A new transfer pricing perspective – ratio analysis techniques

There are many ways of supporting cross border related party transactions from an arm’s length perspective, but sometimes there are options that we may just not think about at the time. This blog post will focus on two specific ratios which you may not have considered but could make your analysis (or life) much easier.

A ratio is a statistical indicator that provides a measure of the relationship between two figures. This relationship can be expressed as either a percentage or as a quotient. In transfer pricing we use ratios to interpret the financial data of our tested party to that of identified comparables.

Typical ratios used in a financial analysis include:

  • Gross profit ratio (GP/revenue)
  • Gross profit margin (COGS/revenue)
  • Operating margin (OM) or return on sales
  • Return on total cost (ROTC) or referred to as net cost plus

But these ratios have their limitations. For example, what if we are trying to test a procurement company that takes flash title but no risk in relation to the goods. We are going to struggle to just apply one of the above ratios as the purchase price or sale of the goods may be reflected in the tested party’s financials.

Or what if we have an intermediary company that buys from and sells to related parties, again this may be a procurement company. In this case it is likely that both the costs and sales numbers of the tested party are ‘tainted’ (e.g., we should not use a related party transaction to support the arm’s length nature, as it is the transaction we are trying to test).

Or what if we find comparable companies that are truly comparable except for making a loss in one or two years of our analysis. Is there a way to get more comfort that the company is not under financial strain and the results are actually acceptable?

Two ratios that may assist you with the above are the Berry ratio and the Altman Z-score model. I will touch on each below:

Berry Ratio

The OECD Guidelines added the Berry ratio as one of the profit level indicators under the transaction net margin method and the concept can also be found in the UN Manual. This means that if the facts and circumstances allow for the Berry ratio to be applied it should be acceptable as long as your country follows the above mentioned guidance.

The Berry ratio is defined as the ratio of gross profit to operating expense (OPEX). When calculating GP, interest and any unrelated income are generally not considered and when calculating OPEX, depreciation and amortization may or may not be included depending on the facts and circumstances. Please keep in mind that COGS does not form part of OPEX which is the beauty of this ratio, it only includes additional or also referred to as value added expenses. In other words the ratio expresses a measure of gross profit return earned on the value added functions performed by the tested party.

This means that the ratio is only really applicable to limited risk distributors or service providers. In relation to service providers we may want to look at a modified version of the Berry ratio which is discussed further below.

By not taking COGS into account we get around the problem of the flash title referred to above but we are still looking at this from a distribution angle rather than services (well for now at least). Furthermore, we get around the issue of being an intermediary company that buys from related parties and sells to related parties where a resale price method or cost plus method does not work (similarly the OM or ROTC). Importantly, the assumption is that our OPEX comes from third party expenses, which if it doesn’t the Berry ratio won’t work.

There are a few other points that the OECD Guidelines provide that must be met in order for the Berry ratio to be appropriate:

  • The value of the functions performed in the controlled transaction
    (taking account of assets used and risks assumed) is proportional to the
    operating expenses,
  • The value of the functions performed in the controlled transaction
    (taking account of assets used and risks assumed) is not materially
    affected by the value of the products distributed, i.e. it is not
    proportional to sales, and
  • The taxpayer does not perform, in the controlled transactions, any other
    significant function (e.g. manufacturing function) that should be
    remunerated using another method or financial indicator.
Modified Berry ratio

The Berry ratio can also be applied to service providers as mentioned above. In order to do so it is usually easier to modify the Berry ratio to reflect a operating profit (OP) / operating expense ratio. This is easily done by subtracting 1 from OPEX in our above equation. Don’t worry, I won’t bore you here with all the equations, but in the end we have OP/OPEX.

This ratio would work for advertising agencies and the like where there are certain pass through costs like advertising space that should not receive a mark-up. Another quick example could be a freight forwarder which pays third parties for distribution costs. As always we must make sure the numbers on the financial analysis are picked up correctly in the ratios, which is important for both the tested party and comparables.

Altman Z-Score

The Altman Z-Score (AZS) is a credit scoring model which predicts the probability that a company may go into bankruptcy within the next two years. As per Investopedia “The Altman Z-score is based on five financial ratios that can be calculated from data found on a company’s annual 10K report [annual financial statements]. It uses profitability, leverage, liquidity, solvency and activity to predict whether a company has a high degree of probability of being insolvent.”

The Z-Score is calculated as follows:

Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E


  • A = working capital / total assets
  • B = retained earnings / total assets
  • C = earnings before interest and tax / total assets
  • D = market value of equity / total liabilities
  • E = sales / total assets

If you would like a more in depth analysis of the above please follow the Investopedia link.

As a final step, the Z-Score can then be compared to the following zones and interpretations:

  • Z-Score of 2.99 and above = Safe zone (relatively low probability of becoming insolvent within a two-year period)
  • Z-Score of 1.81 to 2.99 = Grey zone (a good chance that the company may go bankrupt within the next two years of operations)
  • Z-Score of below 1.81 = Distressed zone (high probability that the company is headed towards bankruptcy)

I want to stress the point that this model assesses the likelihood of a company becoming bankrupt and does not provide a time frame.

Arguably this model is a little old with being implemented in 1968 and as such it may not be the most prudent model for determining a credit rating. There are some conversion models online that you can use to convert a Z-Score to a specific credit rating to give you an indication of what you are dealing with, but I am not sure if it is the best approach for determining a credit rating (especially not for material transactions).

From a transfer pricing perspective I do think that the AZS could be used to provide additional support why a comparable company from a benchmarking study should not be rejected for being loss making. In today’s time of transfer pricing we come across a lot of good comparables that are rejected purely for making losses. As these companies are independent the reason is more around financial distress, but if the Z-Score is above 2.99 we have a good argument that actually there is no financial distress and we should accept the company, unless there are other issues (like extraordinary events we cannot adjust for).

I hope you enjoyed my first transfer pricing perspective blog post and it added value to you. If you liked it, please share it. If you have any comments, feel free to contact me directly or share them below.


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