August 2006
Study Group on the Advancement of Credit Risk Management
Discussions on Advancing Credit Risk Management through Internal Rating
Systems (2)—Summary of Discussions at the “Study Group on the
Advancement of Credit Risk Management”
I. Introduction
The “Study Group on the Advancement of Credit Risk Management” (organized andinaugurated last October by the Center for Advanced Financial Technology, the Bank ofJapan; see the attachment for a list of members), consisting of experienced practitionersof credit risk management, published a summary of discussions from the last fivesessions in April this year.1 The Study Group discussed the issues of advancing credit
risk management through internal rating systems and possible responses to the raised
issues. This paper summarizes the discussions from the sixth to the eighth (final)
session as a sequel to the previous publication.
This paper does not intend to draw conclusions for each of the issues discussed. It
simply aims to present issues and discussions concerning the advancement of credit risk
management. Opinions are those of the members and not necessarily those of theorganization to which the member belongs.

1

The summary of “Discussions on Advancing Credit Risk Management through Internal Rating
Systems (1)” is now available on the website of the Bank of Japan:
Japanese version: http://www.boj.or.jp/type/release/zuiji_new/fsc0604a.pdf
English version: http://www.boj.or.jp/en/type/release/zuiji_new/fsc0605b.pdf
1II. Discussions at the Sixth Session (Held on March 9, 2006)
A. Issues relating to the estimation of risk factors in retail credits
1. Potential Issues
As specified in greater detail below, the issues that are characteristic of retail portfoliosthat may cause problems with the estimation of risk factors include: (i) an absence ofindustry standards for the number of pool categories and a standard definition of default,(ii) inadequate data accumulation, and (iii) dependence of risk management on
outsourcing to an affiliate company or a business partner.
The number of pool categories/definition of default
If there is no industry consensus on the number of pool categories among financial
institutions (a precondition of risk factor estimation for retail credits), then the estimatesof risk factors and the resulting capital requirement may vary even if a similar credit
portfolio or credit risk model is selected.
Likewise, differences in the definition of default (for example, the past due trigger may
range from 90 to 180 days. Also, there may be a disparity in views regarding thetransition from default to nondefault status) may generate different estimates of risk
factors and subsequently different capital requirements, even with respect to similar
credit portfolios.
Data accumulation
When the available data is not sufficient for pool classification, it may be difficult to
identify sufficient risk factors or to make objective judgments. In this case, as data
accumulates, the pool classification may be found to be inappropriate.
Moreover, it is not always easy to understand the sensitivity to economic conditions andthe seasoning effect of the retail portfolios because of a lack of time series of data. The
way these factors are treated may create divergences in risk quantification outcomesamong financial institutions.
Risk management by an affiliate company or business partner
In the credit card business, consumer loan business, and other retail businesses, anaffiliate company or a business partner sometimes undertakes the task of data
accumulation or risk management. In such cases, financial institutions may not haveaccess to sufficient information from business partners, partly because of industry
practice regarding the disclosure of retail information. The lack of access to information
poses a serious challenge to the estimation of risk factors and their validation. A similar
problem may occur in the housing loan business too, if risk management is consigned toan external guarantee company.
2. Participants’ Views
With regard to the estimation of risk factors for retail portfolios, the following issues
should be considered when developing effective solutions:

2The number of pool categories/definition of default
For setting up pool categories of retail portfolios, it is necessary to take the accuracy of
estimated risk factors and the size of the data sample into account in accordance withdifferent product attributes.
The definition of default must at least be consistent within a group of products withsimilar characteristics. In addition, if a different definition is used within a retail credit
portfolio, it is preferable to be accountable for the choice of the different definition.
Data accumulation
If the risk factor values associated with the existing pool classification are found to beunstable during data accumulation, it is necessary to review the classification of thepool categories at that point. If it is difficult to change the classification, it is advisable
to use conservative values for the risk factors considering the instability in their values.
In estimating the risk factors, it is important to capture the dynamics of their behavior
from a long time series data. Even if long time series data is not available, the impact
and the seasoning effect of economic fluctuations should be considered using models
and scenario analysis.
Risk management by an affiliate company or business partner
Even if the majority of risk management is outsourced to an affiliate company or abusiness partner, it is desirable to have access to the same information as the affiliatecompany. If this is difficult, it is necessary to undertake some complementary measures(e.g., detailed results of back testing, some incentives that are provided throughcontracts to the affiliate company and designed to ensure the validity of their services,use of more conservative estimates of risk factors, and so on) in order to compensate forthe lack of information.
B. Issues relating to utilization of internal rating systems from a businessstandpoint
1. Potential Issues
It is necessary for financial institutions to gain confidence in external parties for theirinternal rating systems and estimates of risk parameters. For this purpose, it isparticularly important to examine whether risk parameters including PDs, LGDs, andother outputs such as assigned internal ratings, are effectively utilized for actual
business decisions. Likewise, it is imperative to demonstrate to external parties that thefinancial institutions have confidence in these outputs.
However, the outputs suitable for the regulation of capital requirements are not always
the same as those for the business activities of financial institutions. In that case, a key
point to be noted by financial institutions is how to assure the third party of the qualityof their outputs for regulatory purposes, and demonstrating their relationships with theelements used in making their business decisions.
It is also important to identify the departments (or the divisions) within a financial
institution that are supposed to use these outputs, and also that are supposed to checktheir use for business purposes.

32. Participants’ Views
The discussions mentioned here may be useful for demonstrating the quality andaccuracy of internal rating systems and the validity of risk parameters used in thecalculation of regulatory capital requirements to third parties.
First, financial institutions must be accountable for how the various outputs of theirinternal rating systems are used for business decisions and strategies (see the figure
below).
An example of the use of risk factors in the business operations of financial institutions(an example)
PD, LGD, etc

Regulatory capitalrequirement

Internal rating
system

PD, LGD, etc

Amount of credit risk
(EL, UL)
Economic Capital

Allocation of economic
capitalCredit approval

Set lending rates, Manage

Set credit lines limits

profitability, Credit portfolio analysis

ReportingMonitoring

ReportingDisclosure

Internal audit

Management

Regulatory authority

Market/shareholders

To ensure the credibility of using PDs, LGDs, and other risk elements, or utilizing
internal rating systems for business decisions and strategies, key points include thedegree of utilization for: (i) credit approval and setting credit line limits, (ii) determining
lending rates and operation of lending rate guidelines, (iii) credit portfolio management(monitoring), (iv) economic capital allocation, and (v) the ability to justify thedifference, if any, between risk parameters used for internal risk management and thoseused for regulatory purposes. Furthermore, in terms of the PDs, LGDs, and other risk
parameters that may have a direct impact on the calculation of capital requirements, it isparticularly important to utilize these elements in a manner that warrants highconfidence in their quality by third parties.
These key points must be evaluated based on two yardsticks (see the following chart).
First, the “level of importance” in the sense that the way of using risk parameters orinternal rating systems affects business decisions. Second, the level of“consistent/ongoing utilization” in the sense that the elements and internal rating
systems are used for risk management on a daily basis, while maintaining consistency
within the organization.

4

Examples of points to be evaluated
Level of importance-- The degree of influence on the performance (e.g.,
profits) of the financial institution

Level ofconsistent/ongoing
utilization-- Development of schemes and systems to ensure thecontinued use of the outputs for the operation of front
business lines and the risk control section-- Consistency in the use of information-- Regular reporting to the senior management/the internal
audit function-- Active discussions by senior management using theoutputs-- Discussions with market participants/shareholders on
the outputs through disclosure

In a case where the outputs used for internal risk management are different from thoseused for regulatory purposes, it is important to be capable of providing a clear
explanation to third parties on the relationship between the two different sets of outputs
as well as the reasons for the difference. In this context, for example, if it is found that:(i) the same data source is used for estimation, and (ii) there is little room for a bias in
the relationship between these two sets of outputs from the long-term and medium-term
perspective (in other words, there is no bias from the viewpoint of back testing). This
may then indicate the existence of mutual consistency between the two sets of outputs.
Financial institutions are responsible for validating the utilization of the outputs ofregulatory requirements for their businesses and internal risk management. Within afinancial institution, ultimately, while the front business lines and the risk control
functions take charge of utilization and its validation, the senior management and theinternal audit function need to develop the process for such validation and approval ofutilization.
Furthermore, the scope and degree of utilizing the outputs in business operations orinternal risk management of a financial institution should vary depending on thecircumstances surrounding the financial institution, such as the degree of data
accumulation, customer relationships, and accounting and other schemes. Whileconsidering all factors, financial institutions are expected to maintain consistency
between the outputs for regulatory purposes and the outputs used for internal risk
management.
III. Discussions at the Seventh Session (Held on April 13, 2006)
A. Issues relating to governance of credit risk management
1. Potential Issues
Effective functioning of credit risk management through internal rating systems needs
strong support from the corporate governance mechanism. To be specific, the corporate

5

governance mechanism includes: (i) formulation of rules for risk management, (ii)documentation of the risk management process, (iii) active involvement by senior
management in credit risk management through internal rating systems, (iv)establishment of independent risk control functions from the front business lines, (v)appropriate involvement of external institutions to support internal auditing, and (vi)enhanced accountability through appropriate disclosure of risk management. The
following discussions focus on (iv), (v), and (vi), as these three issues seem to vary
most significantly between financial institutions.
The role and independence of the risk control function-- How should we establish independence of the sections inside front business lines thatare in charge of collating data and also risk management (the so-called “middle officewithin the front office”), or the credit review section from the other parts of the front
business lines? In addition, how should we set up a proper division of work between
this middle office within the front office and the independent risk control function (i.e.,
the real middle office)?
-- How should we define the role of risk control in the area of reviewing individual loan
prices?
-- Given the limits in the number of professional personnel who can deal with new
finance products and difficulties in shifting these staff from the front to middle offices
without damaging front businesses, what kinds of arrangements are necessary in termsof risk management?
-- Is there any risk in adopting an incentive mechanism that may impair the
independence of the middle office and credit review sections? What are the minimum
requirements for avoiding this risk?
Level of involvement of internal/external audits-- To what extent should the internal audit function conduct detailed auditing of theinternal rating and risk quantification models? Are they feasible?
-- If the internal audit function cannot secure professional personnel in the area of new
financial products, then what kind of arrangements are necessary in terms of risk
management?
-- To what extent should dependence on an external audit be tolerated? In addition, howshould the external auditor collaborate/share the role with the internal audit function?
Ways to validate appropriateness of disclosed information regarding credit risk-- What should be checked and how?
2. Participants’ Views
For the questions mentioned above, consideration of the following could lead to helpful
answers:

6

The expected role and independence of the risk control function
In general, setting up a credit risk control function and credit review section that is
independent from front business lines is most important in establishing an effective andfunctional system capable of providing challenges to front business lines.
In order to ensure the independence of the credit review section, it is important to ensure
its independence in the chain of command from front offices (e.g., board members incharge of credit review are not also responsible for front businesses), even if this sectionis under the same umbrella as the front offices.
The degree of independence of the middle office within the front office may varydepending on the level of importance of the relevant operation from the viewpoint of its
scale and degree of risk. In addition, in a business line that is less important in terms ofthe degree of risk, while the middle office will be mainly responsible for the process ofchecking the risk management operations of the middle office within the front office, as
the level of importance increases, it will be responsible for additional risk control
operations in accordance with the increasing level of importance. These may include
collection of risk related data, monitoring of the degree of risk, and monitoring ofcompliance with the risk-related roles.
Pricing of individual loans will be determined primarily by the front office and thecredit review section, with reference to the profits of other products, the future outlook
for growth in business transactions, and the credit rating of the companies. In suchcircumstances, the middle office is required to check whether credit costs/risks are taken
into consideration when pricing the credit portfolio as a whole. In addition, in cases ofpooled-type products for which credit risk is identified as a portfolio, the middle office
may conduct in-depth checking of pricing.
If the number of professionals is limited and the middle office function cannot keepsuch personnel for new finance products, some measures to complement the middle
office functions must be considered. For example, the measures may include restrictive
operation by the front office until personnel capability in the middle office improves,enhanced qualification examination of new products, comparison by the middle officewith the risk evaluations of products with similar characteristics, and rechecking by athird party.
In evaluating the middle office’s performance, in order to avoid the risk of adopting an
incentive mechanism that may impair the independence of the middle office, theincentive mechanism should be exempt from short-term profits as a minimum
requirement. Also, the evaluators of the middle office’s performance should be clearly
separate from the front office.
Degree of involvement of the internal audit function
Essentially, validation of internal ratings and credit risk quantification models must be
conducted by the middle office on an ongoing basis. Admittedly, the internal auditing
function is not required to conduct detailed validation work at the same level as that
conducted by the middle office, or to follow the process checking associated with thevalidation by the middle office. It needs, however, to conduct checking of the front
office and other audited functions to ensure robustness and objectivity, and to prevent
arbitrary operations of the internal rating system. It is also possible to proceed with the7auditing operation in collaboration with an external organization. However, even insuch cases, it is the internal auditing function that should assume the ultimate
responsibility for the checking of the internal auditing operation.
If the same persons are in charge of the estimation of risk factors and the validation ofmodels and risk factors within the same department, the internal auditing function isrequired to exercise greater than normal supervisory authority over the department withmore specialized knowledge.
If the number of professionals for new finance products is limited and the auditing
function cannot keep competent personnel, ways of overcoming the shortage ofmanpower in the internal auditing function (such as enhancement of process checking
and utilization of an external body) must be considered.
Ways to validate appropriateness of disclosed credit risk information
In preparing the basic data to be disclosed, throughout the processes relating topreparation of the data, identification of the risks inherent to each process andevaluations of how the risks are handled should provide an effective means of ensuring
the appropriateness of the disclosed information.
IV. Discussions at the Eighth Session (Held on May 29, 2006)
A. Views on losses relating to loan defaults and LGD estimation
1. Potential Issues
Regulatory losses and accounting reserves
The losses from loan defaults vary depending on their definition, i.e., whether we use
the regulatory definition or the accounting definition, which is used for specific reserve
purposes.2 In this regard, it is crucial to consider how to sort out and deal with theconceptual difference between these two definitions, paying due attention to its impacts
on accounting and information disclosure.
Additional issues relating to LGD estimation
The basic concepts of LGD estimation were already mentioned in previous sessions.3
To expand upon this, in estimating the LGDs of loan defaults, it may be necessary toconsider how we should estimate the effects of a recession period. Admittedly, because
the size of the LGD data sample is limited and there is no established method of LGD
estimation, it is difficult to address these issues using actual data and empirical analysis
at present. However, the following should represent important issues to be considered in
LGD estimation.

2

The loans called loan defaults are mainly supposed to be loans that are transferred to thedebtor categories of “borrowers requiring close supervision” (definition of default for regulatory
purposes) or lower, but that has not yet been in the state of statutory bankruptcy.
3
See pages 14–17 of the publication, “Discussions on Advancing Credit Risk Management
through Internal Rating Systems (1)” (the “Publication” hereafter).
8

2. Participants’ Views
Regulatory losses and accounting reserves
For the purpose of risk management, as with losses from nondefaulted loans, losses
from loan defaults should be estimated based on the data of actual final recoveries.
However, because the disposal (or revitalization) process of loan defaults is unique toindividual transactions, in some cases it may be inappropriate to apply a uniform
methodology in estimation. In this regard, one of the possible approaches may be toconsider the specific reserves for accounting purposes as the losses from loan defaults
for risk management purposes. However, in such a case, a reasonable validation basedon the data is necessary to examine whether this assumption would cause any biases in
LGD estimation. This rather opaque description of LGD estimation reflects the current
situation of a lack of consensus about best practice in this area. To find the best
methodologies of estimating losses from loan defaults, it is necessary for financial
institutions and the relevant authorities to accumulate loan default data and to carefully
examine the empirical results of loss estimation.
Additional issues relating to LGD estimation
Unlike LGD estimation for nondefaulted loans, the following become issues to beconsidered in estimating the LGD of loan defaults:(i) LGD should be estimated based on the assumption that the default status isconsidered deterministic (either in the form of continued financial assistance,
rehabilitation, or liquidation proceedings). On the other hand, in the case of
nondefaulted loans, the default status is stochastic and thus LGD estimation isconducted without dependence on the default status information.
(ii) Because part of a loan may be recovered as time progresses, it is necessary to adjust
LGD estimation for the remaining debt (defined as EAD [exposure at default] minus
recovered amount). <In the case of nondefaulted loans, LGD estimation is made for
EAD.>
The above may indicate that the DCF method can be used for LGD estimation of loan
defaults. If the DCF method is applied to calculating specific reserves for accounting
purposes, it may be considered an alternative for LGD estimation.
However, in this approach, the issue remains as to how the business downturn impact
can be taken into consideration as a stress.
In addition, as a general issue of LGD estimation regardless of defaulted or
nondefaulted loans, it should be noted that LGD estimation approaches are different
between corporate and retail credits (for example, retail LGD is deemed to be based on
more empirical/quantitative approaches <modeling of time series data, etc.> than forcorporate LGD).
B. Additional issues relating to PDs and LGD estimation for specialized lending
1. Potential Issues
As for specialized lending (SL) that lacks sufficient actual data on defaults and forwhich parameter estimates are difficult to validate using actual data, the framework for

9rating systems/models can be categorized into three conceptual types, as follows. Given
the fact that there is as yet no established standard business practice in the industry, it isimportant to keep some flexibility in interpreting these types, which could varydepending on the circumstances surrounding the financial institutions and thecharacteristics of each type.
(i) Estimation of PDs under the same rating system used for corporate credits
The internal credit rating is developed based on PDs only and not on the type ofcredit/business transaction. Consequently, the same PDs are applied to corporate credits
and the SLs belonging to the same rating bucket.
Corporate

RatingProcess

RatingProcess

SL

RatingEstimationof PDs by
ratingAssumedPD
P1%
P2%--P N%

1
2--N

Validationof PDs by
ratingEstimation based oninternal actual data(ii) Estimation using SL-related external data
Default rates published by rating agencies are used by mapping SLs to an externalrating.
Rating Systems for SL

SL

RatingProcess

Rating1
2--N

Data from Rating
Agencies
Rating

Mapping

AAA
AA
--CCC

Estimationof PDs by
ratingDefault
Rate
q1%
q2%
--q N%

Validationof PDs by
rating(iii) Direct estimation using a modelPDs and other risk parameters of individual SLs within a rating bucket are estimated bya model (for example, the Merton type or the scoring model that regards the loan as
defaulted when it falls below a certain threshold). If a rating is assigned based on themodel’s outputs (equal to assumed PDs, etc.), the process follows the one described in(i) above.
Rating system for SLs
SL

Ratingprocess

Rating1
2--N

Estimationof PDs by
ratingValidationof PDs by
rating

For individual SLs within a rating
bucket, PDs etc. are calculatedusing a model10

In the estimation/validation process, it is also possible to combine the aforementioned
three types (for example, ”PD estimation is performed as described in (iii) and mapped
to the system in (i)”, “PD estimation is performed as described in (i) and verified by (ii)or (iii)”, etc.).
2. Participants’ Views
For the aforementioned three types, it is necessary to pay attention to the following
points, respectively:Type 1
If the SL rating is established based on the same rating system used for corporate credits,
it is necessary to conduct ex post validation based on the empirical data to examine
whether there is a difference in the actual default rate between the SLs and corporate
credits within the same rating bucket, and whether there is a difference in the tendenciesof the migration rate, etc. Because defaulted SL samples are scarce, there is a limit tosuch validations. However, it is still important to ensure that the rating systems for both
SLs and corporate loans are of a similar nature by, for example, comparing the
migration rates of the business corporations and SLs.
Type 2
When the ratings of securitization transactions are mapped to those of SLs using an
external rating without distinguishing securitization transactions from SLs (for example,
evaluating the bank’s nonrecourse real-estate loans by using CMBS’ external ratings), it
is necessary to have reasonable explanations about various issues arising from mapping(for example, how to deal with the differences in the risk characteristics of the rated
products, correlations between PD and LGD and tranches structures <i.e., whether theyshould be reflected in the PDs or LGDs>).
Type 3
When establishing the unique rating system for SLs independent of the mapping to theratings of corporate credits, it is desirable to conduct validations based on actual default
data. Because it is currently difficult to set ratings that only cover SLs because of thepaucity of data for defaulted SLs, utilization of a common database (data consortium),for example, should be considered as a future possibility.
<Inquiries>
Secretariat of the Study Group on the
Advancement of Credit Risk Management(c/o Center for Advanced Financial Technology,
Financial Systems and Bank Examination
Department, the Bank of Japan)
Mr. Tsuyoshi Oyama (03-3277-3018)
Mr. Masao Yoneyama (03-3277-2039)
Mr. Hidehiko Umeda (03-3277-1993)

11

<Attachment>
List of Study Group Members
Mizuho Financial
Group

Sumitomo Mitsui
Banking Corporation

Bank of TokyoMitsubishi UFJ

Risk Management Division

Tadahiko Onoyama

Risk Management Division

Hiroshi Taguchi

Credit Risk Management
Division

Yoshiyuki Okubo

Credit Risk Management
Division

Yusuke Oyama

Credit Planning Department

Toshiaki Nakai

Credit Planning Department

Hirokazu Shindo

Credit Planning Department

Takeshi Abiko

Corporate Risk Management
Department

Hiroo Sugai

Corporate Risk Management
Department

Akiya Watanabe

Corporate Risk Management
Department

Yoshitaka Ando

Credit Policy & Planning
Division

Hiroshi Nagasawa

Credit Policy & Planning
DivisionTakashi Mamizuka

Credit Policy & Planning
Division

Koujirou Nakazawa

Credit Policy & Planning
Division

Senshin Masui

Credit Policy & Planning
Division

Tomoya Mizogami

12Bank of Japan

Center for Advanced Financial
Technology

Tsuyoshi Oyama

Center for Advanced Financial
Technology

Nobuyasu Obata(now Personnel andCorporate Affairs
Department)

Center for Advanced Financial
Technology

Masao Yoneyama

Center for Advanced Financial
Technology

Jun Muranaga

Center for Advanced Financial
Technology

Hidehiko Umeda

Center for Advanced Financial
Technology

Yasunari Inamura

Planning and Coordination
Bureau (Supervisory Bureau)

Shunsuke Shirakawa (nowthe Ministry of Finance)

Planning and Coordination
Bureau (Supervisory Bureau)

Yasushi Shiina

Supervisory Bureau

Futoshi Ueno

Observing Members
Financial Services
Agency13