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What are Transfer Pricing Data Points, And 5 reasons to have them structured

Blog

What are Transfer Pricing Data Points, And 5 reasons to have them structured

Blog

What are Transfer Pricing Data Points, And 5 reasons to have them structured

Blog

What are Transfer Pricing Data Points, And 5 reasons to have them structured

Blog

What are Transfer Pricing Data Points, And 5 reasons to have them structured

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What are Transfer Pricing Data Points, And 5 reasons to have them structured

19.5.2022

Data in transfer pricing

In digital transfer pricing, data is essential. Data is different types of information that usually is formatted in a particular manner. For example, data can be in the form of words, numbers, images and so forth. And generally, there are two types of data: unstructured and structured data.

Unstructured data

Unstructured data is where the information is available in a wide range of formats, and a computer cannot quickly process it. It may need to be processed and stored by humans, who can analyze the information. Here are examples of unstructured data from a transfer pricing world:

Example 1: Extract from the OECD Guidelines 2022, p.333

Why is it unstructured data? Because it is raw text. To make things worse, it's not even a text, but a picture of the text. It has certain logic and facts embedded, but it is not machine-readable - you can't give a computer task to list allocation keys based on it (at least without using advanced AI technologies).

Example 2: Description of the transfer pricing case

Same as above, this is raw text with a certain logic, but only experienced humans can read and make sense of it.

Structured data

Structured data, on the other hand, is where data is usually structured in a particular format which makes it easier to analyze or process. It is available in a specific format like a spreadsheet or database, which computer programs can easily read or extract information from. Let's modify one of the previous examples to make it structured:

Now, the transfer pricing scenario from Example 2 is presented in a structured way - the information has specific characteristics (dimensions) and is formatted in the table. Each separate cell in the "data" column is a data point (BOLD). And since it is structured, we call it a structured data point.

Why do you need structured transfer pricing data points?

Traditionally, unstructured data is used in transfer pricing, which makes the entire process manual and error-prone. But the critical issue is that even if the information is available in the tables, it is not structured so that computer programs can easily analyze and make sense of it.

The answer lies in using structured data as part of a digital approach to transfer pricing. If a company collects structured information and stores it in a computer system, transfer pricing or financial specialists can easily analyze it and use it for transfer pricing policy and compliance purposes. Here are a few benefits of having structured data in transfer pricing:

Meet the authors

Author
Borys Ulanenko
Advisor to Aibidia and ArmsLength AI founder

Borys Ulanenko is a Digital Transfer Pricing Expert. Borys has more than 10 years of experience in transfer pricing, with a background in industry and consulting. In addition to advising Aibidia, Borys is the founder of the educational platform StarTax Education and the AI-driven solution ArmsLength.ai.

Borys is passionate about sharing his knowledge and experience with others. He loves explaining complex transfer pricing concepts in simple words and sharing his expertise with Aibidia and the tax community. He sees his mission in demystifying transfer pricing and making this exciting area of international tax available to everyone.

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What are Transfer Pricing Data Points, And 5 reasons to have them structured

Hereʼs Why You Should Get the Report

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See how peers are adapting to global change

Understand how 140+ MNEs and advisory firms are responding to shifting regulations, heightened audit scrutiny, and technology-driven change, and where your approach stands in comparison.

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Explore the approaches to resourcing, data management, and operational transfer pricing that teams are using to tackle growing workloads.

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Gain insight into how AI, automation, and operating models are redefining transfer pricing, so you can plan for the skills, tools, and processes youʼll need next.

Insights

What youʼll learn inside the Aibidia report 2025

The rising cost of tax scrutiny
01

The rising cost of tax scrutiny

Heightened tax authority demands are driving up the time and money TP teams spend on audits. Companies with stronger documentation processes, centralised data, and proactive OTP practices are better positioned to contain both costs and risk.

02

The state of OTP maturity

Only 35% of companies have a well-defined OTP process, while 24% have none at all. Barriers to OTP maturity include poor data access, complex business models, and limited coordination between tax, finance, and IT.

03

The importance of structured data

With 72% of companies in fragmented data environments, the report shows how centralised data helps TP teams insource more processes, ensure consistent compliance, and handle audits more efficiently.

04

Technology and AI adoption in practice

42% of MNEs are investing in specialist software, reducing reliance on traditional tools. AI interest is steady rather than explosive, hinting that TP teams need clean, structured data before advanced analytics can add value.

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Expert insights

Structured, reliable data is essential for executing a consistent, defensible transfer pricing strategy. Common barriers to structured data include siloed legacy source systems, unclear data ownership, and inconsistent definitions across entities and functions.

Prasad Parwidala
Head of Professional Services, Aibidia
Read the case study

We see significant variation in OTP maturity across companies. In many cases, if existing processes appear to work, there’s less motivation to change. However, where we see this changing, is within MNEs that have faced increased scrutiny or operate with more complex structures.

Pia Honkala
Global Commercial Head - Operational Transfer Pricing, Aibidia
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While there are many challenges in accessing the right data for TP calculations and analysis, one of the most significant barriers to OTP adoption can be the misalignment of KPIs between Finance and Tax teams.

Marlon Manto
Director, Transfer Pricing Advisory, Aibidia
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We’re seeing practical AI adoption in areas such as navigating country-specific documentation requirements, researching transfer pricing methods, comparing jurisdictional rules, and tracking global compliance timelines.

Maria Helander
VP Product, Aibidia
Read the case study