Signal model Sales Tax Abroad (OBB)

Dutch Tax and Customs Administration

This page contains information about the 'OB Buitenland (OBB)' algorithm. This algorithm helps employees of the Tax and Customs Administration determine the turnover tax returns of entrepreneurs based outside the Netherlands.

Last change on 4th of March 2025, at 8:22 (CET) | Publication Standard 1.0

• Publication category: Impactful algorithms
• Impact assessment: Field not filled in.
• Status: In use

General information

Theme

Public finance

Begin date

Field not filled in.

Contact information

[e-mail]

Link to publication website

https://over-ons.belastingdienst.nl/onderwerpen/omgaan-met-gegevens/algoritmeregister/

Link to source registration

https://over-ons.belastingdienst.nl/onderwerpen/omgaan-met-gegevens/algoritmeregister/signaalmodel-omzetbelasting-buitenland-obb/

Responsible use

Goal and impact

Almost every entrepreneur files a sales tax (OB) return. This is also known as a VAT return. Some of the entrepreneurs who are required to file OB returns in the Netherlands are located abroad. These entrepreneurs can file their returns through the One-Stop-Shop scheme. This is an arrangement whereby an entrepreneur can file his OB return through one country for all European countries in which he is liable to file returns. Through this scheme, only turnover tax can be paid and not reclaimed. If entrepreneurs do not wish to participate in this scheme or reclaim VAT, they do so via the regular way (via the entrepreneur portal of the Tax and Customs Administration). The OB returns received through this regular way are called foreign returns.

Since 2022, the Tax and Customs Administration staff have been supported by the OBB algorithm in assessing sales tax returns of non-resident taxpayers. The algorithm detects possible discrepancies in the return based on relevant data available to the Tax Administration. For returns that require a manual check, staff receive a signal. These returns are then manually assessed and determined, if necessary after adjustment in consultation with the entrepreneur.

Considerations

The aim of the algorithm is to support the Tax Administration employee with advice on which returns require manual processing. This way, the available capacity of the employees is used in the best possible way. As a result, processors spend less time on returns that are completely correct and do not need to be checked. The sales tax return process has become more effective and efficient with the use of the algorithm. The process has also become more objective because there is a smaller chance of human error and because every return is treated the same.

Human intervention

Human intervention in the Tax Administration context implies that a competent and knowledgeable employee plays a substantial role in decision-making.

The operation of the algorithm always involves human intervention. The algorithm detects and selects for manual handling. It is the Tax Administration employee who makes the decision in manual handling.

Risk management

• Equality and non-discrimination

The algorithm is assessed in line with applicable non-discrimination principles for direct and indirect discrimination. Processing as little personal data as possible reduces the risk of direct discrimination. Employees involved in developing and managing the algorithms receive training on data protection and bias.

• Safeguards

The General Administrative Law Act (Awb) requires government actions to be transparent and lawful. The Tax and Customs Administration observes the general principles of good governance when applying and developing algorithms.

Conditions, a quality framework, have been drawn up by the Tax and Customs Administration for the development of algorithms. This contains rules and agreements that are followed during algorithm development. The conditions of the Audit Service Rijk (ADR) are leading in this respect. At regular intervals, the Tax and Customs Administration checks whether the algorithm still meets the quality requirements.

The algorithm uses data collected under various tax laws. As required by the AVG, no more data is used than necessary.

The algorithm and selection rules are evaluated annually. If necessary, the selection rules are adjusted in cooperation with the tax inspector to remain compliant with laws and regulations.

Legal basis

• General Administrative Law Act (Awb)
• General Act on national taxes (Awr)
• General provisions Citizen Service Number Act (Wabb)
• Turnover Tax Act 1968
• General data protection regulation (AVG)
• General Data Protection Regulation Implementation Act (uAVG)
• Archives Act 1995

Links to legal bases

• Algemene wet Bestuursrecht (Awb): https://wetten.overheid.nl/BWBR0005537/
• Algemene wet inzake rijksbelastingen (Awr): https://wetten.overheid.nl/BWBR0002320/
• Wet algemene bepalingen burgerservicenummer (Wabb): https://wetten.overheid.nl/BWBR0022428/
• Wet op de omzetbelasting 1968: https://wetten.overheid.nl/BWBR0002629/
• Algemene verordening gegevensbescherming (AVG): https://eur-lex.europa.eu/legal-content/NL/TXT/HTML/?uri=CELEX:32016R0679
• Uitvoeringswet algemene verordening gegevensbescherming (uAVG): https://wetten.overheid.nl/BWBR0040940
• Archiefwet 1995: https://wetten.overheid.nl/BWBR0007376/

Elaboration on impact assessments

• Privacy and AVG

The use of data should be assessed against the General Data Protection Regulation (AVG). Reviewing personal data reveals any privacy risks and allows appropriate measures to be taken.

The AVG prescribes that no more data should be used than necessary. This is called data minimisation. The Tax Administration regularly examines whether the data used are still necessary and can therefore be used. The algorithm does not use any special personal data.

Operations

Data

• Identifying data
• Turnover tax (OB) return and assessment data

Links to data sources

• Identificerende gegevens: Basisregistratie Personen (BRP)
• Aangiftegegevens en aanslaggegevens Omzetbelasting : Belastingdienst

Technical design

The algorithm consists of selection rules created by content experts based on laws, regulations and expertise.

The algorithm is not self-learning. This means that the algorithm does not develop itself during its use.

External provider

The algorithm was developed in-house at the Inland Revenue and is also maintained internally.