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Streamlining the Evaluation of Credit Risk


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Streamlining the Evaluation of Credit Risk


The auditing team needed a well-tested solution to assess the PDs of a large number of end customers of their clients, and more so, those with limited financial data.

Auditing companies are responsible for reviewing the financial statements of their clients to ensure that these records are correct. Many factors are taken into consideration, including the creditworthiness of an audit client’s end customers for the purpose of provisioning. All this must be done in a timely fashion, so fully-audited financial statements can be made publicly available.

Pain Points:

This accounting firm has many auditing clients that are listed on the Singapore Exchange. These clients themselves have a large number of end customers that are small, thereby making it difficult to gain access to financial details to assess their ability to pay accounts receivables. The auditing team needed to put in place an efficient and credible system to evaluate this large universe of companies with limited information. With the new International Financial Reporting Standard (IFRS) 9 now in place, this also calls for calculating forward-looking probabilities of default (PDs) in order to determine a client’s provisioning numbers for potential losses.

The Solution:

The auditing team was looking to work with a well-respected risk solutions provider that could offer an array of analytical tools in addition to data. They turned to S&P Global Market Intelligence (“Market Intelligence”) to learn more about the company’s capabilities. 

Market Intelligence representatives recommended that the firm use a credit scoring module within the suite of Credit Analytics solutions. This provides a simplistic framework for calculating PDs using a model that is trained on S&P Global Ratings’ default database.¹ For audit clients with larger accounts receivables, financial information can be used to calculate individual PDs. For the remaining clients, the Expanded PD framework creates proxy PDs based on a combination of industry and geographic factors, which provide the needed context. Point-in-time adjustments then account for credit cycle and market considerations, creating the forward-looking estimates required to comply with IFRS 9.

Whitepapers and ongoing support helped the audit team understand the construction of the models and the applicability to their particular situation. This transparency and assistance was especially important because this was the first year that IFRS 9 provisioning was required, and the team needed to fully appreciate the process for implementation. 

Key Benefits:

The Credit Analytics solution enabled the auditing team to quickly understand and apply the tools to meet their time-sensitive deadlines. The team also valued a number of other features:

  1. A well-tested methodology. A rigorous development process and annual re-calibrations validate that the tools remain predictive of default risk.
  2. An approach that can be used with limited financial data. The solution can be used when there is a lack of data available to construct statistical models that can be calibrated and validated. 
  3. The ability to quickly evaluate a large number of companies. An easy-to-use web-based capability helps automate the creation of credit scores and PDs.
  4. Point-in-time Adjustments. Help adjust PDs to forward looking estimates of defaults.
  5. Transparency. Technical documentation and white papers explain the development process, use of data, and overall model performance.
  6. On-going support. On-site training helped the auditing team become familiar with the capabilities, and on-going support continues to address the team’s needs.
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