Treatment of Extreme Results and Multiple-Year Data in Indian Transfer Pricing Law

[Ayush Chaturvedi and Chandni Bhatia are 4th Year B.A.LLB (Hons) students at Dr. Ram Manohar Lohiya National Law University, Lucknow]


Arm’s length price is obtained by conducting a detailed “comparability analysis” as per the rules laid down in the Income-tax Act, 1961 (“Act”), the Income-tax Rules, 1962 (“Rules”) and the OECD Transfer Pricing Guidelines for Multinational Enterprises and Tax Administrations, 2017 (“OECD Guidelines”). This analysis requires comparison of prices employed in the “controlled transaction” between the associated enterprises with those employed in “uncontrolled transactions” between independent enterprises. However, it is practically impossible to find two transactions which are entirely the same, and rule 10B of the Rules provides that the transactions in question will not be comparable if the dissimilarities materially affect the price or the profit arising from such transactions in the open market. These dissimilarities may be pertaining to certain factors like the functions performed or market conditions. This post deals with the factor of supernormal profits or losses arising in the uncontrolled transaction, its significance and its judicial treatment in India.

Extreme Results in Comparability Considerations

In accordance with rule 10B(2) of the Rules, while comparing the profitability of two companies in the same line of business, it is important to compare their functional aspects. It is probable that two companies with same profits may not be good comparables if their functions performed, assets utilized and risks borne (“FAR”) differ significantly from one another.  This creates an issue at the time of finding appropriate comparables, specifically in a case where such comparables are earning super-normal profits. A view is sometimes taken that comparables earning super-normal profits should be rejected at the very outset as is the case where quartile or inter-quartile range is used for arriving at Arm’s Length Price (“ALP”). The OECD Guidelines observe that extreme results might consist of unusually high profits or losses. Extreme results can affect the financial indicators that are looked at in the chosen transfer pricing method (e.g. resale price, net profit indicator, transactional net margin). They can also affect other factors, which may be below the line but nonetheless reflect exceptional circumstances. Where one or more of the potential comparables have extreme results, further examination would be needed to understand the reasons for such extreme results.[2] The OECD Guidelines mandate carrying out of investigation by the taxpayer for determining the reasons of extreme results; therefore, comparables should only be excluded from the final set, provided the extreme results are due to presence of extraordinary circumstances which are not reflective of the performance of the industry in which the comparables operate.

Treatment in India

Rule 10B(2) mentions that reference needs to be made to the functions performed, taking into account assets employed or to be employed and the risks assumed by the respective parties to the transactions

No specific guidance is contained in the Indian transfer pricing regulations, i.e. Sections 92 and 92A to 92F of the Act read with rules thereunder, on exclusion of comparables having extreme results although the Central Board of Direct Taxes (“CBDT”) has issued guidelines for application of the concept of ‘Range’ by way of Notification No. 83/2015 dated October 19, 2015 but the same is applicable only in circumstances where at least six comparables are present in the dataset. Arriving at ALP through application of such range helps in taking care of the effect of extreme results, including both profit and loss which are absent in the case of arriving at ALP via arithmetic mean which remains to be dominant under the Indian regulations.

On a perusal of tribunal cases on this issue, it can be observed that Indian tax authorities tend to exclude comparables having diminishing revenue or consistent losses on the premise that these comparables do not represent the performance of the industry and hence would close down in years to come. Such an approach is not applied to comparables earning super-normal profits. These comparables are “cherry-picked” for determining the final set of comparables. This particular Indian approach tends to increase the tax base for the revenue authorities as, under the Indian transfer pricing regulations, the arm’s length margin has to be the arithmetic mean of margins earned by the comparables. On this practice of “cherry-picking”, a set of favourable third-party comparables either by the assessee or the tax authorities, the UN Transfer Pricing Manual, 2017 observes that “it must be ensured that potentially relevant external comparables are not excluded because of “cherry picking” of favourable third party information by either the taxpayers or the tax authorities, ignoring other information that does not support the position argued for. To come to a correct conclusion, an unbiased analysis of the facts and circumstances surrounding the transactions has to be carried out. Further, in few recent cases, a consistent approach of sticking to the FAR principle has been adopted thereby excluding further analysis of such factors. For example, The Delhi Income Tax Appellate Tribunal (“ITAT”) in the case of Adobe Systems India Private Limited[5] held that comparables earning super-normal profits should be rejected out-right. However, the ITAT did not analyze the rationale for such high profitability.

There has been case law where the issue of exclusion or inclusion of comparable based solely on supernormal profits or losses has been raised. In Nortel Networks India (P.) Ltd. v. Additional Commissioner of Income-tax,[6] the ITAT observed that the specific characteristics of services provided, assets employed and risk assumed, i.e., the FAR analysis of the comparable, is decisive for inclusion or exclusion of comparables and that higher or lower rate of profit is nowhere prescribed as the determinative factor in this behalf. Only if the higher or lower profit rate results on account of effect of factors given in rule 10B(2) read with sub-rule (3), such a case shall merit omission. If higher profits are achieved due to factors not mentioned in the rule, then such case shall continue to find place in the list of comparables. 

A landmark ruling on this issue was rendered by Delhi HC in the case of Chryscapital Investment Advisors (India) (P.) Ltd. v. Deputy Commissioner of Income-tax,[7] where the Transfer Pricing Officer (“TPO”) had included three entities as comparables which had very high profit margins as compared to that of the assessee and made certain additions to the assessee’s ALP. The assessee’s contentions with respect to the exclusion of the said three entities were based only on their exceptionally high profit margins for the assessment year in question and not on the grounds of functional dissimilarities. The Court observed that the mere fact that an entity makes high, or extremely high, profits or losses does not lead to its exclusion from the list of comparables for the purposes of determination of ALP. In such circumstances, an enquiry under rule 10B(3) ought to be carried out, to determine as to whether the material differences between the assessee and the said entity can be eliminated. Unless it is the case that the differences cannot be eliminated, the entity should be included as a comparable.

Thus, according to the High Court, in case extreme profit margins are observed, a further inquiry needs to be made in order to determine the suitability of the comparables. Since the purpose of transfer pricing is to make sure that the prices charged by the assessee are at arm’s length, the size of the turnover or the profit/loss margins of the assessee and comparable become vital factors which are required to be looked into. Further, if such differences in the turnover or the profit or loss margin is affecting the price or cost materially, they have to be removed by making suitable adjustments. If it is found that such high turnover or profit or loss is affecting the comparability and suitable adjustment is not possible to be made to remove such differences, it is only then that such comparable should be excluded. This is in line with the UN Transfer Pricing Guidelines, 2017 which in this regard observes that in order to come to a correct conclusion, an unbiased analysis of the facts and circumstances surrounding the transactions has to be carried out. Where one or more of the potential comparables are loss-making, further examination would be needed to understand the reasons for such losses and confirm whether the loss-making transaction or company is a reliable comparable.

This ruling of the Delhi High Court has been consistently followed by the tribunals throughout the country, although there has been an aberration in a Bombay High Court decision of CIT v. Pentair Water India Pvt. Ltd.[8] where the turnover of comparables was exponentially high compared to turnover of assessee company. It was held that the entities were not good comparables based solely upon the difference in turnover without going into any further inquiry. However, this case has been distinguished in subsequent decisions of the tribunals on the basis that the argument regarding any further enquiry was not brought forth before the bench.[9]

Multiple-Year Data

The use of multiple-year data assumes importance in the Indian context because, unlike OECD Guidelines which provide for an ‘inter-quartile methodology’ or ‘quartile methodology’, the Indian transfer pricing regulations provide mainly for “arithmetic mean” and the concept of range is restricted only in certain cases.[10] When data is gathered for comparable uncontrolled companies or transactions, there are often unrecognizable factors that might affect the data, causing them to either be too low or too high. Arithmetic mean has an inherent shortcoming of not excluding the effect of such factors, which may distort the overall results of the analysis.

According to Chryscapital, in case extreme results are observed in the comparable data, further inquiries need to be made in order to arrive at a finding on whether the comparable is suitable to be taken into account to arrive at an ALP. With this background, the issue of multiple-year data gains importance. Paras 1.49 to 1.51 of the OECD Guidelines recommend the use of multiple-year data because such data generally provides additional information on the product life cycle. The multiple-year data use can also mitigate the effect caused by business cycles or other economic distortions. The UN Transfer Pricing Guidelines observe that examining multiple-year data may be useful in a comparability analysis, but it is not a systematic requirement. Multiple-year data may be used where they add value and make the transfer pricing analysis more reliable. Circumstances that may warrant consideration of data from multiple years include the effect of business cycles in the taxpayer’s industry or the effects of life cycles for a particular product or intangible.

However, the Indian law is restrictive in this matter. The rules regarding use of multiple-year data were announced by the CBDT in 2015,[11] wherein it was provided that multiple-year data can only be used if the most appropriate method selected for benchmarking purposes is either Transactional Net Margin Method, Resale Price Method or Cost-Plus Method. Further, the data for the current year is mandatory to be considered. Most notably, rule 10B(4) as a general rule provides that only the relevant year’s assessment data should be taken into account. However, use of multiple-year data has been allowed for by way of the proviso to rule 10B(4) only where such data reveals facts which could have an influence on the determination of transfer prices.

Thus, in a scenario where an otherwise functionally similar comparable has extreme profit or loss margins, reliance may be placed on multi-year data as it will be useful in discovering, for example, whether the extreme results is due to exceptional circumstances or whether the comparables with similar FAR earn such level of profit in normal course. Conclusions based on multiple-year data would be one of the relevant factors in deciding whether or not comparable needs to be included or not in the TP analysis. However, the onus to lead evidence in order to be able to use multiple-year data remains upon the assessee.

It should be noted that Indian courts have imposed a restrictive threshold in order to allow the assessee to rely on multiple-year data. In Chryscapital, the Court has, on the issue of use of multiple-year data by the assesse, observed

The transfer pricing mechanism in the act and the rules prescribes that while determining the ALP, the arithmetic mean of all the comparables is to be adopted. This is to offset the consequences of any extreme margins that comparables may have and arrive at a balanced price. Similarly, the wide fluctuations in profit margins of the same entity on a year to year basis would be offset by taking the arithmetic mean of all comparables for the assessment year in question. In any case, in the event that the volatility is on account of a materially different aspect incapable of being accounted for, the analysis under Rule 10B(3) would exclude such an entity from being considered as a comparable.

The tribunals have consistently followed this decision on the question of use of such data which has led to a restrictive approach whereas the same may be an important factor for arriving at sound conclusions for determination of relevant comparable for arriving at ALP. This intent of placing primary reliance on relevant assessment year data is further discernible from the use of ‘shall’ in rule 10B(4) and use of ‘may’ in the proviso which provides for use of previous year data.


The problem regarding the use of extreme results and multiple-year data could have been easily resolved by providing more liberal rules for the use of concept of range. For example, US transfer pricing laws provide for a liberal use of the concept of range and acceptable ALP may range from 25th to 75th percentile whereas, in India, the same is allowed to be used only when at least six or more comparable are available and the acceptable ALP percentile is between 35 to 65. Notwithstanding the above, extreme results, including both profits and losses, is an important factor which should be carefully looked at in the comparability analysis to arrive at a consistent ALP, while at the same time it is worthwhile to mention that the same should not be used by way of “cherry-picking” to reach at pre-determined conclusions either by the tax-authorities or the assessee. The decision of the Delhi High Court goes a long way in consolidating the position in this regard; however, the latter part of the judgment dealing with the use of multiple-year data leaves a lot to be desired as multi-year data can be very useful in determining the true reasons behind the extreme results in the dataset of comparables. The above mentioned financial parameters provide useful guidance in ascertaining the functional profile of a tested party vis-à-vis comparable companies, and should be used together as tools to determine whether there are material differences between the taxpayer and potential comparables.

Ayush Chaturvedi and Chandni Bhatia

[2] OECD Transfer Pricing Guidelines for Multinational Enterprises and Tax Administrations, 2017, para 3.63.

[5]I.T.A. No. 5043/Del/2010.

[6] [2014] 44 26 (Delhi – Trib.).

[7] ITA 417/2014.

[8] Tax Appeal No. 18 of 2015.

[9] Income-tax Officer v. IGEFI Software India (P.) Ltd.

[10] Rampgreen Solutions (P.) Ltd. v. Commissioner of Income-tax.

[11] Notification No. 83/2015 dated October 19, 2015.

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