Enhanced Disclosure of the Models Used in the Federal Reserve's Supervisory Stress Test, 59547-59555 [2017-26856]
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Federal Register / Vol. 82, No. 240 / Friday, December 15, 2017 / Proposed Rules
By order of the Board of Governors of the
Federal Reserve System, December 7, 2017.
Ann E. Misback,
Secretary of the Board.
[FR Doc. 2017–26858 Filed 12–14–17; 8:45 am]
BILLING CODE 6210–01–P
FEDERAL RESERVE SYSTEM
12 CFR Chapter II
[Docket No. OP–1586]
Enhanced Disclosure of the Models
Used in the Federal Reserve’s
Supervisory Stress Test
Board of Governors of the
Federal Reserve System (Board).
ACTION: Notification with request for
public comment.
AGENCY:
The Board is inviting
comment on an enhanced disclosure of
the models used in the Federal
Reserve’s supervisory stress test
conducted under the Board’s Regulation
YY pursuant to the Dodd-Frank Wall
Street Reform and Consumer Protection
Act (Dodd-Frank Act) and the Board’s
capital plan rule.
DATES: Comments must be received by
January 22, 2018.
ADDRESSES: You may submit comments,
identified by Docket No. OP–1586 by
any of the following methods:
• Agency website: https://
www.federalreserve.gov. Follow the
instructions for submitting comments at
https://www.federalreserve.gov/
generalinfo/foia/ProposedRegs.aspx.
• Federal eRulemaking Portal: https://
www.regulations.gov. Follow the
instructions for submitting comments.
• Email: regs.comments@
federalreserve.gov. Include the docket
number and RIN number in the subject
line of the message.
• Fax: (202) 452–2819 or (202) 452–
3102.
• Mail: Ann Misback, Secretary,
Board of Governors of the Federal
Reserve System, 20th Street and
Constitution Avenue NW, Washington,
DC 20551.
All public comments will be made
available on the Board’s website at
https://www.federalreserve.gov/
generalinfo/foia/ProposedRegs.aspx as
submitted, unless modified for technical
reasons. Accordingly, your comments
will not be edited to remove any
identifying or contact information.
Public comments may also be viewed
electronically or in paper form in Room
3515, 1801 K St. NW (between 18th and
19th Streets NW), Washington, DC
20006 between 9:00 a.m. and 5:00 p.m.
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SUMMARY:
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on weekdays. For security reasons, the
Board requires that visitors make an
appointment to inspect comments. You
may do so by calling (202) 452–3684.
Upon arrival, visitors will be required to
present valid government-issued photo
identification and to submit to security
screening in order to inspect and
photocopy comments.
FOR FURTHER INFORMATION CONTACT: Lisa
Ryu, Associate Director, (202) 263–4833,
Kathleen Johnson, Assistant Director,
(202) 452–3644, Robert Sarama,
Manager (202) 973–7436, Division of
Supervision and Regulation; Benjamin
W. McDonough, Assistant General
Counsel, (202) 452–2036, or Julie
Anthony, Counsel, (202) 475–6682,
Legal Division, Board of Governors of
the Federal Reserve System, 20th Street
and Constitution Avenue NW,
Washington, DC 20551. Users of
Telecommunication Device for Deaf
(TDD) only, call (202) 263–4869.
SUPPLEMENTARY INFORMATION:
Table of Contents
I. Overview
II. Description of Enhanced Model Disclosure
A. Enhanced Description of Models
B. Modeled Loss Rates on Pools of Loans
C. Portfolios of Hypothetical Loans and
Associated Loss Rates
D. Explanatory Notes on Enhanced Model
Disclosures
III. Request for Comment
IV. Example of Enhanced Model Disclosure
A. Enhanced Description of Models
B. Modeled Loss Rates on Pools of Loans
C. Portfolios of Hypothetical Loans and
Associated Loss Rates
I. Overview
Each year the Federal Reserve
publicly discloses the results of the
supervisory stress test.1 The disclosures
include revenues, expenses, losses, pretax net income, and capital ratios that
would result under two sets of adverse
economic and financial conditions. As
part of the disclosures, the Federal
Reserve also describes the broad
framework and methodology used in the
supervisory stress test, including
information about the models used to
estimate the revenues, losses, and
capital ratios in the stress test. The
annual disclosures of both the stress test
results and supervisory model
framework and methodology represent a
significant increase in the public
transparency of large bank supervision
in the U.S.2 Indeed, prior to the first
1 See, for example, Dodd-Frank Act Stress Test
2017: Supervisory Stress Test Methodology and
Results, June 2017 and Comprehensive Capital
Analysis and Review 2017: Assessment Framework
and Results, June 2017.
2 In addition to those public disclosures, the
Federal Reserve has published detailed information
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supervisory stress test in 2009, many
analysts and institutions cautioned
against these disclosures, arguing that
releasing bank-specific loss estimates to
the public would be destabilizing.
However, experience to date has shown
the opposite to be true—disclosing these
details to the public has garnered public
and market confidence in the process.
The Federal Reserve routinely reviews
its stress testing and capital planning
programs, and during those reviews the
Federal Reserve has received feedback
regarding the transparency of the
supervisory stress test models.3 Some of
those providing feedback requested
more detail on modeling methodologies
with a focus on year-over-year changes
in the supervisory models.4 Others,
however, cautioned against disclosing
too much information about the
supervisory models because doing so
could permit firms to reverse-engineer
the stress test.
The Federal Reserve recognizes that
disclosing additional information about
supervisory models and methodologies
has significant public benefits, and is
committed to finding ways to further
increase the transparency of the
supervisory stress test. More detailed
disclosures could further enhance the
credibility of the stress test by providing
the public with information on the
fundamental soundness of the models
and their alignment with best modeling
practices. These disclosures would also
facilitate comments on the models from
the public, including academic experts.
These comments could lead to
improvements, particularly in the data
most useful to understanding the risks
of particular loan types. More detailed
disclosures could also help the public
understand and interpret the results of
the stress test, furthering the goal of
maintaining market and public
confidence in the U.S. financial system.
Finally, more detailed disclosures of
how the Federal Reserve’s models
assign losses to particular positions
about its scenario design framework and annual
letters detailing material model changes. The
Federal Reserve also hosts an annual symposium in
which supervisors and financial industry
practitioners share best practices in modeling,
model risk management, and governance.
3 During a review that began in 2015, the Federal
Reserve received feedback from senior management
at firms subject to the Board’s capital plan rule, debt
and equity market analysts, representatives from
public interest groups, and academics in the fields
of economics and finance. That review also
included an internal assessment.
4 Some of the comments in favor of additional
disclosure included requests that the Federal
Reserve provide additional information to firms
only, without making the additional disclosures
public. Doing so would be contrary to the Federal
Reserve’s established practice of not disclosing
information related to the stress test to firms if that
information is not also publicly disclosed.
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could help those financial institutions
that are subject to the stress test
understand the capital implications of
changes to their business activities, such
as acquiring or selling a portfolio of
assets.
The Federal Reserve also believes
there are material risks associated with
fully disclosing the models to the firms
subject to the supervisory stress test.
One implication of releasing all details
of the models is that firms could
conceivably use them to make
modifications to their businesses that
change the results of the stress test
without changing the risks they face. In
the presence of such behavior, the stress
test could give a misleading picture of
the actual vulnerabilities faced by firms.
Further, such behavior could increase
correlations in asset holdings among the
largest banks, making the financial
system more vulnerable to adverse
financial shocks.5 Another implication
is that full model disclosure could
incent banks to simply use models
similar to the Federal Reserve’s, rather
than build their own capacity to
identify, measure, and manage risk.
That convergence to the Federal
Reserve’s model would create a ‘‘model
monoculture,’’ in which all firms have
similar internal stress testing models
which may miss key idiosyncratic risks
faced by the firms.6
In the next section of the paper, three
proposed enhancements to the
supervisory stress test model
disclosures are described, with an
example of the enhanced disclosure for
the Federal Reserve’s corporate loan loss
model. If the proposed enhancements
were implemented, the Federal Reserve
would expect to publish the enhanced
disclosures in the first quarter of each
year, starting with selected loan
portfolios in 2018. The Federal Reserve
expects that the annual disclosure
would reflect any updates to
supervisory models, for applicable
portfolios, in a given year, but would be
based on data and scenarios from the
prior year.
The proposed enhancements are
designed to balance the costs and
benefits discussed above in a way that
would further enhance the public’s
understanding of the supervisory stress
test models without undermining the
5 For example, if firms were to deem a specific
asset as more advantageous to hold based on the
particulars of the supervisory models, were an
exogenous shock to occur to that specific asset
class, the firms’ losses would be magnified because
they held correlated assets.
6 See, Schuermann, T. (March 19, 2013). The
Fed’s Stress Tests Add Risk to the Financial
System. Wall Street Journal, which highlights bank
incentives to mimic Federal Reserve’s stress test
models.
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effectiveness of the stress test as a
supervisory tool.
II. Description of Enhanced Model
Disclosure
The proposed enhanced disclosures
have three components: (1) Enhanced
descriptions of supervisory models,
including key variables; (2) modeled
loss rates on loans grouped by important
risk characteristics and summary
statistics associated with the loans in
each group; and, (3) portfolios of
hypothetical loans and the estimated
loss rates associated with the loans in
each portfolio.7
Collectively, the additional
information is designed to facilitate the
public’s ability to understand the
workings of the models and provide
meaningful feedback.
A. Enhanced Description of Models
The Federal Reserve currently
discloses descriptions of the supervisory
stress test models in an appendix in the
annual Dodd-Frank Act supervisory
stress test methodology and results
document. For each modeling area, the
appendix includes a description of the
structure of the model, key features, and
the most important explanatory
variables in the model.
The proposed enhanced descriptions
of the models would expand these
descriptions in two ways. First, they
would provide more detailed
information about the structure of the
models. For example, the existing
disclosure for corporate loans explains
that the model estimates expected losses
using models of probability of default
(PD), loss given default (LGD), and
exposure at default (EAD). It further
explains that PDs are projected using a
series of equations fitted to the
historical relationship between changes
in the PD and macroeconomic variables,
including growth in real gross domestic
product, changes in the unemployment
rate, and changes in the spread on BBBrated corporate bonds. The proposed
enhanced model description would
include certain important equations that
characterize aspects of the model.
Second, the proposed enhanced
descriptions would include a table that
contains a list of the key loan
characteristics and macroeconomic
variables that influence the results of a
given model. The table would show the
relevant variables for each component of
the model (e.g., PD, LGD, EAD), and
information about the source of the
variables (see Table 1).
7 The second and third components would be
provided for the models used to project losses on
the most material loan portfolios.
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B. Modeled Loss Rates on Pools of Loans
The proposed enhanced disclosure
would include estimated loss rates for
groups of loans with distinct
characteristics. Those loss rates would
allow the public to directly see how the
supervisory models treat specific assets
under stress. The corporate loan
example included below illustrates how
this new loss rate disclosure could
operate in practice. The modeled loss
rates are reported for eight groups of
loans that have combinations of three
loan characteristics: sector (financial
and nonfinancial), security status
(secured and unsecured), and rating
class (investment grade and noninvestment grade). The average (mean)
estimated loss rate and 25th and 75th
percentiles of the estimated loan-level
loss rates are presented for each group
of loans. By presenting the modeled loss
rates in ranges as well as the average for
each group, the disclosure highlights
that loans within the same group may
have different loss rates because of
differences in other risk characteristics.
For example, nonfinancial sector loans
would include loans to companies in a
range of sectors, which may have
different sensitivities to the
macroeconomic environment associated
with any given scenario.
To shed more light on the degree of
heterogeneity of loans within a given
group, the enhanced disclosure could
also include summary statistics
associated with the loans in each group.
Combined, the modeled loss rates and
summary statistics would allow a firm
to compare the characteristics of its own
portfolio to those of the aggregate
portfolio for all firms subject to the
stress test and to better understand
differences in loss rates between the
two. The modeled loss rates could be
reported for both the supervisory
adverse and supervisory severely
adverse scenarios, which would help to
illustrate the effect of variation in
macroeconomic conditions on modeled
loss rates.
C. Portfolios of Hypothetical Loans and
Associated Loss Rates
Publishing portfolios of hypothetical
loans is another way to enhance
transparency. This approach would
allow outside parties to use their own
suites of models to estimate losses on
the portfolios and compare loss rates
across different models.
The portfolios the Federal Reserve
may publish for certain asset classes
could comprise three sets of
hypothetical loans designed to mimic
the characteristics of the actual loans
reported by firms participating in the
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D. Explanatory Notes on Enhanced
Model Disclosures 8
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The proposed enhanced model
disclosures described in this document
focus on the design of and projections
from particular models, whereas the
current disclosures of supervisory stress
test results include projections
aggregated to the portfolio level that in
most cases contain the outputs from
multiple supervisory models. As such,
the two different disclosures will not
align exactly.
The proposed enhanced model
disclosures would also differ from the
current stress testing results disclosures
in that they would not include
accounting and other adjustments used
to translate projected credit losses into
net income. In the current supervisory
stress test results disclosure, accounting
adjustments are used to translate
supervisory model estimates into
provisions and other income or expense
items needed to calculate stressed pretax net income. These adjustments often
depend on factors that vary across
participating banks, such as the write-
8 This section highlights definitional differences
between the proposed enhanced disclosures and the
loss rate disclosures in the annual Dodd-Frank Act
stress test methodology and results document.
Those differences are intended to facilitate the
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down amounts on loans purchased with
credit impairments.
III. Request for Comment
The Board requests comment on the
proposed enhanced disclosure of the
models used in the Federal Reserve’s
supervisory stress test. Where possible,
commenters should provide both
quantitative data and detailed analysis
in their comments. Commenters should
also explain the rationale for their
suggestions. Specifically, feedback is
requested on the following questions:
• Does the enhanced disclosure
appropriately balance the benefits and
costs of additional disclosure as
outlined above?
• Would the enhanced disclosure
allow the public, including academics,
to comment on the soundness of the
models and their alignment with best
modeling practices?
• Are there specific ways the
enhanced disclosures could be tailored
to limit the potential for increased
correlation of risks in the system?
• Are there additional disclosures
that would be more helpful to the public
without increasing the potential for
increased correlation of risks in the
system?
IV. Example of Enhanced Model
Disclosure
This section contains an illustrative
example of what an enhanced model
disclosure could look like for the
supervisory corporate loan model.
A. Enhanced Description of Models
Overview of Corporate Loan Model
Losses stemming from the default of
corporate loans are projected using a
model that assigns a specific loss
amount to each corporate loan held by
a firm subject to the supervisory stress
test. The model projects losses as the
product of three components:
Probability of default (PD), loss given
default (LGD), and exposure at default
(EAD). The PD component measures the
likelihood that a borrower will stop
repaying the loan. The other two
components capture the lender’s loss on
the loan if the borrower enters default.
stated goal of the proposed enhanced disclosure to
illustrate more clearly how the Federal Reserve’s
models translate firms’ portfolio characteristics and
the scenarios into loss rates.
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The LGD component measures the
percent of the loan balance that the
lender will not be able to recover after
the loan defaults, and the EAD
component measures the total expected
outstanding balance on the loan at the
time of default.
The model is estimated using
historical data on corporate loan losses,
loan characteristics, and economic
conditions. Losses are projected using
the estimated model, firm-reported loan
characteristics, and economic
conditions defined in the Federal
Reserve’s supervisory stress scenarios.
Some of the key loan characteristics that
affect projected losses include:
• The loan’s credit rating;
• The industry of the borrower;
• The country in which the borrower
is domiciled; and
• Whether or not the loan is secured.
The losses projected by the model for
a given loan vary based on changes in
the defined economic conditions over
the nine quarters of the projection
horizon. Those include:
• Growth in real gross domestic
product (GDP);
• Changes in the unemployment rate;
and
• Changes in the spread on BBB-rated
loans relative to Treasuries.
Loan Coverage and Model Structure
Corporate loans modeled using the
expected loss modeling framework
described in this document consist of a
number of different categories of loans,
as defined by the Consolidated
Financial Statements for Holding
Companies—FR Y–9C report. The
largest group of these loans includes
commercial and industrial (C&I) loans
with more than $1 million in committed
balances that are ‘‘graded’’ using a firm’s
corporate rating process. The corporate
loan model is designed to project
quarterly losses on those loans over the
projection horizon of each stress test
scenario.
Expected loss (EL) is the product of
the three components described above
(PD, LGD, and EAD), and for loan i in
quarter t of the projection horizon it can
be expressed as: 9
9 For example, if the probability of default is 1
percent, the loss given default is 20 percent, and the
expected outstanding balance at default is
$1,000,000 the expected loss is: EL =
0.01*0.20*1,000,000 = $2,000.
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stress test. The first set could be based
on the full sample of loans observed in
the data, the second could capture
characteristics associated with lowerthan-average risk loans, and the third
could capture characteristics associated
with higher-than-average risk loans.
Importantly, those portfolios would not
contain any individual firm’s actual
loan portfolio or any actual loans
reported by firms, but rather would be
portfolios of hypothetical loans
designed to illustrate the effect of loan
characteristics on estimated loss rates.
The set of variables included for each
portfolio would be designed such that
the public could independently estimate
loss rates for these portfolios, although
this set would not necessarily include
every variable that might be included in
a loss model for the relevant loan type.
The disclosure could also include the
loss rates estimated by the supervisory
models for each portfolio of
hypothetical loans under the
supervisory adverse and supervisory
severely adverse scenarios.
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Probability of Default
The PD model assumes that the
probability that a loan defaults depends
on macroeconomic factors, such as the
unemployment rate. The model first
calculates the loan’s PD at the beginning
of the projection horizon and then
projects it forward using the estimated
relationship between historical changes
in PD and changes in the
macroeconomic environment.10
Calculating the Initial PD: The initial
PD, which is the PD at the beginning of
the projection horizon (i.e., PD(i,t=0)), is
calculated as the long-run average of
daily expected default frequencies
(EDFs). EDFs are measures of the
probability of default based on a
Where bjk(m) is the estimated sensitivity
of the probability of default to
macroeconomic factor m, for countryindustry segment j and rating category k,
and S(t,m) is macroeconomic factor m in
period t.
Loss Given Default
Similar to the PD model, the LGD
model first calculates the loan’s LGD at
the beginning of the projection horizon
and then projects it forward using the
estimated relationship between
historical changes in LGD and changes
in the macroeconomic environment.
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Where F[·] denotes the standard normal
cumulative distribution function and
F¥1[·] is its inverse. LGD in period t
depends on PD in period t and on PD
and LGD in period t-1. If PD(i,t) = PD(i,t1), then LGD(i,t) = LGD(i,t-1).
Exposure at Default
For closed-end loans, the EAD is the
utilized exposure.
10 Loans that are 90 days past due, in non-accrual
status, or that have a Financial Accounting
Standards Board Accounting Standards
Codification Subtopic 310–10 (ASC 310–10) reserve
as of the reference date for the stress test are
considered in default.
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structural model that links the value of
a firm to credit risk. The initial PD for
publicly traded borrowers for which a
CUSIP is available in the firm-reported
data reflects a borrower-specific EDF.
The initial PD for other borrowers is
based on the average EDF for the
industry and rating category group in
which the borrower is classified. A
borrower’s industry category is directly
observed in the firm-reported data, and
the rating category is derived from the
firm-reported internal credit rating for
the borrower and a firm-reported table
that maps the internal rating to a
standardized rating scale.
Projecting the PD: The initial PDs are
then projected over the projection
horizon using equations fitted to the
historical relationship between changes
in the EDFs and changes in
macroeconomic variables. The
equations are estimated separately by
borrower industry, rating category, and
country of borrower domicile. The
macroeconomic variables used to
project changes in PDs over the
projection horizon are GDP growth,
changes in the unemployment rate, and
changes in the spread on BBB-rated
loans relative to Treasuries (BBB
spread). GDP growth and the rate of
unemployment reflect economy-wide
changes in demand for goods and
services which affect firms’ probabilities
of default, while the BBB spread
represents factors that affect firms’
profitability and investment
opportunities, such as aggregate credit
risk and the cost of borrowing.
For loan i, which is in countryindustry group j, and rating category k,
the change in PD from period t-1 to t is
given by:
Calculating the Initial LGD: Firmreported data on line of business and
whether the loan is secured or
unsecured are used to set the initial
LGD for performing loans. In cases in
which the loan has already been
identified as troubled, i.e., the firm has
already put aside a reserve to cover the
expected loss, the initial LGD is based
on the size of the reserve. Further
adjustments are made to the initial
LGDs of loans that are in default at
inception.11 For foreign loans, initial
LGDs are also adjusted based on the
country in which the obligor is
domiciled, capturing differences in
collateral recovery rates across
countries.
Projecting LGD: The LGD is then
projected forward by relating the change
in the LGD to changes in the PD
following Frye and Jacobs (2012).12
Under that approach, changes in LGD
are explicitly calculated as an increasing
function of PD. Specifically, loan i’s
LGD from period t–1 to period t is given
by:
For lines of credit and other revolving
commitments, the EAD equals the
utilized exposure plus a portion of the
unfunded commitment (i.e., the
difference between the committed
exposure and utilized exposure), which
reflects the amount that is likely to be
drawn down by the borrower in the
event of default. The amount that is
likely to be drawn down is calibrated to
the historical drawdown experience for
defaulted U.S. syndicated revolving
lines of credit that are in the Shared
National Credit (SNC) database.13
Formally, the EAD for a line of credit
or other revolving product i is set to:
11 Loans that are in default at inception of the
stress period (i.e., t=0) are assigned a PD of 100%,
and a LGD using the ASC 310–10 reserves reported
by the firm.
12 See, Frye, J., & Jacobs Jr, M. (2012). Credit loss
and systematic loss given default. The Journal of
Credit Risk, 8(1), 109.
13 SNC loans have commitments of greater than
$20 million and are held by three or more regulated
participating entities. For additional information,
see ‘‘Shared National Credit Program,’’ Board of
Governors of the Federal Reserve System,
www.federalreserve.gov/supervisionreg/snc.htm.
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Each of the three components is
modeled separately. The three
component models are described below.
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Where LEQ is the calibrated drawdown
amount, OB(i,t=0) is the line’s
outstanding exposure at the start of the
projection horizon, and CB(i,t=0) is the
line’s committed exposure at the start of
the projection horizon.
For standby letters of credit and trade
finance credits, EADs are conservatively
assumed to equal the total commitment,
since typically these types of credits are
fully drawn when they enter default
status.
TABLE 1—LIST OF KEY VARIABLES IN THE CORPORATE LOAN MODELS AND SOURCES OF VARIABLES
Variable
Description
Variable type
Source
PD model 1
U.S. BBB corporate yield spread ...
U.S. Real GDP growth ...................
U.S. unemployment rate ................
Country ..........................................
Industry of obligor ..........................
Internal obligor rating .....................
The difference between quarterly average of the yield on 10-year
BBB corporate bonds and quarterly average of the yield on 10year U.S. Treasury bonds.
Percent change in real gross domestic product in chained dollars, expressed at annualized rate.
Quarterly average of seasonally-adjusted monthly data for the unemployment rate of civilian, non-institutional population of age 16
years and older.
The two letter country code for the country in which the obligor is
headquartered.
Numeric code that describes the primary business activity of the obligor.
The obligor rating grade from the reporting entity’s internal risk rating
system.
Macroeconomic
FR supervisory
scenarios.
Macroeconomic
FR supervisory
scenarios.
FR supervisory
scenarios.
Macroeconomic
Loan/borrower
characteristic.
Loan/borrower
characteristic.
Loan/borrower
characteristic.
FR Y–14.
Loan/borrower
characteristic.
Loan/borrower
characteristic.
Loan/borrower
characteristic.
Loan/borrower
characteristic.
FR Y–14.
Loan/borrower
characteristic.
Loan/borrower
characteristic.
Loan/borrower
characteristic.
FR Y–14.
FR Y–14.
FR Y–14.
LGD model
Country ..........................................
Lien position ...................................
Line of business .............................
Type of facility ................................
The two letter country code for the country in which the obligor is
headquartered.
The type of lien. Options include first lien senior, second lien, senior
unsecured, or contractually subordinated.
The name of the internal line of business that originated the credit facility using the institution’s own department descriptions.
The type of credit facility. Potential types are defined in the FR Y–
14Q H.1 corporate schedule.
FR Y–14.
FR Y–14.
FR Y–14.
EAD model
Committed exposure amount .........
Type of facility ................................
Utilized exposure amount ..............
FR Y–14.
variables used to calculate initial loan status include days past due, non-accrual date, and ASC 310–10 amount.
B. Modeled Loss Rates on Pools of Loans
ethrower on DSK3G9T082PROD with PROPOSALS
FR Y–14
The output of the corporate loan
model is the expected loss on each loan.
As described above, estimated corporate
loan loss rates depend on a number of
variables. This section groups loans
according to three of the most important
variables in the model: Sector (financial
and nonfinancial), security status
(secured and unsecured), and rating
class (investment grade and noninvestment grade).14 Categorizing
14 Financial loans have a NAICS category (‘‘naics_
two_digit_cat’’) of 52; all other loans are marked
nonfinancial. Secured loans are defined as loans
with lien positions (‘‘lien_position_cat’’) marked as
‘‘first-lien senior’’; all other loans are marked as
unsecured. Investment grade loans are defined as
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corporate loans reported on schedule
H.1 of the FR Y–14Q report as of the
fourth quarter of 2016 by sector, security
status, and rating class results in eight
groups of loans: 15
• Financial, secured, investment grade
• Financial, secured, non-investment
grade
loans with a credit rating (‘‘rating’’) higher than and
including BBB; all other loans are marked as noninvestment grade.
15 The set of loans on which loss rates are
calculated excludes loans held for sale or accounted
for under the fair value option, loan observations
missing data fields used in the model, lines of
credit that were undrawn as of 2016:Q4, and other
types of loans that are not modeled using the
corporate loan model (e.g., loans to financial
depositories).
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• Financial, unsecured, investment
grade
• Financial, unsecured, non-investment
grade
• Nonfinancial, secured, investment
grade
• Nonfinancial, secured, noninvestment grade
• Nonfinancial, unsecured, investment
grade
• Nonfinancial, unsecured, noninvestment grade.
The remainder of this section reports
summary statistics and modeled loss
rates for these eight groups of corporate
loans.
Table 2 reports summary statistics for
the eight groups of loans. The summary
statistics cover a wide set of variables
E:\FR\FM\15DEP1.SGM
15DEP1
EP15DE17.002
1 Other
The current dollar amount the obligor is legally allowed to borrow according to the credit agreement.
The type of credit facility. Potential types are defined in the FR Y–
14Q H.1 corporate schedule.
The current dollar amount the obligor has drawn which has not been
repaid, net of any charge-offs, ASC 310–30 (originally issued as
SOP 03–03) adjustments, or fair value adjustments taken by the
reporting institution, but gross of ASC 310–10 reserve amounts.
59552
Federal Register / Vol. 82, No. 240 / Friday, December 15, 2017 / Proposed Rules
that capture important characteristics of
the loans and borrowers in the set of
loans.
Tables 3 and 4 show the modeled loss
rates for the eight groups of loans for the
DFAST 2017 supervisory severely
adverse and supervisory adverse
scenarios, respectively. Each entry in
the table shows the average (mean)
estimated loss rate for the loans in one
of the eight groups, as well as the 25th
and 75th percentiles of the estimated
loss rates.
ranges of loss rates. For example, among
secured, non-investment grade loans,
the loss rates shown in Table 3 range
from 8.7 to 12.1 for financial firms, but
range from 2.7 to 9.8 for nonfinancial
firms, which include a wider variety of
industries. Secured, non-investment
grade loans to nonfinancial firms are
predominantly loans to firms in the
manufacturing, transportation, and
technology sectors, but also include
loans to firms in other sectors like
education and utilities (Table 2).
Certain groups of loans generally have
wider ranges of losses than other
groups. Although the loans are grouped
according to the most important
characteristics in the model, other loan
characteristics in the model also affect
loss rates, albeit in more limited
manner. Differences in these other
characteristics within each loan group
are responsible for the range of loss rates
shown in the tables. Greater variation in
these other characteristics within a
group will generally lead to larger
TABLE 2—SUMMARY STATISTICS OF SELECTED VARIABLES IN THE CORPORATE LOAN DATA GROUPED BY LOAN AND
BORROWER CHARACTERISTICS 1
[Percent, except as noted]
Non-investment grade
Variables
Nonfinancial sector
Unsecured
Number of loans (thousands) ...........................
15.60
Investment grade
Financial sector
Secured
Unsecured
101.80
1.28
Nonfinancial sector
Secured
Unsecured
8.20
Secured
Financial sector
Unsecured
Secured
21.34
52.80
2.11
5.91
32.27
44.48
23.25
37.17
42.20
20.63
51.78
35.54
12.67
71.39
14.57
14.04
1.22
6.55
22.23
70.00
0.00
0.00
0.00
0.92
7.17
23.63
68.28
0.00
0.00
0.00
3.36
12.12
25.16
59.35
0.00
0.00
0.00
4.89
11.05
39.80
44.26
0.00
0.00
0.00
0.00
98.26
1.74
100.00
0.00
0.00
0.00
98.75
1.25
100.00
0.00
0.00
24.93
68.75
6.22
27.97
68.72
2.74
17.69
77.52
4.73
6.92
90.21
2.74
Facility type, share of utilized balance
Revolving .........................
Term loan .........................
Other ................................
37.14
45.06
17.80
41.52
40.33
18.15
33.37
34.08
32.55
45.28
20.83
33.89
Credit rating, share of utilized balance
AAA ..................................
AA ....................................
A .......................................
BBB ..................................
BB ....................................
B .......................................
CCC or below ..................
0.00
0.00
0.00
0.00
80.06
19.63
0.31
0.00
0.00
0.00
0.00
76.66
22.28
1.07
0.00
0.00
0.00
0.00
88.97
10.89
0.14
0.00
0.00
0.00
0.00
81.82
18.05
0.13
Lien position, share of utilized balance
First-lien senior ................
Senior unsecured .............
Other ................................
0.00
95.10
4.90
100.00
0.00
0.00
0.00
98.51
1.49
100.00
0.00
0.00
Interest rate variability, share of utilized balance
Fixed ................................
Floating ............................
Mixed ................................
23.04
71.61
5.33
14.45
79.99
5.54
13.11
81.29
5.59
6.17
88.65
5.15
ethrower on DSK3G9T082PROD with PROPOSALS
Industry, share of utilized balance 2
Agriculture, fishing, and
hunting ..........................
Natural resources, utilities,
and construction ...........
Manufacturing ..................
Trade and transportation
Technological and business services ................
Finance and insurance ....
Education, health care,
and social assistance ...
Entertainment and lodging
Other services ..................
0.66
1.50
0.00
0.00
0.28
0.50
0.00
0.00
13.02
25.70
28.30
7.92
18.82
32.57
0.00
0.00
0.00
0.00
0.00
0.00
8.89
28.19
15.95
5.21
13.73
29.17
0.00
0.00
0.00
0.00
0.00
0.00
22.28
0.00
22.18
0.00
0.00
100.00
0.00
100.00
28.91
0.00
19.54
0.00
0.00
100.00
0.00
100.00
3.76
2.46
3.82
6.45
6.06
4.49
0.00
0.00
0.00
0.00
0.00
0.00
8.08
2.13
7.57
13.84
4.39
13.62
0.00
0.00
0.00
0.00
0.00
0.00
30.23
29.95
42.22
12.02
Guarantor flag, share of utilized balance
Full guarantee ..................
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TABLE 2—SUMMARY STATISTICS OF SELECTED VARIABLES IN THE CORPORATE LOAN DATA GROUPED BY LOAN AND
BORROWER CHARACTERISTICS 1—Continued
[Percent, except as noted]
Non-investment grade
Variables
Nonfinancial sector
Unsecured
U.S. government guarantee .............................
Partial guarantee ..............
No guarantee ...................
Domestic obligor, share of
utilized balance .............
Remaining maturity, average in months 3 4 ..........
Interest rate, average in
percent 4 .......................
Committed exposure, average in millions of dollars ................................
Utilized exposure, average in millions of dollars
Investment grade
Financial sector
Secured
Unsecured
Nonfinancial sector
Secured
Unsecured
Secured
Financial sector
Unsecured
Secured
5.03
2.62
51.11
0.18
4.23
53.74
0.23
3.09
54.47
0.03
3.28
67.60
0.52
1.77
67.49
0.26
2.41
67.31
0.00
3.86
53.92
0.00
4.99
82.99
63.53
91.35
65.10
72.29
71.58
91.46
65.93
81.37
38.34
48.44
28.95
23.89
38.26
57.59
38.55
30.44
2.77
3.24
2.36
2.68
2.17
2.48
2.26
2.32
15.24
8.32
25.22
17.43
24.79
10.81
43.24
57.37
10.89
6.17
19.89
14.17
16.46
8.35
28.36
39.64
1 The
set of loans presented in this table excludes loans held for sale or accounted for under the fair value option, loan observations missing
data fields used in the model, lines of credit that were undrawn as of 2016:Q4, and other types of loans that are not modeled using the corporate
loan model (e.g., loans to financial depositories).
2 Industries are collapsed using the first digit of the NAICS 2007 code, except for finance and insurance.
3 Maturity excludes demand loans.
4 Averages for remaining maturity and interest rate are weighted by utilized exposure.
TABLE 3—PROJECTED AVERAGE LOAN LOSS RATES AND 25TH AND 75TH PERCENTILE RANGES BY LOAN AND BORROWER
CHARACTERISTICS, 2017:Q1–2019:Q1, DFAST 2017 SEVERELY ADVERSE SCENARIO
Sector
Security status
Rating class
Financial ...............................................
Financial ...............................................
Financial ...............................................
Financial ...............................................
Nonfinancial .........................................
Nonfinancial .........................................
Nonfinancial .........................................
Nonfinancial .........................................
Secured ...............................................
Secured ...............................................
Unsecured ...........................................
Unsecured ...........................................
Secured ...............................................
Secured ...............................................
Unsecured ...........................................
Unsecured ...........................................
Investment grade .................................
Non-investment grade .........................
Investment grade .................................
Non-investment grade .........................
Investment grade .................................
Non-investment grade .........................
Investment grade .................................
Non-investment grade .........................
Loss rates (percent)
2.5 [1.6 to 3.3].
10.4 [8.7 to 12.1].
3.3 [1.9 to 5.3].
12.6 [8.3 to 17.0].
0.8 [0.3 to 1.0].
5.4 [2.7 to 9.8].
1.2 [0.5 to 1.7].
6.0 [3.6 to 11.7].
Note: Loan-level loss rates are calculated as cumulative nine-quarter losses on a given loan divided by initial utilized balance on that loan. Average loss rates reported in the table are the average of the loan-level loss rates weighted by initial utilized balances. The set of loans on which
loss rates are calculated excludes loans held for sale or accounted for under the fair value option, loan observations missing data fields used in
the model, lines of credit that were undrawn as of 2016:Q4, and other types of loans that are not modeled using the corporate loan model (e.g.,
loans to financial depositories).
TABLE 4—PROJECTED AVERAGE LOAN LOSS RATES AND 25TH AND 75TH PERCENTILE RANGES BY LOAN AND BORROWER
CHARACTERISTICS, 2017:Q1–2019:Q1, DFAST 2017 ADVERSE SCENARIO
Security status
Rating class
Financial ...............................................
Financial ...............................................
Financial ...............................................
Financial ...............................................
Nonfinancial .........................................
Nonfinancial .........................................
Nonfinancial .........................................
Nonfinancial .........................................
ethrower on DSK3G9T082PROD with PROPOSALS
Sector
Secured ...............................................
Secured ...............................................
Unsecured ...........................................
Unsecured ...........................................
Secured ...............................................
Secured ...............................................
Unsecured ...........................................
Unsecured ...........................................
Investment grade .................................
Non-investment grade .........................
Investment grade .................................
Non-investment grade .........................
Investment grade .................................
Non-investment grade .........................
Investment grade .................................
Non-investment grade .........................
Loss rates (percent)
1.5
5.9
2.0
7.3
0.5
3.2
0.8
3.7
[1.0
[4.7
[1.2
[4.7
[0.2
[1.6
[0.4
[2.1
to
to
to
to
to
to
to
to
2.0].
6.7].
3.3].
9.8].
0.6].
5.8].
1.1].
7.1].
Note: Loan-level loss rates are calculated as cumulative nine-quarter losses on a given loan divided by initial utilized balance on that loan. Average loss rates reported in the table are the average of the loan-level loss rates weighted by initial utilized balances. The set of loans on which
loss rates are calculated excludes loans held for sale or accounted for under the fair value option, loan observations missing data fields used in
the model, lines of credit that were undrawn as of 2016:Q4, and other types of loans that are not modeled using the corporate loan model (e.g.,
loans to financial depositories).
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Federal Register / Vol. 82, No. 240 / Friday, December 15, 2017 / Proposed Rules
C. Portfolios of Hypothetical Loans and
Associated Loss Rates
The effect of borrower and loan
characteristics on the losses estimated
by the corporate loan model can also be
illustrated by the differences in the
estimated loss rate on specific sets of
hypothetical loans. This section
contains descriptive statistics from three
portfolios of hypothetical loans (Table
6) and the modeled loss rates for the
three portfolios under the DFAST 2017
supervisory adverse and supervisory
severely adverse scenarios (Table 7).
The portfolios of hypothetical loans
are designed to have characteristics
similar to the actual loans reported in
schedule H.1 of the FR Y–14Q report.
Three portfolios containing 200 loans
each are provided, and they are
designed to capture characteristics
associated with:
1. Typical set of loans reported in the
FR Y–14Q;
2. Higher-than-average-risk loans (in
this case, non-investment grade loans);
and,
3. Lower-than-average-risk loans (in
this case, investment grade loans).
The portfolios of hypothetical loans
include 12 variables that describe
characteristics of corporate loans that
are generally used to estimate corporate
loan losses (Table 5).16
Table 6 contains summary statistics
for the portfolios of hypothetical loans
in the same format as Table 2. The
portfolios of hypothetical loans are
constructed to capture characteristics of
certain sets of loans, but are not fully
representative of the population of loans
reported in Table 2. Table 7 contains the
loss rates for the portfolios of
hypothetical loans calculated under the
DFAST 2017 supervisory severely
adverse and supervisory adverse
scenarios. The rank ordering of the loss
rates is consistent with the ranges of
loss rates reported in Tables 3 and 4.
The portfolio of higher-risk loans has
higher loss rates under both the severely
adverse and adverse scenarios and is
also more sensitive to changes in
macroeconomic conditions (loss rate of
7.2 percent in the severely adverse
scenario and 4.2 percent in the adverse
scenario) than the portfolio of typical
loans (loss rate of 5.4 percent in the
severely adverse scenario and 3.2
percent in the adverse scenario).
Conversely, the portfolio of lower-risk
loans has lower losses under both
scenarios, and is less sensitive to
changes in macroeconomic conditions
(loss rate of 1.8 percent in the severely
adverse scenario and 1.1 percent in the
adverse scenario).
TABLE 5—LIST OF VARIABLES INCLUDED IN PORTFOLIOS OF HYPOTHETICAL LOANS
Variable
Mnemonic
Description
Origination year ...............................
Type of facility ..................................
orig_year ........................................
facility_type_cat .............................
Lien position .....................................
lien_position_cat ............................
Credit rating .....................................
rating ..............................................
Domestic flag ...................................
Industry code (2-digit) ......................
Committed exposure amount ..........
Utilized exposure amount ................
Interest rate ......................................
Interest rate variability .....................
domestic_flag ................................
naics_two_digit_cat ........................
committed_exposure_amt .............
utilized_exposure_amt ...................
interest_rate ...................................
interest_rate_variability ..................
Remaining maturity ..........................
Guarantor flag ..................................
term ...............................................
guarantor_flag ...............................
Year loan was originated.
The type of credit facility.
1 is revolving;
5 is non-revolving; and
0 is other.
The type of lien.
1 is first-lien senior;
2 is second-lien;
3 is senior unsecured; and,
4 is contractually subordinated.
Credit rating of obligor. Categories include AAA, AA, A, BBB, BB, B,
CCC, CC, C, and D.
Equal to 1 if obligor is domiciled in the U.S.
Two-digit industry code based on 2007 NAICS definitions.
Committed exposure in dollars.
Utilized exposure in dollars.
Interest rate on credit facility.
Interest rate type.
0 is fully undrawn (interest rate not provided);
1 is fixed;
2 is floating;
3 is mixed.
Remaining term of the loan in months.
Indicates the type of guarantee of the guarantor.
1 is full guarantee;
2 is partial guarantee;
3 is U.S. government agency guarantee;
4 is no guarantee.
Note: Some of the variables included in the portfolios of hypothetical loans are presented in a more aggregated form than they are reported in
the FR Y–14.
TABLE 6—SUMMARY STATISTICS OF SELECTED VARIABLES IN THE PORTFOLIOS OF HYPOTHETICAL LOANS
ethrower on DSK3G9T082PROD with PROPOSALS
[Percent, except as noted]
Variables
Higher-risk
Lower-risk
Typical
Facility type, share of utilized balance
Revolving .....................................................................................................................................
Term loan .....................................................................................................................................
16 The sets of loans are available for download on
the Federal Reserve’s website: Higher-than-averagerisk loans (https://www.federalreserve.gov/
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typical-risk loans (https://www.federalreserve.gov/
newsevents/pressreleases/files/Typical.csv); and
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36.52
42.67
46.02
39.97
50.77
33.32
lower-than-average-risk loans (https://
www.federalreserve.gov/newsevents/pressreleases/
files/LowerRisk.csv).
E:\FR\FM\15DEP1.SGM
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Federal Register / Vol. 82, No. 240 / Friday, December 15, 2017 / Proposed Rules
TABLE 6—SUMMARY STATISTICS OF SELECTED VARIABLES IN THE PORTFOLIOS OF HYPOTHETICAL LOANS—Continued
[Percent, except as noted]
Variables
Higher-risk
Other ............................................................................................................................................
Lower-risk
Typical
20.81
14.02
15.91
0.00
0.00
0.00
0.00
78.68
20.85
0.47
0.00
6.79
9.72
83.49
0.00
0.00
0.00
0.45
1.06
4.48
41.32
40.91
10.57
1.21
82.79
17.21
0.00
61.31
38.69
0.00
76.61
23.39
0.00
16.26
83.44
0.30
26.36
71.99
1.64
11.72
86.04
2.24
0.42
10.71
15.46
19.30
26.36
16.36
6.40
1.96
3.03
0.00
9.34
5.26
31.32
11.52
15.51
7.67
1.66
17.73
0.16
4.03
18.96
20.64
13.74
20.15
7.05
1.52
13.75
41.61
1.50
1.57
55.32
93.88
48.57
3.33
7.87
5.76
50.93
0.00
0.06
49.01
82.34
56.35
2.75
17.94
7.35
32.40
0.38
2.15
65.08
94.64
39.23
2.87
17.47
5.86
Credit rating, share of utilized balance
AAA ..............................................................................................................................................
AA ................................................................................................................................................
A ...................................................................................................................................................
BBB ..............................................................................................................................................
BB ................................................................................................................................................
B ...................................................................................................................................................
CCC or below ..............................................................................................................................
Lien position, share of utilized balance
First-lien senior ............................................................................................................................
Senior unsecured .........................................................................................................................
Other ............................................................................................................................................
Interest rate variability, share of utilized balance
Fixed ............................................................................................................................................
Floating ........................................................................................................................................
Mixed ...........................................................................................................................................
Industry, share of utilized balance 1
Agriculture, fishing, and hunting ..................................................................................................
Natural resources, utilities, and construction ..............................................................................
Manufacturing ..............................................................................................................................
Trade and transportation .............................................................................................................
Technological and business services ..........................................................................................
Finance and insurance ................................................................................................................
Education, health care, and social assistance ............................................................................
Entertainment and lodging ...........................................................................................................
Other services ..............................................................................................................................
Guarantor flag, share of utilized balance
Full guarantee ..............................................................................................................................
U.S. government guarantee ........................................................................................................
Partial guarantee .........................................................................................................................
No guarantee ...............................................................................................................................
Domestic obligor, share of utilized balance ................................................................................
Remaining maturity, average in months 2 3 .................................................................................
Interest rate, average in percentage 3 .........................................................................................
Committed exposure, average in millions of dollars ...................................................................
Utilized exposure, average in millions of dollars .........................................................................
1 Industries
are collapsed using the first digit of the NAICS 2007 code, except for finance and insurance.
excludes demand loans.
3 Averages for remaining maturity and interest rate are weighted by utilized exposure.
2 Maturity
TABLE 7—PROJECTED PORTFOLIO
LOSS RATES, 2017:Q1–2019:Q1,
DFAST 2017 SCENARIOS
[Percent]
By Order of the Board of Governors of the
Federal Reserve System, December 7, 2017.
Ann E. Misback,
Secretary of the Board.
[FR Doc. 2017–26856 Filed 12–14–17; 8:45 am]
Scenario
ethrower on DSK3G9T082PROD with PROPOSALS
Hypothetical portfolio
Severely
adverse
Typical ......................
Lower-risk .................
Higher-risk ................
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Aerospace Limited Airplanes
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1.1
4.2
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RIN 2120–AA64
Federal Aviation
Administration (FAA), Department of
Transportation (DOT).
ACTION: Notice of proposed rulemaking
(NPRM).
AGENCY:
Note: Portfolio loss rates are calculated as
sum of the cumulative nine-quarter losses divided by sum of initial utilized balances.
VerDate Sep<11>2014
Federal Aviation Administration
[Docket No. FAA–2017–1184; Product
Identifier 2017–CE–029–AD]
BILLING CODE 6210–01–P
Adverse
5.4
1.8
7.2
DEPARTMENT OF TRANSPORTATION
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Agencies
[Federal Register Volume 82, Number 240 (Friday, December 15, 2017)]
[Proposed Rules]
[Pages 59547-59555]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2017-26856]
-----------------------------------------------------------------------
FEDERAL RESERVE SYSTEM
12 CFR Chapter II
[Docket No. OP-1586]
Enhanced Disclosure of the Models Used in the Federal Reserve's
Supervisory Stress Test
AGENCY: Board of Governors of the Federal Reserve System (Board).
ACTION: Notification with request for public comment.
-----------------------------------------------------------------------
SUMMARY: The Board is inviting comment on an enhanced disclosure of the
models used in the Federal Reserve's supervisory stress test conducted
under the Board's Regulation YY pursuant to the Dodd-Frank Wall Street
Reform and Consumer Protection Act (Dodd-Frank Act) and the Board's
capital plan rule.
DATES: Comments must be received by January 22, 2018.
ADDRESSES: You may submit comments, identified by Docket No. OP-1586 by
any of the following methods:
Agency website: https://www.federalreserve.gov. Follow the
instructions for submitting comments at https://www.federalreserve.gov/generalinfo/foia/ProposedRegs.aspx.
Federal eRulemaking Portal: https://www.regulations.gov.
Follow the instructions for submitting comments.
Email: [email protected]. Include the
docket number and RIN number in the subject line of the message.
Fax: (202) 452-2819 or (202) 452-3102.
Mail: Ann Misback, Secretary, Board of Governors of the
Federal Reserve System, 20th Street and Constitution Avenue NW,
Washington, DC 20551.
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SUPPLEMENTARY INFORMATION:
Table of Contents
I. Overview
II. Description of Enhanced Model Disclosure
A. Enhanced Description of Models
B. Modeled Loss Rates on Pools of Loans
C. Portfolios of Hypothetical Loans and Associated Loss Rates
D. Explanatory Notes on Enhanced Model Disclosures
III. Request for Comment
IV. Example of Enhanced Model Disclosure
A. Enhanced Description of Models
B. Modeled Loss Rates on Pools of Loans
C. Portfolios of Hypothetical Loans and Associated Loss Rates
I. Overview
Each year the Federal Reserve publicly discloses the results of the
supervisory stress test.\1\ The disclosures include revenues, expenses,
losses, pre-tax net income, and capital ratios that would result under
two sets of adverse economic and financial conditions. As part of the
disclosures, the Federal Reserve also describes the broad framework and
methodology used in the supervisory stress test, including information
about the models used to estimate the revenues, losses, and capital
ratios in the stress test. The annual disclosures of both the stress
test results and supervisory model framework and methodology represent
a significant increase in the public transparency of large bank
supervision in the U.S.\2\ Indeed, prior to the first supervisory
stress test in 2009, many analysts and institutions cautioned against
these disclosures, arguing that releasing bank-specific loss estimates
to the public would be destabilizing. However, experience to date has
shown the opposite to be true--disclosing these details to the public
has garnered public and market confidence in the process.
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\1\ See, for example, Dodd-Frank Act Stress Test 2017:
Supervisory Stress Test Methodology and Results, June 2017 and
Comprehensive Capital Analysis and Review 2017: Assessment Framework
and Results, June 2017.
\2\ In addition to those public disclosures, the Federal Reserve
has published detailed information about its scenario design
framework and annual letters detailing material model changes. The
Federal Reserve also hosts an annual symposium in which supervisors
and financial industry practitioners share best practices in
modeling, model risk management, and governance.
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The Federal Reserve routinely reviews its stress testing and
capital planning programs, and during those reviews the Federal Reserve
has received feedback regarding the transparency of the supervisory
stress test models.\3\ Some of those providing feedback requested more
detail on modeling methodologies with a focus on year-over-year changes
in the supervisory models.\4\ Others, however, cautioned against
disclosing too much information about the supervisory models because
doing so could permit firms to reverse-engineer the stress test.
---------------------------------------------------------------------------
\3\ During a review that began in 2015, the Federal Reserve
received feedback from senior management at firms subject to the
Board's capital plan rule, debt and equity market analysts,
representatives from public interest groups, and academics in the
fields of economics and finance. That review also included an
internal assessment.
\4\ Some of the comments in favor of additional disclosure
included requests that the Federal Reserve provide additional
information to firms only, without making the additional disclosures
public. Doing so would be contrary to the Federal Reserve's
established practice of not disclosing information related to the
stress test to firms if that information is not also publicly
disclosed.
---------------------------------------------------------------------------
The Federal Reserve recognizes that disclosing additional
information about supervisory models and methodologies has significant
public benefits, and is committed to finding ways to further increase
the transparency of the supervisory stress test. More detailed
disclosures could further enhance the credibility of the stress test by
providing the public with information on the fundamental soundness of
the models and their alignment with best modeling practices. These
disclosures would also facilitate comments on the models from the
public, including academic experts. These comments could lead to
improvements, particularly in the data most useful to understanding the
risks of particular loan types. More detailed disclosures could also
help the public understand and interpret the results of the stress
test, furthering the goal of maintaining market and public confidence
in the U.S. financial system. Finally, more detailed disclosures of how
the Federal Reserve's models assign losses to particular positions
[[Page 59548]]
could help those financial institutions that are subject to the stress
test understand the capital implications of changes to their business
activities, such as acquiring or selling a portfolio of assets.
The Federal Reserve also believes there are material risks
associated with fully disclosing the models to the firms subject to the
supervisory stress test. One implication of releasing all details of
the models is that firms could conceivably use them to make
modifications to their businesses that change the results of the stress
test without changing the risks they face. In the presence of such
behavior, the stress test could give a misleading picture of the actual
vulnerabilities faced by firms. Further, such behavior could increase
correlations in asset holdings among the largest banks, making the
financial system more vulnerable to adverse financial shocks.\5\
Another implication is that full model disclosure could incent banks to
simply use models similar to the Federal Reserve's, rather than build
their own capacity to identify, measure, and manage risk. That
convergence to the Federal Reserve's model would create a ``model
monoculture,'' in which all firms have similar internal stress testing
models which may miss key idiosyncratic risks faced by the firms.\6\
---------------------------------------------------------------------------
\5\ For example, if firms were to deem a specific asset as more
advantageous to hold based on the particulars of the supervisory
models, were an exogenous shock to occur to that specific asset
class, the firms' losses would be magnified because they held
correlated assets.
\6\ See, Schuermann, T. (March 19, 2013). The Fed's Stress Tests
Add Risk to the Financial System. Wall Street Journal, which
highlights bank incentives to mimic Federal Reserve's stress test
models.
---------------------------------------------------------------------------
In the next section of the paper, three proposed enhancements to
the supervisory stress test model disclosures are described, with an
example of the enhanced disclosure for the Federal Reserve's corporate
loan loss model. If the proposed enhancements were implemented, the
Federal Reserve would expect to publish the enhanced disclosures in the
first quarter of each year, starting with selected loan portfolios in
2018. The Federal Reserve expects that the annual disclosure would
reflect any updates to supervisory models, for applicable portfolios,
in a given year, but would be based on data and scenarios from the
prior year.
The proposed enhancements are designed to balance the costs and
benefits discussed above in a way that would further enhance the
public's understanding of the supervisory stress test models without
undermining the effectiveness of the stress test as a supervisory tool.
II. Description of Enhanced Model Disclosure
The proposed enhanced disclosures have three components: (1)
Enhanced descriptions of supervisory models, including key variables;
(2) modeled loss rates on loans grouped by important risk
characteristics and summary statistics associated with the loans in
each group; and, (3) portfolios of hypothetical loans and the estimated
loss rates associated with the loans in each portfolio.\7\
---------------------------------------------------------------------------
\7\ The second and third components would be provided for the
models used to project losses on the most material loan portfolios.
---------------------------------------------------------------------------
Collectively, the additional information is designed to facilitate
the public's ability to understand the workings of the models and
provide meaningful feedback.
A. Enhanced Description of Models
The Federal Reserve currently discloses descriptions of the
supervisory stress test models in an appendix in the annual Dodd-Frank
Act supervisory stress test methodology and results document. For each
modeling area, the appendix includes a description of the structure of
the model, key features, and the most important explanatory variables
in the model.
The proposed enhanced descriptions of the models would expand these
descriptions in two ways. First, they would provide more detailed
information about the structure of the models. For example, the
existing disclosure for corporate loans explains that the model
estimates expected losses using models of probability of default (PD),
loss given default (LGD), and exposure at default (EAD). It further
explains that PDs are projected using a series of equations fitted to
the historical relationship between changes in the PD and macroeconomic
variables, including growth in real gross domestic product, changes in
the unemployment rate, and changes in the spread on BBB-rated corporate
bonds. The proposed enhanced model description would include certain
important equations that characterize aspects of the model. Second, the
proposed enhanced descriptions would include a table that contains a
list of the key loan characteristics and macroeconomic variables that
influence the results of a given model. The table would show the
relevant variables for each component of the model (e.g., PD, LGD,
EAD), and information about the source of the variables (see Table 1).
B. Modeled Loss Rates on Pools of Loans
The proposed enhanced disclosure would include estimated loss rates
for groups of loans with distinct characteristics. Those loss rates
would allow the public to directly see how the supervisory models treat
specific assets under stress. The corporate loan example included below
illustrates how this new loss rate disclosure could operate in
practice. The modeled loss rates are reported for eight groups of loans
that have combinations of three loan characteristics: sector (financial
and nonfinancial), security status (secured and unsecured), and rating
class (investment grade and non-investment grade). The average (mean)
estimated loss rate and 25th and 75th percentiles of the estimated
loan-level loss rates are presented for each group of loans. By
presenting the modeled loss rates in ranges as well as the average for
each group, the disclosure highlights that loans within the same group
may have different loss rates because of differences in other risk
characteristics. For example, nonfinancial sector loans would include
loans to companies in a range of sectors, which may have different
sensitivities to the macroeconomic environment associated with any
given scenario.
To shed more light on the degree of heterogeneity of loans within a
given group, the enhanced disclosure could also include summary
statistics associated with the loans in each group. Combined, the
modeled loss rates and summary statistics would allow a firm to compare
the characteristics of its own portfolio to those of the aggregate
portfolio for all firms subject to the stress test and to better
understand differences in loss rates between the two. The modeled loss
rates could be reported for both the supervisory adverse and
supervisory severely adverse scenarios, which would help to illustrate
the effect of variation in macroeconomic conditions on modeled loss
rates.
C. Portfolios of Hypothetical Loans and Associated Loss Rates
Publishing portfolios of hypothetical loans is another way to
enhance transparency. This approach would allow outside parties to use
their own suites of models to estimate losses on the portfolios and
compare loss rates across different models.
The portfolios the Federal Reserve may publish for certain asset
classes could comprise three sets of hypothetical loans designed to
mimic the characteristics of the actual loans reported by firms
participating in the
[[Page 59549]]
stress test. The first set could be based on the full sample of loans
observed in the data, the second could capture characteristics
associated with lower-than-average risk loans, and the third could
capture characteristics associated with higher-than-average risk loans.
Importantly, those portfolios would not contain any individual firm's
actual loan portfolio or any actual loans reported by firms, but rather
would be portfolios of hypothetical loans designed to illustrate the
effect of loan characteristics on estimated loss rates. The set of
variables included for each portfolio would be designed such that the
public could independently estimate loss rates for these portfolios,
although this set would not necessarily include every variable that
might be included in a loss model for the relevant loan type. The
disclosure could also include the loss rates estimated by the
supervisory models for each portfolio of hypothetical loans under the
supervisory adverse and supervisory severely adverse scenarios.
D. Explanatory Notes on Enhanced Model Disclosures \8\
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\8\ This section highlights definitional differences between the
proposed enhanced disclosures and the loss rate disclosures in the
annual Dodd-Frank Act stress test methodology and results document.
Those differences are intended to facilitate the stated goal of the
proposed enhanced disclosure to illustrate more clearly how the
Federal Reserve's models translate firms' portfolio characteristics
and the scenarios into loss rates.
---------------------------------------------------------------------------
The proposed enhanced model disclosures described in this document
focus on the design of and projections from particular models, whereas
the current disclosures of supervisory stress test results include
projections aggregated to the portfolio level that in most cases
contain the outputs from multiple supervisory models. As such, the two
different disclosures will not align exactly.
The proposed enhanced model disclosures would also differ from the
current stress testing results disclosures in that they would not
include accounting and other adjustments used to translate projected
credit losses into net income. In the current supervisory stress test
results disclosure, accounting adjustments are used to translate
supervisory model estimates into provisions and other income or expense
items needed to calculate stressed pre-tax net income. These
adjustments often depend on factors that vary across participating
banks, such as the write-down amounts on loans purchased with credit
impairments.
III. Request for Comment
The Board requests comment on the proposed enhanced disclosure of
the models used in the Federal Reserve's supervisory stress test. Where
possible, commenters should provide both quantitative data and detailed
analysis in their comments. Commenters should also explain the
rationale for their suggestions. Specifically, feedback is requested on
the following questions:
Does the enhanced disclosure appropriately balance the
benefits and costs of additional disclosure as outlined above?
Would the enhanced disclosure allow the public, including
academics, to comment on the soundness of the models and their
alignment with best modeling practices?
Are there specific ways the enhanced disclosures could be
tailored to limit the potential for increased correlation of risks in
the system?
Are there additional disclosures that would be more
helpful to the public without increasing the potential for increased
correlation of risks in the system?
IV. Example of Enhanced Model Disclosure
This section contains an illustrative example of what an enhanced
model disclosure could look like for the supervisory corporate loan
model.
A. Enhanced Description of Models
Overview of Corporate Loan Model
Losses stemming from the default of corporate loans are projected
using a model that assigns a specific loss amount to each corporate
loan held by a firm subject to the supervisory stress test. The model
projects losses as the product of three components: Probability of
default (PD), loss given default (LGD), and exposure at default (EAD).
The PD component measures the likelihood that a borrower will stop
repaying the loan. The other two components capture the lender's loss
on the loan if the borrower enters default. The LGD component measures
the percent of the loan balance that the lender will not be able to
recover after the loan defaults, and the EAD component measures the
total expected outstanding balance on the loan at the time of default.
The model is estimated using historical data on corporate loan
losses, loan characteristics, and economic conditions. Losses are
projected using the estimated model, firm-reported loan
characteristics, and economic conditions defined in the Federal
Reserve's supervisory stress scenarios. Some of the key loan
characteristics that affect projected losses include:
The loan's credit rating;
The industry of the borrower;
The country in which the borrower is domiciled; and
Whether or not the loan is secured.
The losses projected by the model for a given loan vary based on
changes in the defined economic conditions over the nine quarters of
the projection horizon. Those include:
Growth in real gross domestic product (GDP);
Changes in the unemployment rate; and
Changes in the spread on BBB-rated loans relative to
Treasuries.
Loan Coverage and Model Structure
Corporate loans modeled using the expected loss modeling framework
described in this document consist of a number of different categories
of loans, as defined by the Consolidated Financial Statements for
Holding Companies--FR Y-9C report. The largest group of these loans
includes commercial and industrial (C&I) loans with more than $1
million in committed balances that are ``graded'' using a firm's
corporate rating process. The corporate loan model is designed to
project quarterly losses on those loans over the projection horizon of
each stress test scenario.
Expected loss (EL) is the product of the three components described
above (PD, LGD, and EAD), and for loan i in quarter t of the projection
horizon it can be expressed as: \9\
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\9\ For example, if the probability of default is 1 percent, the
loss given default is 20 percent, and the expected outstanding
balance at default is $1,000,000 the expected loss is: EL =
0.01*0.20*1,000,000 = $2,000.
[GRAPHIC] [TIFF OMITTED] TP15DE17.083
[[Page 59550]]
Each of the three components is modeled separately. The three
component models are described below.
Probability of Default
The PD model assumes that the probability that a loan defaults
depends on macroeconomic factors, such as the unemployment rate. The
model first calculates the loan's PD at the beginning of the projection
horizon and then projects it forward using the estimated relationship
between historical changes in PD and changes in the macroeconomic
environment.\10\
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\10\ Loans that are 90 days past due, in non-accrual status, or
that have a Financial Accounting Standards Board Accounting
Standards Codification Subtopic 310-10 (ASC 310-10) reserve as of
the reference date for the stress test are considered in default.
---------------------------------------------------------------------------
Calculating the Initial PD: The initial PD, which is the PD at the
beginning of the projection horizon (i.e., PD(i,t=0)), is calculated as
the long-run average of daily expected default frequencies (EDFs). EDFs
are measures of the probability of default based on a structural model
that links the value of a firm to credit risk. The initial PD for
publicly traded borrowers for which a CUSIP is available in the firm-
reported data reflects a borrower-specific EDF. The initial PD for
other borrowers is based on the average EDF for the industry and rating
category group in which the borrower is classified. A borrower's
industry category is directly observed in the firm-reported data, and
the rating category is derived from the firm-reported internal credit
rating for the borrower and a firm-reported table that maps the
internal rating to a standardized rating scale.
Projecting the PD: The initial PDs are then projected over the
projection horizon using equations fitted to the historical
relationship between changes in the EDFs and changes in macroeconomic
variables. The equations are estimated separately by borrower industry,
rating category, and country of borrower domicile. The macroeconomic
variables used to project changes in PDs over the projection horizon
are GDP growth, changes in the unemployment rate, and changes in the
spread on BBB-rated loans relative to Treasuries (BBB spread). GDP
growth and the rate of unemployment reflect economy-wide changes in
demand for goods and services which affect firms' probabilities of
default, while the BBB spread represents factors that affect firms'
profitability and investment opportunities, such as aggregate credit
risk and the cost of borrowing.
For loan i, which is in country-industry group j, and rating
category k, the change in PD from period t-1 to t is given by:
[GRAPHIC] [TIFF OMITTED] TP15DE17.000
Where [beta]jk(m) is the estimated sensitivity of the probability of
default to macroeconomic factor m, for country-industry segment j and
rating category k, and S(t,m) is macroeconomic factor m in period t.
Loss Given Default
Similar to the PD model, the LGD model first calculates the loan's
LGD at the beginning of the projection horizon and then projects it
forward using the estimated relationship between historical changes in
LGD and changes in the macroeconomic environment.
Calculating the Initial LGD: Firm-reported data on line of business
and whether the loan is secured or unsecured are used to set the
initial LGD for performing loans. In cases in which the loan has
already been identified as troubled, i.e., the firm has already put
aside a reserve to cover the expected loss, the initial LGD is based on
the size of the reserve. Further adjustments are made to the initial
LGDs of loans that are in default at inception.\11\ For foreign loans,
initial LGDs are also adjusted based on the country in which the
obligor is domiciled, capturing differences in collateral recovery
rates across countries.
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\11\ Loans that are in default at inception of the stress period
(i.e., t=0) are assigned a PD of 100%, and a LGD using the ASC 310-
10 reserves reported by the firm.
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Projecting LGD: The LGD is then projected forward by relating the
change in the LGD to changes in the PD following Frye and Jacobs
(2012).\12\ Under that approach, changes in LGD are explicitly
calculated as an increasing function of PD. Specifically, loan i's LGD
from period t-1 to period t is given by:
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\12\ See, Frye, J., & Jacobs Jr, M. (2012). Credit loss and
systematic loss given default. The Journal of Credit Risk, 8(1),
109.
[GRAPHIC] [TIFF OMITTED] TP15DE17.001
Where [Phi][[sdot]] denotes the standard normal cumulative distribution
function and [Phi]-\1\[[sdot]] is its inverse. LGD in period
t depends on PD in period t and on PD and LGD in period t-1. If PD(i,t)
= PD(i,t-1), then LGD(i,t) = LGD(i,t-1).
Exposure at Default
For closed-end loans, the EAD is the utilized exposure.
For lines of credit and other revolving commitments, the EAD equals
the utilized exposure plus a portion of the unfunded commitment (i.e.,
the difference between the committed exposure and utilized exposure),
which reflects the amount that is likely to be drawn down by the
borrower in the event of default. The amount that is likely to be drawn
down is calibrated to the historical drawdown experience for defaulted
U.S. syndicated revolving lines of credit that are in the Shared
National Credit (SNC) database.\13\
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\13\ SNC loans have commitments of greater than $20 million and
are held by three or more regulated participating entities. For
additional information, see ``Shared National Credit Program,''
Board of Governors of the Federal Reserve System,
www.federalreserve.gov/supervisionreg/snc.htm.
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Formally, the EAD for a line of credit or other revolving product i
is set to:
[[Page 59551]]
[GRAPHIC] [TIFF OMITTED] TP15DE17.002
Where LEQ is the calibrated drawdown amount, OB(i,t=0) is the line's
outstanding exposure at the start of the projection horizon, and
CB(i,t=0) is the line's committed exposure at the start of the
projection horizon.
For standby letters of credit and trade finance credits, EADs are
conservatively assumed to equal the total commitment, since typically
these types of credits are fully drawn when they enter default status.
Table 1--List of Key Variables in the Corporate Loan Models and Sources of Variables
----------------------------------------------------------------------------------------------------------------
Variable Description Variable type Source
----------------------------------------------------------------------------------------------------------------
PD model \1\
----------------------------------------------------------------------------------------------------------------
U.S. BBB corporate yield The difference between quarterly Macroeconomic......... FR supervisory
spread. average of the yield on 10-year scenarios.
BBB corporate bonds and
quarterly average of the yield
on 10-year U.S. Treasury bonds.
U.S. Real GDP growth.......... Percent change in real gross Macroeconomic......... FR supervisory
domestic product in chained scenarios.
dollars, expressed at
annualized rate.
U.S. unemployment rate........ Quarterly average of seasonally- Macroeconomic......... FR supervisory
adjusted monthly data for the scenarios.
unemployment rate of civilian,
non-institutional population of
age 16 years and older.
Country....................... The two letter country code for Loan/borrower FR Y-14.
the country in which the characteristic.
obligor is headquartered.
Industry of obligor........... Numeric code that describes the Loan/borrower FR Y-14.
primary business activity of characteristic.
the obligor.
Internal obligor rating....... The obligor rating grade from Loan/borrower FR Y-14.
the reporting entity's internal characteristic.
risk rating system.
----------------------------------------------------------------------------------------------------------------
LGD model
----------------------------------------------------------------------------------------------------------------
Country....................... The two letter country code for Loan/borrower FR Y-14.
the country in which the characteristic.
obligor is headquartered.
Lien position................. The type of lien. Options Loan/borrower FR Y-14.
include first lien senior, characteristic.
second lien, senior unsecured,
or contractually subordinated.
Line of business.............. The name of the internal line of Loan/borrower FR Y-14.
business that originated the characteristic.
credit facility using the
institution's own department
descriptions.
Type of facility.............. The type of credit facility. Loan/borrower FR Y-14.
Potential types are defined in characteristic.
the FR Y-14Q H.1 corporate
schedule.
----------------------------------------------------------------------------------------------------------------
EAD model
----------------------------------------------------------------------------------------------------------------
Committed exposure amount..... The current dollar amount the Loan/borrower FR Y-14.
obligor is legally allowed to characteristic.
borrow according to the credit
agreement.
Type of facility.............. The type of credit facility. Loan/borrower FR Y-14
Potential types are defined in characteristic.
the FR Y-14Q H.1 corporate
schedule.
Utilized exposure amount...... The current dollar amount the Loan/borrower FR Y-14.
obligor has drawn which has not characteristic.
been repaid, net of any charge-
offs, ASC 310-30 (originally
issued as SOP 03-03)
adjustments, or fair value
adjustments taken by the
reporting institution, but
gross of ASC 310-10 reserve
amounts.
----------------------------------------------------------------------------------------------------------------
\1\ Other variables used to calculate initial loan status include days past due, non-accrual date, and ASC 310-
10 amount.
B. Modeled Loss Rates on Pools of Loans
The output of the corporate loan model is the expected loss on each
loan. As described above, estimated corporate loan loss rates depend on
a number of variables. This section groups loans according to three of
the most important variables in the model: Sector (financial and
nonfinancial), security status (secured and unsecured), and rating
class (investment grade and non-investment grade).\14\ Categorizing
corporate loans reported on schedule H.1 of the FR Y-14Q report as of
the fourth quarter of 2016 by sector, security status, and rating class
results in eight groups of loans: \15\
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\14\ Financial loans have a NAICS category
(``naics_two_digit_cat'') of 52; all other loans are marked
nonfinancial. Secured loans are defined as loans with lien positions
(``lien_position_cat'') marked as ``first-lien senior''; all other
loans are marked as unsecured. Investment grade loans are defined as
loans with a credit rating (``rating'') higher than and including
BBB; all other loans are marked as non-investment grade.
\15\ The set of loans on which loss rates are calculated
excludes loans held for sale or accounted for under the fair value
option, loan observations missing data fields used in the model,
lines of credit that were undrawn as of 2016:Q4, and other types of
loans that are not modeled using the corporate loan model (e.g.,
loans to financial depositories).
Financial, secured, investment grade
Financial, secured, non-investment grade
Financial, unsecured, investment grade
Financial, unsecured, non-investment grade
Nonfinancial, secured, investment grade
Nonfinancial, secured, non-investment grade
Nonfinancial, unsecured, investment grade
Nonfinancial, unsecured, non-investment grade.
The remainder of this section reports summary statistics and
modeled loss rates for these eight groups of corporate loans.
Table 2 reports summary statistics for the eight groups of loans.
The summary statistics cover a wide set of variables
[[Page 59552]]
that capture important characteristics of the loans and borrowers in
the set of loans.
Tables 3 and 4 show the modeled loss rates for the eight groups of
loans for the DFAST 2017 supervisory severely adverse and supervisory
adverse scenarios, respectively. Each entry in the table shows the
average (mean) estimated loss rate for the loans in one of the eight
groups, as well as the 25th and 75th percentiles of the estimated loss
rates.
Certain groups of loans generally have wider ranges of losses than
other groups. Although the loans are grouped according to the most
important characteristics in the model, other loan characteristics in
the model also affect loss rates, albeit in more limited manner.
Differences in these other characteristics within each loan group are
responsible for the range of loss rates shown in the tables. Greater
variation in these other characteristics within a group will generally
lead to larger ranges of loss rates. For example, among secured, non-
investment grade loans, the loss rates shown in Table 3 range from 8.7
to 12.1 for financial firms, but range from 2.7 to 9.8 for nonfinancial
firms, which include a wider variety of industries. Secured, non-
investment grade loans to nonfinancial firms are predominantly loans to
firms in the manufacturing, transportation, and technology sectors, but
also include loans to firms in other sectors like education and
utilities (Table 2).
Table 2--Summary Statistics of Selected Variables in the Corporate Loan Data Grouped by Loan and Borrower Characteristics \1\
[Percent, except as noted]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-investment grade Investment grade
-------------------------------------------------------------------------------------------------------
Variables Nonfinancial sector Financial sector Nonfinancial sector Financial sector
-------------------------------------------------------------------------------------------------------
Unsecured Secured Unsecured Secured Unsecured Secured Unsecured Secured
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of loans (thousands)..................... 15.60 101.80 1.28 8.20 21.34 52.80 2.11 5.91
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility type, share of utilized balance
--------------------------------------------------------------------------------------------------------------------------------------------------------
Revolving....................................... 37.14 41.52 33.37 45.28 32.27 37.17 51.78 71.39
Term loan....................................... 45.06 40.33 34.08 20.83 44.48 42.20 35.54 14.57
Other........................................... 17.80 18.15 32.55 33.89 23.25 20.63 12.67 14.04
--------------------------------------------------------------------------------------------------------------------------------------------------------
Credit rating, share of utilized balance
--------------------------------------------------------------------------------------------------------------------------------------------------------
AAA............................................. 0.00 0.00 0.00 0.00 1.22 0.92 3.36 4.89
AA.............................................. 0.00 0.00 0.00 0.00 6.55 7.17 12.12 11.05
A............................................... 0.00 0.00 0.00 0.00 22.23 23.63 25.16 39.80
BBB............................................. 0.00 0.00 0.00 0.00 70.00 68.28 59.35 44.26
BB.............................................. 80.06 76.66 88.97 81.82 0.00 0.00 0.00 0.00
B............................................... 19.63 22.28 10.89 18.05 0.00 0.00 0.00 0.00
CCC or below.................................... 0.31 1.07 0.14 0.13 0.00 0.00 0.00 0.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
Lien position, share of utilized balance
--------------------------------------------------------------------------------------------------------------------------------------------------------
First-lien senior............................... 0.00 100.00 0.00 100.00 0.00 100.00 0.00 100.00
Senior unsecured................................ 95.10 0.00 98.51 0.00 98.26 0.00 98.75 0.00
Other........................................... 4.90 0.00 1.49 0.00 1.74 0.00 1.25 0.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
Interest rate variability, share of utilized balance
--------------------------------------------------------------------------------------------------------------------------------------------------------
Fixed........................................... 23.04 14.45 13.11 6.17 24.93 27.97 17.69 6.92
Floating........................................ 71.61 79.99 81.29 88.65 68.75 68.72 77.52 90.21
Mixed........................................... 5.33 5.54 5.59 5.15 6.22 2.74 4.73 2.74
--------------------------------------------------------------------------------------------------------------------------------------------------------
Industry, share of utilized balance \2\
--------------------------------------------------------------------------------------------------------------------------------------------------------
Agriculture, fishing, and hunting............... 0.66 1.50 0.00 0.00 0.28 0.50 0.00 0.00
Natural resources, utilities, and construction.. 13.02 7.92 0.00 0.00 8.89 5.21 0.00 0.00
Manufacturing................................... 25.70 18.82 0.00 0.00 28.19 13.73 0.00 0.00
Trade and transportation........................ 28.30 32.57 0.00 0.00 15.95 29.17 0.00 0.00
Technological and business services............. 22.28 22.18 0.00 0.00 28.91 19.54 0.00 0.00
Finance and insurance........................... 0.00 0.00 100.00 100.00 0.00 0.00 100.00 100.00
Education, health care, and social assistance... 3.76 6.45 0.00 0.00 8.08 13.84 0.00 0.00
Entertainment and lodging....................... 2.46 6.06 0.00 0.00 2.13 4.39 0.00 0.00
Other services.................................. 3.82 4.49 0.00 0.00 7.57 13.62 0.00 0.00
--------------------------------------------------------------------------------------------------------------------------------------------------------
Guarantor flag, share of utilized balance
--------------------------------------------------------------------------------------------------------------------------------------------------------
Full guarantee.................................. 41.24 41.83 42.22 29.09 30.23 29.95 42.22 12.02
[[Page 59553]]
U.S. government guarantee....................... 5.03 0.18 0.23 0.03 0.52 0.26 0.00 0.00
Partial guarantee............................... 2.62 4.23 3.09 3.28 1.77 2.41 3.86 4.99
No guarantee.................................... 51.11 53.74 54.47 67.60 67.49 67.31 53.92 82.99
Domestic obligor, share of utilized balance..... 63.53 91.35 65.10 72.29 71.58 91.46 65.93 81.37
Remaining maturity, average in months 3 4....... 38.34 48.44 28.95 23.89 38.26 57.59 38.55 30.44
Interest rate, average in percent \4\........... 2.77 3.24 2.36 2.68 2.17 2.48 2.26 2.32
Committed exposure, average in millions of 15.24 8.32 25.22 17.43 24.79 10.81 43.24 57.37
dollars........................................
Utilized exposure, average in millions of 10.89 6.17 19.89 14.17 16.46 8.35 28.36 39.64
dollars........................................
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ The set of loans presented in this table excludes loans held for sale or accounted for under the fair value option, loan observations missing data
fields used in the model, lines of credit that were undrawn as of 2016:Q4, and other types of loans that are not modeled using the corporate loan
model (e.g., loans to financial depositories).
\2\ Industries are collapsed using the first digit of the NAICS 2007 code, except for finance and insurance.
\3\ Maturity excludes demand loans.
\4\ Averages for remaining maturity and interest rate are weighted by utilized exposure.
Table 3--Projected Average Loan Loss Rates and 25th and 75th Percentile Ranges by Loan and Borrower
Characteristics, 2017:Q1-2019:Q1, DFAST 2017 Severely Adverse Scenario
----------------------------------------------------------------------------------------------------------------
Sector Security status Rating class Loss rates (percent)
----------------------------------------------------------------------------------------------------------------
Financial......................... Secured.............. Investment grade.... 2.5 [1.6 to 3.3].
Financial......................... Secured.............. Non-investment grade 10.4 [8.7 to 12.1].
Financial......................... Unsecured............ Investment grade.... 3.3 [1.9 to 5.3].
Financial......................... Unsecured............ Non-investment grade 12.6 [8.3 to 17.0].
Nonfinancial...................... Secured.............. Investment grade.... 0.8 [0.3 to 1.0].
Nonfinancial...................... Secured.............. Non-investment grade 5.4 [2.7 to 9.8].
Nonfinancial...................... Unsecured............ Investment grade.... 1.2 [0.5 to 1.7].
Nonfinancial...................... Unsecured............ Non-investment grade 6.0 [3.6 to 11.7].
----------------------------------------------------------------------------------------------------------------
Note: Loan-level loss rates are calculated as cumulative nine-quarter losses on a given loan divided by initial
utilized balance on that loan. Average loss rates reported in the table are the average of the loan-level loss
rates weighted by initial utilized balances. The set of loans on which loss rates are calculated excludes
loans held for sale or accounted for under the fair value option, loan observations missing data fields used
in the model, lines of credit that were undrawn as of 2016:Q4, and other types of loans that are not modeled
using the corporate loan model (e.g., loans to financial depositories).
Table 4--Projected Average Loan Loss Rates and 25th and 75th Percentile Ranges by Loan and Borrower
Characteristics, 2017:Q1-2019:Q1, DFAST 2017 Adverse Scenario
----------------------------------------------------------------------------------------------------------------
Sector Security status Rating class Loss rates (percent)
----------------------------------------------------------------------------------------------------------------
Financial......................... Secured.............. Investment grade.... 1.5 [1.0 to 2.0].
Financial......................... Secured.............. Non-investment grade 5.9 [4.7 to 6.7].
Financial......................... Unsecured............ Investment grade.... 2.0 [1.2 to 3.3].
Financial......................... Unsecured............ Non-investment grade 7.3 [4.7 to 9.8].
Nonfinancial...................... Secured.............. Investment grade.... 0.5 [0.2 to 0.6].
Nonfinancial...................... Secured.............. Non-investment grade 3.2 [1.6 to 5.8].
Nonfinancial...................... Unsecured............ Investment grade.... 0.8 [0.4 to 1.1].
Nonfinancial...................... Unsecured............ Non-investment grade 3.7 [2.1 to 7.1].
----------------------------------------------------------------------------------------------------------------
Note: Loan-level loss rates are calculated as cumulative nine-quarter losses on a given loan divided by initial
utilized balance on that loan. Average loss rates reported in the table are the average of the loan-level loss
rates weighted by initial utilized balances. The set of loans on which loss rates are calculated excludes
loans held for sale or accounted for under the fair value option, loan observations missing data fields used
in the model, lines of credit that were undrawn as of 2016:Q4, and other types of loans that are not modeled
using the corporate loan model (e.g., loans to financial depositories).
[[Page 59554]]
C. Portfolios of Hypothetical Loans and Associated Loss Rates
The effect of borrower and loan characteristics on the losses
estimated by the corporate loan model can also be illustrated by the
differences in the estimated loss rate on specific sets of hypothetical
loans. This section contains descriptive statistics from three
portfolios of hypothetical loans (Table 6) and the modeled loss rates
for the three portfolios under the DFAST 2017 supervisory adverse and
supervisory severely adverse scenarios (Table 7).
The portfolios of hypothetical loans are designed to have
characteristics similar to the actual loans reported in schedule H.1 of
the FR Y-14Q report. Three portfolios containing 200 loans each are
provided, and they are designed to capture characteristics associated
with:
1. Typical set of loans reported in the FR Y-14Q;
2. Higher-than-average-risk loans (in this case, non-investment
grade loans); and,
3. Lower-than-average-risk loans (in this case, investment grade
loans).
The portfolios of hypothetical loans include 12 variables that
describe characteristics of corporate loans that are generally used to
estimate corporate loan losses (Table 5).\16\
---------------------------------------------------------------------------
\16\ The sets of loans are available for download on the Federal
Reserve's website: Higher-than-average-risk loans (https://www.federalreserve.gov/newsevents/pressreleases/files/HigherRisk.csv); typical-risk loans (https://www.federalreserve.gov/newsevents/pressreleases/files/Typical.csv); and lower-than-average-
risk loans (https://www.federalreserve.gov/newsevents/pressreleases/files/LowerRisk.csv).
---------------------------------------------------------------------------
Table 6 contains summary statistics for the portfolios of
hypothetical loans in the same format as Table 2. The portfolios of
hypothetical loans are constructed to capture characteristics of
certain sets of loans, but are not fully representative of the
population of loans reported in Table 2. Table 7 contains the loss
rates for the portfolios of hypothetical loans calculated under the
DFAST 2017 supervisory severely adverse and supervisory adverse
scenarios. The rank ordering of the loss rates is consistent with the
ranges of loss rates reported in Tables 3 and 4. The portfolio of
higher-risk loans has higher loss rates under both the severely adverse
and adverse scenarios and is also more sensitive to changes in
macroeconomic conditions (loss rate of 7.2 percent in the severely
adverse scenario and 4.2 percent in the adverse scenario) than the
portfolio of typical loans (loss rate of 5.4 percent in the severely
adverse scenario and 3.2 percent in the adverse scenario). Conversely,
the portfolio of lower-risk loans has lower losses under both
scenarios, and is less sensitive to changes in macroeconomic conditions
(loss rate of 1.8 percent in the severely adverse scenario and 1.1
percent in the adverse scenario).
Table 5--List of Variables Included in Portfolios of Hypothetical Loans
----------------------------------------------------------------------------------------------------------------
Variable Mnemonic Description
----------------------------------------------------------------------------------------------------------------
Origination year........................ orig_year.................. Year loan was originated.
Type of facility........................ facility_type_cat.......... The type of credit facility.
1 is revolving;
5 is non-revolving; and
0 is other.
Lien position........................... lien_position_cat.......... The type of lien.
1 is first-lien senior;
2 is second-lien;
3 is senior unsecured; and,
4 is contractually subordinated.
Credit rating........................... rating..................... Credit rating of obligor. Categories
include AAA, AA, A, BBB, BB, B, CCC, CC,
C, and D.
Domestic flag........................... domestic_flag.............. Equal to 1 if obligor is domiciled in the
U.S.
Industry code (2-digit)................. naics_two_digit_cat........ Two-digit industry code based on 2007
NAICS definitions.
Committed exposure amount............... committed_exposure_amt..... Committed exposure in dollars.
Utilized exposure amount................ utilized_exposure_amt...... Utilized exposure in dollars.
Interest rate........................... interest_rate.............. Interest rate on credit facility.
Interest rate variability............... interest_rate_variability.. Interest rate type.
0 is fully undrawn (interest rate not
provided);
1 is fixed;
2 is floating;
3 is mixed.
Remaining maturity...................... term....................... Remaining term of the loan in months.
Guarantor flag.......................... guarantor_flag............. Indicates the type of guarantee of the
guarantor.
1 is full guarantee;
2 is partial guarantee;
3 is U.S. government agency guarantee;
4 is no guarantee.
----------------------------------------------------------------------------------------------------------------
Note: Some of the variables included in the portfolios of hypothetical loans are presented in a more aggregated
form than they are reported in the FR Y-14.
Table 6--Summary Statistics of Selected Variables in the Portfolios of Hypothetical Loans
[Percent, except as noted]
----------------------------------------------------------------------------------------------------------------
Variables Higher-risk Lower-risk Typical
----------------------------------------------------------------------------------------------------------------
Facility type, share of utilized balance
----------------------------------------------------------------------------------------------------------------
Revolving....................................................... 36.52 46.02 50.77
Term loan....................................................... 42.67 39.97 33.32
[[Page 59555]]
Other........................................................... 20.81 14.02 15.91
----------------------------------------------------------------------------------------------------------------
Credit rating, share of utilized balance
----------------------------------------------------------------------------------------------------------------
AAA............................................................. 0.00 0.00 0.45
AA.............................................................. 0.00 6.79 1.06
A............................................................... 0.00 9.72 4.48
BBB............................................................. 0.00 83.49 41.32
BB.............................................................. 78.68 0.00 40.91
B............................................................... 20.85 0.00 10.57
CCC or below.................................................... 0.47 0.00 1.21
----------------------------------------------------------------------------------------------------------------
Lien position, share of utilized balance
----------------------------------------------------------------------------------------------------------------
First-lien senior............................................... 82.79 61.31 76.61
Senior unsecured................................................ 17.21 38.69 23.39
Other........................................................... 0.00 0.00 0.00
----------------------------------------------------------------------------------------------------------------
Interest rate variability, share of utilized balance
----------------------------------------------------------------------------------------------------------------
Fixed........................................................... 16.26 26.36 11.72
Floating........................................................ 83.44 71.99 86.04
Mixed........................................................... 0.30 1.64 2.24
----------------------------------------------------------------------------------------------------------------
Industry, share of utilized balance \1\
----------------------------------------------------------------------------------------------------------------
Agriculture, fishing, and hunting............................... 0.42 0.00 0.16
Natural resources, utilities, and construction.................. 10.71 9.34 4.03
Manufacturing................................................... 15.46 5.26 18.96
Trade and transportation........................................ 19.30 31.32 20.64
Technological and business services............................. 26.36 11.52 13.74
Finance and insurance........................................... 16.36 15.51 20.15
Education, health care, and social assistance................... 6.40 7.67 7.05
Entertainment and lodging....................................... 1.96 1.66 1.52
Other services.................................................. 3.03 17.73 13.75
----------------------------------------------------------------------------------------------------------------
Guarantor flag, share of utilized balance
----------------------------------------------------------------------------------------------------------------
Full guarantee.................................................. 41.61 50.93 32.40
U.S. government guarantee....................................... 1.50 0.00 0.38
Partial guarantee............................................... 1.57 0.06 2.15
No guarantee.................................................... 55.32 49.01 65.08
Domestic obligor, share of utilized balance..................... 93.88 82.34 94.64
Remaining maturity, average in months 2 3....................... 48.57 56.35 39.23
Interest rate, average in percentage \3\........................ 3.33 2.75 2.87
Committed exposure, average in millions of dollars.............. 7.87 17.94 17.47
Utilized exposure, average in millions of dollars............... 5.76 7.35 5.86
----------------------------------------------------------------------------------------------------------------
\1\ Industries are collapsed using the first digit of the NAICS 2007 code, except for finance and insurance.
\2\ Maturity excludes demand loans.
\3\ Averages for remaining maturity and interest rate are weighted by utilized exposure.
Table 7--Projected Portfolio Loss Rates, 2017:Q1-2019:Q1, DFAST 2017
Scenarios
[Percent]
------------------------------------------------------------------------
Scenario
---------------------
Hypothetical portfolio Severely
adverse Adverse
------------------------------------------------------------------------
Typical........................................... 5.4 3.2
Lower-risk........................................ 1.8 1.1
Higher-risk....................................... 7.2 4.2
------------------------------------------------------------------------
Note: Portfolio loss rates are calculated as sum of the cumulative nine-
quarter losses divided by sum of initial utilized balances.
By Order of the Board of Governors of the Federal Reserve
System, December 7, 2017.
Ann E. Misback,
Secretary of the Board.
[FR Doc. 2017-26856 Filed 12-14-17; 8:45 am]
BILLING CODE 6210-01-P