This document discusses regulatory validation of internal ratings-based (IRB) models used to estimate credit risk factors. It outlines some of the challenges in validating these models statistically due to limitations in historical default data and the unobservable nature of certain credit risk factors. The regulatory validation process therefore includes both qualitative and quantitative assessments. The principles of regulatory validation are described, including that it assesses predictive ability, involves independent review, and is an iterative process without a single validation method. The components of the validation process seek to demonstrate IRB systems can deliver sufficient accuracy in credit risk estimates through board oversight, use of risk rating systems in credit processes, backtesting, and stress testing.

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Regulatory IRB Validation
19
KEY CONCEPTS
• Model validation • Regulatory validation
19 Regulatory IRB validation
19.1 Model validation
Model validation is the process of assessing the accuracy of the estimates derived from a
quantitative model, using historical data. For example, to assess the accuracy of a
quantitative model which predicates the closing price of an equity on the next trading day,
the model closing prices derived from the quantitative model are compared with the
corresponding empirical closing prices observed from the equity market. If on most
trading days, the model closing prices are close to the empirical closing prices, the
quantitative model is considered to be accurate.
This assessment is formalized through statistical hypothesis testing:
Null hypothesis: Empirical closing price - Model closing price = 0
Alternative hypothesis: Empirical closing price - Model closing price ≠ 0
With a sufficiently large size of samples and at a significantly high confidential level, if
the alternative hypothesis is rejected, then the quantitative model may be adopted for
production.
Banks using quantitative models to derive estimates of credit risk factors, in particular,
the PD. Therefore, these quantitative models should be subject to similar statistical
hypothesis testing in order to ensure that a bank can measure its credit risk with sufficient
accuracy. Nevertheless, it is difficult to conduct statistical hypothesis testing of
quantitative models which derive estimates of credit risk factors, primarily because:
• There is a lack of historical default records due to banks’ conservative lending
practices;
• Empirical default is a binary process (0 or 1) which cannot be used directly to
validate a PD having any value between 0 and 1; and
• The empirical CCC is unobservable.
These limitations prevent the development of a rigorous and universal standard on model
validation for credit risk factors. Regulators therefore adopt an alternative methodology,
which comprises both qualitative and quantitative requirements, to assess whether a bank

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is technically competent to use the IRB approach to calculate the capital charges for
credit risk. This mixed assessment process is referred to as the regulatory IRB validation.
19.2 Principles of regulatory IRB validation
In 2005, the Validation Subgroup of the BCBS’s Accord Implementation Group
published a paper which elaborated the concept of regulatory IRB validation in six
principles:
• A bank has the primary responsibility for the regulatory IRB validation;
• Regulatory IRB validation is fundamentally about assessing the predictive ability of a
bank’s credit risk estimates and the use of ratings in credit processes;
• There is no single method of regulatory IRB validation;
• The regulatory IRB validation is an iterative process;
• The regulatory IRB validation should encompass both qualitative and quantitative
elements; and
• The regulatory IRB validation processes and outcomes should be subject to
independent review.
Nevertheless, many specific areas concerning the regulatory IRB validation remain
unclear, and the public documents issued by most regulators in the major financial
markets have taken the form of research studies, working papers and/or studies of
practices adopted by the financial industry. Explicit guidance from regulators on the
regulatory IRB validation remains outstanding. To address this issue, this chapter takes a
more prescriptive approach to describe the regulatory IRB validation, with an aim to
reduce the grey areas in the validation process.
19.3 Components of the validation process
Broadly speaking, the regulatory IRB validation process seeks to demonstrate that a
bank’s IRB systems can deliver estimates of credit risk factors with sufficient accuracy.
The BCBS believes that by satisfying certain qualitative and quantitative requirements
around the IRB systems, these IRB systems are considered to be qualified.
19.3.1 Board and senior management oversight
A bank should place substantial emphasis on the systems and controls environment in
which its IRB systems are developed, implemented and operated. In particular, an