Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Signal model OB Issue OB number (ABN)

This page contains information about the algorithm 'OB Issue OB number'. This algorithm supports the Tax Administration in determining which registration requests need to be assessed manually before the OB number can be issued.

Last change on 8th of April 2025, at 9:14 (CET) | Publication Standard 1.0
Publication category
Impactful algorithms
Impact assessment
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Status
In use

General information

Theme

Public finance

Begin date

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Contact information

algoritmeregister@belastingdienst.nl

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-ob-afgifte-ob-nummer-abn/

Responsible use

Goal and impact

An entrepreneur starts a new business by registering it in the Commercial Register of the Chamber of Commerce (CoC). The CoC provides the details of the new company to the Tax Administration. The Inland Revenue assesses whether the company is liable to pay sales tax (OB). If it is, an OB number is issued to the entrepreneur. This number is needed to file a tax return.

The algorithm selects which registration requests need to be assessed manually. An employee assesses whether the OB number can be issued. If anything is still unclear, the employee contacts the entrepreneur. If the conditions of entrepreneurship for OB are not met, no OB number is issued.

Considerations

Because the algorithm is used, the selection for the manual assessment always takes place in the same way. This ensures an efficient and consistent method of selection. This allows the employee to fully focus on the substantive handling.

Human intervention

Human intervention in the Inland Revenue context implies that a competent and knowledgeable employee plays a substantial role in the decision-making process.

The algorithm determines whether a business owner is given an OB number immediately or whether an employee has to assess it manually. If all data is correct and complete and there are no questions about tax liability, the OB number is issued automatically. If something is not clear, the registration is selected by the algorithm for manual assessment. In that case, the employee decides after investigation whether the OB number may be issued. This eliminates substantial human intervention in the decision-making process.

Risk management

The General Administrative Law Act (Awb) requires the government's 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 National Audit Authority are leading in this respect. At set moments, 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 business rules are reviewed periodically and adjusted if necessary to remain compliant with laws and regulations.

Legal basis

  • General Act on national taxes (Awr)
  • General Administrative Law Act (Awb)
  • General data protection regulation (AVG)
  • General Data Protection Regulation (Implementation) Act (UAVG)
  • General provisions Citizen Service Number Act (Wabb)
  • Turnover Tax Act 1968
  • Archives Act 1995
  • Regulation (EU) No 904/2010 on administrative cooperation and combating fraud in the field of value added tax.

Links to legal bases

  • Algemene wet inzake rijksbelastingen (Awr): https://wetten.overheid.nl/BWBR0002320/
  • Algemene wet bestuursrecht (Awb): https://wetten.overheid.nl/BWBR0005537/
  • Algemene verordening gegevensbescherming: https://eur-lex.europa.eu/legal-content/NL/TXT/HTML/?uri=CELEX:32016R0679
  • Uitvoeringswet algemene verordening gegevensbescherming (UAVG): https://wetten.overheid.nl/BWBR0040940/
  • Wet algemene bepalingen Burgerservicenummer: https://wetten.overheid.nl/BWBR0022428/
  • Wet op de omzetbelasting 1968 : https://wetten.overheid.nl/BWBR0002629/
  • Archiefwet 1995: https://wetten.overheid.nl/BWBR0007376/
  • Verordening (EU) nr. 904/2010 betreffende de administratieve samenwerking en de bestrijding van fraude op het gebied van de belasting over de toegevoegde waarde.: https://eur-lex.europa.eu/legal-content/NL/TXT/HTML/?uri=CELEX:02010R0904-20240101

Elaboration on impact assessments

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.

  • 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.

Operations

Data

  • Identifying data entrepreneur
  • Company identification data
  • Company details
  • Account details

Links to data sources

  • Identificerende gegevens ondernemer: Basisregistratie Personen (BRP)
  • Identificerende gegevens onderneming: Beheer van Relaties (BvR)
  • Bedrijfsgegevens: KvK (Kamer van Koophandel)
  • Rekeninggegevens: Belastingdienst en Banken

Technical design

The algorithm uses business rules created in cooperation with content experts. Based on these business rules, the algorithm selects which registration requests should be manually reviewed by a Tax Administration employee.

The algorithm is not self-learning. This means that it does not evolve during its use.

External provider

The algorithm was developed by Tax Administration staff and is maintained internally.

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