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Meeting the Revised OECD Transfer Pricing Guidance on Financial Transactions: A Spotlight on Issue Risk Assessment

On February 11, 2020 the Organization for Economic Co-operation and Development (OECD) published the “Transfer Pricing Guidance on Financial Transactions” (Guidance). This offers long-awaited further guidance for corporate tax payers, auditors, and tax authorities in relation to Base Erosion and Profit Shifting (BEPS) Action 4 and Actions 8-10.[1]

The purpose of the Guidance is to clarify the application of principles outlined in the “OECD Transfer Pricing Guidelines for Multinational Enterprises (MNEs) and Tax Administrations”, originally published in 2017. In particular, the recent Guidance represents a common view on the treatment of intercompany financial transactions regarding the delineation analysis, as well as the arm’s-length pricing of those transactions (e.g., intra-group loans, cash pools, and guarantees).

One of the key aspects with regards to intragroup loans relates to the consideration of group membership, also known as implicit support. The Guidance now explicitly acknowledges that a group membership may affect the creditworthiness of the borrower, which results in potential adjustments – either positive or negative – to the S&P Global Market Intelligence’s Credit Analytics stand-alone credit score.[2] The Credit Analytics solution, available on the S&P Capital IQ platform, has incorporated a “Parental & Government Support” overlay (PGS), which addresses implicit support. It therefore utilizes quantifiable, as well as qualitative, overriding factors that classify the MNE in one of three categories: core subsidiary, strategically important subsidiary, and non-strategic subsidiary.

The aim of this overlay for parental support is to add or subtract notches to the so-called stand-alone credit risk assessment of an entity from Credit Analytics credit risk models, such as CreditModelTM or Probability of Default (PD) Model Fundamentals. Due to its sophisticated framework, the PGS overlay has been in use for years by many transfer pricing practitioners.

There is another aspect of the Guidance that previously wasn’t given careful consideration, namely the use of issue versus issuer credit ratings. This relates to paragraph C.1.1.2.2. : “The credit rating of a specific debt issuance” and 10.70 therein: “[…] when both an issuer and issue rating are available, the issue rating of the particular debt issuance would be more appropriate to use to price the controlled financial transaction.” How should tax professionals cope with the newly-emphasized issue risk determination?[3] To answer this question, an additional concept has to be introduced, namely the assessment of Recovery Given Default (the inverse of Loss Given Default). This framework allows us to estimate the percentage of principal and accrued interest due at the point of hypothetical default on a company's debt instruments to be recovered following its emergence from a hypothetical bankruptcy.

Credit Analytics features the LossStats approach, which returns a recovery estimate that assumes that the MNE has hypothetically defaulted on its debt obligations. It takes into account the seniority structure (i.e., senior secured, unsecured, subordinated loans, or the actual capital structure characteristic), including potential collateralizations, industry riskiness, and the macroeconomic environment.

The example depicted in Figure 1 for the hypothetical company entity “SuperVision” showcases the workflow for a non-investment grade credit exposure.

Figure 1: Sample Workflow

Source: S&P Global Market Intelligence, April 2, 2020. For illustrative purposes only. 

Once the Recovery Given Default estimate has been returned, a lookup table is utilized that translates the recovery value into an issue risk assessment. Following S&P Global Ratings’ criteria,[4] and assuming an issuer risk assessment includes the implicit support consideration for ‘BB-’, the example assessment in Figure 2 would result in a one notch upward adjustment.

Figure 2: Sample Assessment

For illustrative purposes only.

The issue credit score of ‘bb’ would then be utilized to determine the Comparable Uncontrolled Price (CUP) method, which is considered the most appropriate approach in the context of intra-group loans, not the least of which is due to the large amount of public data available on such transactions. S&P Capital IQ Corporate Bond Yield Curves, which are sector-, credit risk score-, duration-, and industry-specific, can be used for this benchmarking exercise. For instance, consider Figure 3 that shows EUR and USD denominated All-In Corporate Yield Curves for the industrials sector, 5Y, ‘BB’ risk category over a one-year timeframe as the foundation to price the loan associated with a credit risk score of ‘bb’ accordingly.

Figure 3: Corporate Yield Curves

Source: S&P Capital IQ Corporate Yield Curves, April 2, 2020. For illustrative purposes only.

The recent OECD Guidance certainly brings new challenges, but also specifications that will hopefully lead to less uncertainty regarding analytical requirements for transfer pricing and, therefore, more reliable estimates. The aforementioned framework addresses one of those specifications: how to derive an issue risk assessment using a sound and comprehensive approach. This can help companies meet regulatory requirements, and also have greater insight into business operations and potential risks.



[1] The Actions provide governments with domestic and international rules and instruments to address tax avoidance.

[2] 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 credit model scores from the credit ratings issued by S&P Global Ratings.

[3] S&P Global Market Intelligence is not a tax advisor and does not provide tax advice.

[4] Recovery Rating Criteria For Speculative-Grade Corporate Issuers, S&P Global Ratings, Muthukrishnan, Gillmor, and Wilkinson, December 7, 2016, revised February 4, 2020.

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