Our professional experience suggests that paragraph 3.3.2 of the Cabinet of Ministers’ Rule No. 802, “Transfer Pricing Documentation and Procedures for Entering Into an Advance Pricing Agreement Between the Taxpayer and the Tax Authority for a Transaction or a Type of Transactions”, which states that the taxpayer’s transfer pricing (TP) documentation should include financial information and tables showing how the financial data used in applying the TP method is linked to the financial statements, has taxpayers confused as a maze of legal interpretation.
Everything turns out to be quite straightforward. The above formulation applies to the taxpayer’s aggregated financial data for the financial year and to the need to prepare a TP financial statement, i.e. to carry out an appropriate profit & loss account data segmentation for benchmarking purposes, showing separately the financial information that applies to controlled1 transactions.
This article explores a simplified financial data segmentation and a new trend – the need to prepare a detailed financial data segmentation:
As we have written earlier, the State Revenue Service (SRS) has pointed out a key risk associated with providing incomplete information. A taxpayer’s TP documentation that gives information to show that his controlled transactions are arm’s length suffers from two significant errors:
It is important to note that section 15.2(14) of the Taxes and Duties Act authorises the SRS to fine the taxpayer (up to EUR 100,000 for each controlled transaction) if his TP documentation fails to provide the required information. This includes a lack of financial information.
Our experience suggests that more taxpayers are now confused about statutory requirements and consider the significant errors pointed out by the SRS. So the TP documentation includes financial data relating to controlled transactions (TP financial statements), including a financial data segmentation that shows the total profitability in the analysed transaction with related and unrelated parties (a simplified financial data segmentation).
However, considering the events we have seen globally over the last three years and the implications of the Covid-19 pandemic that have adversely affected the economic situation of various countries and industries and consequently the taxpayer’s profitability in transactions with suppliers, including related parties, this raises the question of whether preparing a simplified financial data segmentation only to meet the statutory requirement is sufficient and does not create TP adjustment risk for the taxpayer.
Let us look at a theoretical example. A taxpayer provides comparable (similar) construction services to related and unrelated parties. To measure the profitability (operating profit markup) in his controlled transactions and to conduct a benchmarking study, the taxpayer has prepared a simplified financial data segmentation:
Financial indicator |
Total (EUR) |
Services (EUR): |
|
to related parties |
to unrelated parties |
||
Net revenue |
10,000 |
6,500 |
3,500 |
Cost of goods sold |
8,000 |
5,300 |
2,700 |
Gross profit |
2,000 |
1,200 |
800 |
Selling costs |
1,200 |
780 |
420 |
Administration costs |
700 |
455 |
245 |
Total service costs (operating costs) |
9,900 |
6,535 |
3,365 |
Result of service |
100 |
–35 |
135 |
Operating profit markup (result of service / total service costs) |
1.01% |
–0.54% |
4.01% |
The simplified financial data segmentation shows that the taxpayer faces TP adjustment risk when assessing the result (operating profit markup) in his transactions with related and unrelated parties, because he failed to gain arm’s length income from his services to related parties and the difference3 must be included in the taxable base under section 4(2)(2)(e) of the Corporate Income Tax Act.
In such situations the taxpayer often tries to ensure his TP documentation includes a statement that the negative indicator results from the market conditions. However, such a general statement will not be sufficient, should the SRS decide to assess whether the controlled transaction is arm’s length. The situation could be saved by a detailed, well-grounded explanation of the factors having affected the taxpayer’s related-party transactions, as well as a detailed financial data segmentation that substantiates those factors.
The taxpayer’s financial result in transactions with related and unrelated parties may be affected by a variety of internal and external factors. In each particular case, this impact may vary according to the facts and circumstances of the transaction – its type, where it is performed, and the taxpayer’s strategy for a particular market (e.g. investing in market penetration or carrying out a customer winning/retention strategy).
As stated above, the impact of various factors on taxpayers’ business has been especially relevant in the last three years:
– It was totally or partially impossible to trade and perform services face-to-face, with additional idle-time costs arising from quarantine rules that had to be observed before services could be started in a particular country, etc.
– Transport costs were affected by higher fuel prices and supply chain disruptions.
– USD exchange rate fluctuations, etc.
When it comes to assessing the total profitability in controlled transactions, it is not possible to show the factors having affected particular transactions, so it is advisable to carry out a detailed financial data segmentation, for instance, to assess transactions by related party, by engagement, or by geographical market.
Let us again look at a theoretical example. The taxpayer’s situation is the same, but to measure the profitability in his controlled transactions, he has prepared a detailed financial data segmentation for related-party transactions:
Financial indicator |
Total (EUR) |
Services (EUR): |
|||
to related parties |
to unrelated parties |
||||
No. 1 |
No. 2 |
No. 3 |
|||
Net revenue |
10,000 |
1,200 |
2,700 |
2,600 |
3,500 |
Cost of goods sold |
8,000 |
1,250 |
2,050 |
2,000 |
2,700 |
Gross profit |
2,000 |
–50 |
650 |
600 |
800 |
Selling costs |
1,200 |
150 |
200 |
430 |
420 |
Administration costs |
700 |
84 |
189 |
182 |
245 |
Total service costs (operating costs) |
9,900 |
1,484 |
2,439 |
2,612 |
3,365 |
Result of service |
100 |
–284 |
261 |
–12 |
135 |
Operating profit markup (result of service / total service costs) |
1.01% |
–19.14% |
10.70% |
–0.46% |
4.01% |
The detailed financial data segmentation shows that the operating profit markup for related parties is not always lower than the markup in transactions with independent parties. And the detailed financial data segmentation for transactions with related parties No. 1 and No. 3 shows which cost items mainly affected the end result, so we may assess in detail the factors that increased the costs. In case No. 1, for example, the cause may be idle-time costs arising from Covid-19 restrictions, while in case No. 3 this could have been an aggressive marketing strategy focused on market penetration/ market share retention.
A detailed financial data segmentation shows the actual results of related-party transactions more accurately and allows the taxpayer to mitigate TP adjustment risk. This is especially important where the total results are negative or where there are legitimate grounds for certain controlled transactions being out of line, which is not so easy for the SRS to see when assessing the taxpayer’s financial data for the year in general.
We believe that the results of a detailed financial data segmentation will make the SRS unlikely to claim that the controlled transaction made in the financial year (the service rendered in our theoretical example) is not arm’s length, thereby eliminating TP adjustment risk.
If you have any comments on this article please email them to lv_mindlink@pwc.com
Ask questionAssessing compliance with the arm’s length principle in transfer pricing (TP) involves conducting a benchmarking study based on high-quality comparable data. While the taxpayer can use internally available data on his transactions with unrelated parties, it’s common practice to use external data obtained from commercial databases or other sources. Several comparable companies are selected from a database according to certain criteria to build a range of financial results. This often raises the question of which values in that range are acceptable to demonstrate that the taxpayer’s controlled transactions are arm’s length. This article explores how wide an arm’s length range may be used in Latvia and compares how this range is interpreted in Lithuania and Estonia.
Latvian transfer pricing (TP) rules provide that a company’s transactions with related parties must be arm’s length, whether the parties are Latvian or foreign tax residents. The arm’s length principle dictates that a company making comparable transactions under comparable conditions must receive comparable revenue, whether the transaction is with a related or an unrelated party. Basically companies know and understand this, yet there are various facts and circumstances that make this requirement difficult to enforce in real time. This is because before or during the transaction, companies often lack sufficient information on arm’s length prices that unrelated parties apply in comparable transactions. This is where companies can use a TP adjustment, which is not always so painful as it might originally seem. This article explores what TP adjustment a company can make by adjusting its taxable base for corporate income tax (CIT) purposes.
Taxpayers involved in cross-border transactions with related parties widely use globally recognised methods of analysis to show that their prices match market values. Selecting the most accurate method depends on the economic substance of a transaction and on the availability of credible information. Having limited access to a comparable data set often becomes an insurmountable obstacle to applying a particular method. This article explores some problems with data use, as well as international practice and potential solutions where the comparable uncontrolled price (CUP) method is used.
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