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the shareholders to whom they owe a fiduciary duty. On the other hand, adverse selection is when one party possesses important hidden information. For example, a persons driving ability is private knowledge and a potential buyer of auto insurance will have the incentive to represent themselves as good drivers even if they are not. Mechanisms are designed to minimize these information problems such as board oversight for the managers and examination of driving records for those seeking auto insurance.
There are seven frictions in the mortgage securitization process. Each friction is discussed as follows.
Friction 1: Mortgagor and originator. The typical subprime borrower is typically
financially unsophisticated. As a result, the borrower may not select the best borrowing alternative for themselves. In fact, the borrower may not even be aware of the financing options available. On the other hand, the lender may steer the borrower to products that are not suitable.
Friction 2: Originator and arranger. The arranger (issuer) purchases the loans from
the originators for the purpose of resale through securitized products. The arranger will perform due diligence but still operates at an information disadvantage to the originator. That is, the originator has superior knowledge about the borrower (adverse selection problem). In addition, the originator may falsify or stretch the bounds of the application resulting in larger than optimal lending (predatory lending or predatory borrowing as discussed in

LO 36.1: Explain the subprim e m ortgage credit securitization process in the United States.
The subprime securitization process in the United States involves several different parties beginning with the borrowing needs of the home buyer. The borrower (mortgagor) applies for a mortgage and, conditional on the due diligence of the lender, is extended a loan with the residence serving as collateral. Borrowers range in quality from prime (i.e., strong credit history) to Alt-A (i.e., borrowers with good credit but more aggressive underwriting standards) to subprime (i.e., borrowers with poor credit history). Lenders sell a significant portion of their loans to a third-party (special purpose vehicle) and receive cash in return. Prime loans that meet conforming standards are sold to government sponsored enterprises (GSEs). The remaining loans are increasingly being sold and taken off the originators balance sheet. Approximately 73% of newly originated subprime mortgages were securitized in 2003 and 2006.
F r i c t i o n s i n S u b p r i m e M o r t g a g e S e c u r i t i z a t i o n