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Blog — 9 Jan, 2023
By Lois Beyriere and Guilhem Tranchant
This article is written and published by S&P Global Market Intelligence, a division independent from S&P Global Ratings. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit scores from the credit ratings issued by S&P Global Ratings.
Intercompany finance compliance can be time-consuming, labor-intensive and often challenging, yet it is one of the most important taxation issues facing multinational organizations today. Manual processes, data and reporting period disparities, and new regulatory environments make it hard for companies to navigate intercompany accounting successfully. As international obligations grow, however, it is critically important to have access to the right data and tools to manage the pricing of cross-border transactions.
On November 29, 2022, S&P Global Market Intelligence held an interactive discussion on tackling the challenges of intercompany finance. This article summarizes the highlights of the session.
Moderator: Lois Beyriere, Senior Credit Product Specialist, Credit & Risk Solutions, S&P Global Market Intelligence
Presenter: Guilhem Tranchant, Team Lead Southern Europe, Credit & Risk Solutions, S&P Global Market Intelligence
Session Summary
When transfer pricing professionals think about workflow frameworks, they often consider tax authority requirements, which are typically aligned with the OECD Transfer Pricing Guidance (“Guidance”). The Guidance calls for being able to:
Two approaches can be used to calculate the appropriate transfer price: expert judgment and quantitative. Credit ratings reflect expert judgment. While they are the golden source in terms of risk assessment, they cover a limited universe, with S&P Global Ratings covering 9,000 companies around the world, for example.
On the quantitative side, there are two main company financials-driven models that are used by clients of S&P Global Market Intelligence (“Market Intelligence”), that are part of the Credit Analytics suite of models. The first is CreditModelTM, is a powerful suite of over 100 statistical models, trained on credit ratings from S&P Global Ratings to help you evaluate the long-term creditworthiness of public and private, rated and unrated companies. The first model output is a score aligned with the S&P Global Ratings’ scale (i.e., ‘AAA’ to ‘D’) using lowercase nomenclature to differentiate it from a credit rating.[1] The second output is a probability of default (PD). This model works well for larger public and private entities, and scores are automatically generated for approximately 450,000 companies.[2] It should be noted that users can also leverage the backend scoring engine should they want a score that is not included or would like an alternative assessment.
The other is the Probability of Default Fundamental (PDFN) model, which is aligned with 20 years of default data, where the model tries to predict the likelihood of default. Here, the initial output of the model is a PD that is matched to a score aligned with the S&P Global Ratings’ scale. The model works well for public and private entities of any size, and scores are automatically generated for over 8 million entities. Depending on the type of company, one or the other model should be used.
Historically, we had two modules on the S&P Capital IQ platform used for transfer pricing: the Credit Analytics risk models described above and a yield curve analysis, dedicated to the benchmark based on all bonds rated by S&P Global Ratings. To bring everything together, a new module called Credit Risk Pricing was created two years ago. The workflow for Credit Risk Pricing involves the following four steps:
Step 1: Scoring Inputs — Input financial and non-financial data for the subsidiary or affiliate
The analysis starts by leveraging Market Intelligence’s comprehensive database of financials to input company details automatically. Alternatively, users can manually input their proprietary financials. If values are missing, an imputation function estimates them, if desired.
This initial screen also asks for two non-financial information (country and Industry) that are converted into qualitative risk factors (country risk and Industry risk). Qualitative factors are important from the OECD perspective, and the country/industry information provides essential insight into the subsidiary/affiliate from a standalone basis before any parental support. These inputs can be adjusted if users have an alternative perspective.
Step 2: Adjustments & Overlays — Input additional information as desired
Three areas are considered that can positively or negatively impact the final credit score:
Six Qualitative Factors: The Guidance suggests adding qualitative information where available. For example, this could include how diversified a subsidiary is by country/product line/customer base, its competitive position, and its capital structure. Qualitative information is ranked from excellent to vulnerable.
Parental & Government Support (PGS): The Guidance acknowledges that PGS can affect the borrower's creditworthiness, and this feature factors in the financial health of the parent company. If the parent is covered in the Market Intelligence database, all information will be automatically populated. The only qualitative consideration to be added is the support expectation of being positive, neutral, or negative.
The Transaction: The solution will deliver two scores: the issuer score (based on all information filled so far) and the issue score (based on the issuer score plus the transaction characteristics).
Step 3: Credit Risk Score — Click to generate a standalone credit score
Once the financials and optional adjustments have been entered, users simply click to generate a PD in percentage terms and the associated letter grade credit score. The score is broken into the standalone score based on the company's characteristics, the score with qualitative overlays, the score with parental support, and finally, the score with parental support but sovereign capped. Outputs shown in this step also includes the full-term structure of PDs by time buckets from 1 month to 35 years. If a user has filled in the transaction characteristics, this step will also deliver the Loss Given Default and the expected loss.
As required by the OECD, the model is fully transparent. Users can easily explain or interpret outputs and get access to the methodology in the backend of each scoring model.
Step 4: Credit Risk Pricing — Construct a yield curve and produce the final interest rate
The final adjusted score (issue score) is then matched to the corporate yield curve based on four criteria: currency, sector, rating/score, and maturity, which automatically generates an all-in-yield interest rate. A new interest rate can be easily generated by adjusting any of the four criteria and clicking ‘update’. In addition, the yield curves used to calculate the interest rate are provided along with the curve transparency, which is the composition of the curve (i.e., the observed bonds used to estimate the yield at spend).
Finally, when the workflow is complete, the results can be exported to Word or a PDF. The modules can also be used independently to simply score a company or get a benchmark.
Market Intelligence currently has over 100 clients worldwide (including seven tax authorities) using this transfer pricing analysis tool and access to a dedicated team of specialists. We also offer Credit Assessment Scorecards, a solution that can be used for alternative asset classes (e.g., real estate asset finance, investment holding companies, project finance, and alternative investment funds). Our scorecards are broadly aligned to S&P Global Ratings' criteria, and are further supported by historical default data dating back to 1981.
Contact us to learn more about our Credit Risk Pricing solution.
[1]S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD credit model scores from the credit ratings issued by S&P Global Ratings.
[2]Coverage numbers as of January 2022.