Transfer pricing

Transfer pricing and valuations: The devil is in the data

insight featured image

Transfer pricing is more than a compliance exercise—it’s essential to operating a multinational enterprise regardless of size. It can have a material impact on the after-tax profits your business can use to reinvest in itself or distribute to shareholders as dividends. Transfer pricing data—from various analyses that rely on the non-consolidated financial data attributed to particular entities within a multinational group—can also significantly impact results. Simply put, relying on inadequate data can cost you. Determining if your data is reliable is critical to making strategic decisions and avoiding harsh penalties and loss.  

Unreliable transfer pricing = unreliable data = unreliable valuations

Recently, our team at Grant Thornton LLP provided transfer pricing advice involving a foreign subsidiary's enterprise value, reinforcing this valuable lesson. The matter involved the enterprise value of two chains of foreign subsidiaries of a Canadian-based multinational, which a buyer had acquired for a combined price. During negotiations, the buyer and seller agreed to allocate the purchase price between these two chains after closing the deal. 
The enterprise value of each chain of foreign entities was determined using the discounted cash flow (DCF) method. A DCF estimates the value of an enterprise by calculating the after-tax net present value of its forecasted earnings before interest and tax (EBIT). The quality of any DCF analysis relies on the quality of the financial data used to predict future EBIT and other assumptions. 
In this case, our team identified that the entities along one chain had material transactions with their related parties along the other chain. For that reason, the financial data used to calculate the future EBIT of the entities along both chains was materially impacted by the transfer pricing policies governing these related party transactions. Our advice helped the client to demonstrate that these related party transactions were materially mispriced and, as a result, the DCF analysis produced a materially incorrect enterprise value for both chains—one valued too low and the other too high. Had these values not been corrected, the DCF analysis would have had material tax consequences. Valuing an entity too high could have resulted in the seller reporting higher capital gains and an immediate tax payment. Materially mispriced related party transactions could also have exposed the buyer to potential future transfer pricing adjustments and penalties unless compensated by the seller.  
Remembering Ford Motor Company of Canada v. OMERS et al
This recent matter is reminiscent of another case heard before the Ontario Superior Court, Ford Motor Company of Canada, Limited (Ford Canada) v. Ontario Municipal Employees Retirement Board (OMERS) et al., (98-CL-3075). OMERS and other minority shareholders claimed Ford Motor Company's (Ford US) offer of $185 per share to privatize Ford Canada was inadequate because they took issue with Ford US's transfer pricing policies. For 19 consecutive years, these policies resulted in Ford Canada losing money selling vehicles purchased from Ford US in Canada. The assumption that such losses would continue understated Ford Canada's future earnings and the present value of its future cash flows. The defendants were awarded a fair value of $207 per share for the go-forward component of a Ford Canada share and up to an additional $52.36 per share for the historical oppression caused by Ford's transfer pricing system during a specific period before its privatization.

Other related party transactions can also be affected by unreliable transfer prices

DCF models are also used to estimate the value of intangibles or the royalty rates to license them. Again, the reliability of the estimates derived using a DCF analysis in these cases depends on the financial data quality. Suppose the transfer pricing policies are inconsistent with the arm's length principle. In that case, the financial data will be unreliable, as will the results from any DCF analysis relying on that data.

The same holds for pricing other related party transactions. The analysis used to measure a borrower's creditworthiness in an intercompany loan or loan guarantee depends on the borrower's standalone financial data. The transactional net margin method relies on the tested party's standalone financial data. Transfer pricing policies inconsistent with the arm's length principle yield unreliable standalone financial data and that kind of data produces unreliable transfer pricing analyses.  

We can help

Transfer pricing can be complex but with the right advice, it’s possible to find and use quality data to achieve the best outcome. Our award-winning transfer pricing team can evaluate your company's transfer pricing policies to determine whether they unduly impact the reliability of the standalone financial data being relied on to price enterprises, tangibles, intangibles, and interest rates. Contact us today.  

Brad Rolph
T +1 416 360 5021