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A Comprehensive Guide to IFRS and CECL Credit Risk Modelling and Validation

Eddie Powell

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Published in IFRS 9 And CECL Credit Risk Modelling And Validation: A Practical Guide With Examples Worked In R And SAS

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Credit risk is one of the most significant risks faced by financial institutions. The ability to accurately model and validate credit risk is therefore essential for these institutions to manage their risk exposure and ensure their financial stability.

The International Financial Reporting Standard (IFRS) 9 and the Current Expected Credit Loss (CECL) standard are two accounting standards that have recently been introduced to enhance the reporting of credit risk. IFRS 9 requires banks to recognise expected credit losses (ECL) on a forward-looking basis, while CECL requires banks to recognise ECL on a current basis.

These new standards have led to a significant increase in the complexity of credit risk modelling and validation. In this article, we will provide a comprehensive overview of these processes, covering the key concepts, challenges, and best practices involved.

IFRS 9 and CECL Credit Risk Modelling and Validation: A Practical Guide with Examples Worked in R and SAS

by Tiziano Bellini

4.1 out of 5

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Credit Risk

Credit risk is the risk of loss that a lender may incur due to the failure of a borrower to repay a loan. Credit risk can be categorised into two main types:

Default risk: The risk that a borrower will fail to make a payment on a loan on time.
Loss given default (LGD): The amount of money that a lender will lose if a borrower defaults on a loan.

Expected Credit Loss (ECL)

ECL is the expected amount of credit losses that a lender will incur over the life of a loan. ECL is calculated by multiplying the probability of default (PD) by the LGD.

Impairment

Impairment is the recognition of a loss on a loan. Impairment is triggered when the ECL on a loan exceeds the carrying value of the loan.

IFRS 9

IFRS 9 is an accounting standard that was introduced in 2018. IFRS 9 requires banks to recognise ECL on a forward-looking basis. This means that banks must estimate the ECL on all of their loans, even if they are not yet in default.

CECL

CECL is an accounting standard that was introduced in the United States in 2016. CECL requires banks to recognise ECL on a current basis. This means that banks must recognise ECL on all of their loans, even if they are not yet in default.

Credit risk modelling and validation is a complex and challenging process. Some of the key challenges involved include:

Data availability: Accurate credit risk modelling requires a large amount of data, including historical data on defaults and LGDs. This data can be difficult to obtain, especially for smaller institutions.
Model complexity: Credit risk models are often complex and non-linear. This can make it difficult to validate the models and ensure that they are accurate.
Regulatory requirements: IFRS 9 and CECL have introduced new regulatory requirements for credit risk modelling and validation. These requirements can be complex and time-consuming to comply with.

There are a number of best practices that can be followed to improve the accuracy and validity of credit risk models. These best practices include:

Use a combination of internal and external data. Internal data can provide valuable insights into the creditworthiness of a bank's customers. However, it is also important to use external data to supplement internal data. External data can provide a more comprehensive view of the credit environment and help to identify emerging risks.
Use a variety of modelling techniques. There are a number of different credit risk modelling techniques available. The best technique will vary depending on the specific needs of the bank. However, it is important to use a variety of techniques to ensure that the models are not overly reliant on any one technique.
Validate the models regularly. Credit risk models should be validated on a regular basis to ensure that they are accurate and reliable. The validation process should include a thorough review of the model's assumptions, data, and results.
Document the modelling process. The credit risk modelling process should be documented in detail. This documentation will help to ensure that the models are transparent and auditable.

Credit risk modelling and validation is a complex and challenging process, but it is essential for financial institutions to manage their risk exposure and ensure their financial stability. By following the best practices outlined in this article, banks can improve the accuracy and validity of their credit risk models and ensure that they are meeting the latest regulatory requirements.

IFRS 9 and CECL Credit Risk Modelling and Validation: A Practical Guide with Examples Worked in R and SAS

by Tiziano Bellini

4.1 out of 5