Foundations and Associations (HSTV)

Dutch Tax and Customs Administration

This page contains information about the algorithm 'Signal Model Tax Obligation Stivers'. This algorithm helps employees of the Inland Revenue monitor the presence of tax liability and return obligation of foundations and associations (Stivers).

Last change on 19th of December 2025, at 12:29 (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

10-2025

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-belastingplicht-stivers/

Responsible use

Goal and impact

The signal model supports the monitoring process for Foundations and Associations (Stivers). Stivers are institutions whose legal form is a foundation or association, which receive a status from the Tax Authorities as Taxable, Tax Exempt or Taxpayer Obligatory for Corporation Tax, Turnover Tax and/or Payroll Tax. The population of Stivers consists of ca 202,220 organisations (2024). Annually, there is an increase of about 8,000 Stivers and about 16,000 Stivers are dissolved.

The Inland Revenue monitors the presence of tax liability and declaration obligation in individual Stivers. A Stiver can conduct its own review of this via the Tax and Customs Administration's website, and can also submit a request to the Tax and Customs Administration for a further (re)assessment of the tax and declaration obligation. In addition, newly registered Stivers are assessed on these duties and a reassessment of existing Stivers takes place periodically.

Considerations

This algorithm helps the Tax Administration deploy employees (handlers) in a more targeted, and therefore more efficient, manner.

Human intervention

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

Human intervention is always involved in the operation of the algorithm. It is the Tax Administration employee/handler who, after further investigation, makes the decision whether a Stiver is liable to tax.

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 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.

The evaluation is carried out annually by the service unit that carries out the supervision, Belastingdienst-MKB, in cooperation with the service unit that developed the signalling model, Corporate Service Data Foundations and Analytics.

Legal basis

1. General State Tax Act:
2. General Administrative Law Act:
3. General Data Protection Regulation:
4. General Data Protection Regulation Implementation Act:
5. Payroll Tax Act 1964:
6. Income Tax Act 2001:
7. Corporation Tax Act 1969:
8. Turnover Tax Act 1968:
9. General Provisions Citizens' Service Number Act:
10. Archives Act 1995:

Links to legal bases

• General State Tax Act:: https://wetten.overheid.nl/BWBR0002320/
• General Administrative Law Act:: https://wetten.overheid.nl/BWBR0005537/
• General Data Protection Regulation:: https://eur-lex.europa.eu/legal-content/NL/TXT/HTML/?uri=CELEX:32016R0679
• General Data Protection Regulation Implementation Act: https://wetten.overheid.nl/BWBR0040940/
• Payroll Tax Act 1964:: https://wetten.overheid.nl/BWBR0002471/
• Income Tax Act 2001:: https://wetten.overheid.nl/BWBR0011353/
• Corporation Tax Act 1969:: https://wetten.overheid.nl/BWBR0002672/
• Turnover Tax Act 1968:: https://wetten.overheid.nl/BWBR0002629/
• General provisions Citizen Service Number Act:: https://wetten.overheid.nl/BWBR0022428/
• Archives Act 1995:: https://wetten.overheid.nl/BWBR0007376/

Elaboration on impact assessments

• Privacy and AVG

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

Among other things, the AVG prescribes that no more data should be used than necessary. This is called data minimisation. The Tax and Customs Administration regularly examines whether the data used are still necessary for the purpose and whether there is a basis for processing the data.

• Use of special personal data

Special personal data in the AVG include race, political views and religion.

The algorithm does not use special personal data.

• 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

1. Personal data of directors (relations between natural persons, tax liability)
2. Company data (relations and tax liability, tax number)
3. Financial products
4. Wage tax return details (LH)
5. Corporate income tax (VPB) return details
6. Turnover tax (OB) return details
7. Motor vehicle tax (MRB) collection details
8. ANBI status
9. Property details
10. Vehicle data

Links to data sources

• Personal data directors (relations between natural persons, tax liability): Basisregistratie Personen (BRP)
• Company data (relations and tax liability, tax number): Kamer van Koophandel
• Financial products: Banken
• Payroll tax (LH) declaration details: Belastingdienst
• Corporate income tax (VPB) return details: Belastingdienst
• Turnover tax (OB) declaration details: Belastingdienst
• Motor vehicle tax (MRB) collection details: Belastingdienst
• ANBI status: Belastingdienst
• Property details: Kadaster en Landelijke voorziening WOZ
• Vehicle data: Rijksdienst voor Wegverkeer (RDW)

Technical design

The algorithm consists of selection rules drawn up by content experts based on laws, regulations and expertise. The algorithm scores Stivers according to a traffic light principle with increasing probability of tax liability: green > orange > red.

Based on treatment capacity, an x number of Stivers scored green, orange and red are then selected for treatment by a practitioner.

In addition to the previously mentioned score for each Stiver, the algorithm provides both the requested samples for the green, orange and red categories as well as the information needed for the practitioner to assess whether the score is correct.

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

External provider

The algorithm was developed by the Inland Revenue and is also maintained internally.