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.

Supervision declaration of private use of car (VPGA)

The 'Statement of Private Use (Van) Car (VPGA)' algorithm helps Tax Administration staff monitor correct and complete deduction and remittance of payroll taxes. The VPGA algorithm helps Tax Administration employees to respond to the potentially incorrect application of statements of private use (van) car.

Last change on 5th of February 2025, at 10:21 (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

algoritmeregister@belastingdienst.nl

Link to publication website

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

Responsible use

Goal and impact

The Tax Authority supervises the correct and complete declaration and remittance of payroll taxes. Payroll taxes are taxes and contributions that withholding agents (such as employer, pension fund or benefits agency) withhold from (wage tax and national insurance contributions) and pay on (employee insurance contributions and income-dependent healthcare insurance contributions) their employees' wages. The VPGA algorithm helps Tax Administration staff monitor proper compliance with legislation relevant to payroll taxes. A statement no private car use can be requested by an employee if the conditions are met.

The VPGA algorithm is designed to detect the wrongly omitted addition to the private use of a car when the statement no private use car is used. The algorithm combines different types of data to detect indications of situations in which there may be an incorrectly omitted addition to the private use of the car and thus an underpayment of payroll taxes.

The algorithm detects that there is no logical explanation for the fact that, for tax purposes, there is a period of additional private use of the car and a period of no additional use of the car due to the use of a statement of no private use. An addition period does mean that it is apparently not possible to provide evidence for the entire calendar year that no more than 500 kilometres were driven for private purposes. The addition for private car use will then apply for the entire calendar year, including for the period of statement holding.

The practitioner uses the results of the algorithm when supervising correct compliance with rules from the relevant legislation when using the statement no private use of car.

The processor contacts the withholding agent to request an explanation. If this contact shows that the addition was rightly omitted, the investigation is closed. If this investigation shows that there is no proof that no more than 500 kilometres were driven for private purposes on a calendar year basis, an additional assessment for payroll taxes will be imposed.

Considerations

  • Supervision of correct application of car use statement

If, for example, the statement no private use of car is applied incorrectly, no or too little payroll taxes are wrongly paid.

When a car is made available by the employer, it is taxed with a fixed amount as wages in kind, i.e. the additional taxable benefit for the private use of the car. The employer (withholding agent) may omit the additional taxable benefit if it can be proven that the car was driven for private purposes for no more than 500 kilometres on a calendar year.

The employer (withholding agent) can also omit the addition for private use of the car if he has received a copy of the car use statement from the employee.

The employee can request this decision from the Tax Administration. When handing over the statement to the employer, the burden of proof that no more than 500 kilometres for private use have been driven with the car(s) made available on a calendar year basis will be on the employee. Any additional taxes will thus fall on the employee.


  • Advantages of using algorithm

Monitoring private car use is important for the accuracy of the payroll tax return. The algorithm can support a Tax Administration employee in this. This makes the assessment more careful, efficient and uniform.

The algorithm contributes to the systematic and accurate checking of payroll tax returns on the subject of private car use at statement holders. By deploying an algorithm, declarations can be checked for accuracy more quickly.

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. It is the Tax Administration employee who contacts the declaration holder and makes the decision after a substantive review.

Risk management

  • 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.

The AVG prescribes that no more data should be used than necessary. This is called data minimisation. The Tax Authority regularly examines whether the data used are still necessary and can therefore be used.

The VPGA algorithm does not use any special personal data.

  • Equality and non-discrimination

The selection rules in the algorithm are tested against non-discrimination legislation. 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.

The General Administrative Law Act (Awb) requires government actions to be transparent and lawful. The Inland Revenue observes the general principles of good governance when applying and developing algorithms. The decision rules are reviewed and, if necessary, adjusted to remain compliant with laws and regulations, if warranted.

Legal basis

  • General State Tax Act
  • General Administrative Law Act
  • General Data Protection Regulation
  • General Data Protection Regulation (Implementation) Act
  • Payroll Tax Act 1964
  • Income Tax Act 2001
  • General provisions Citizen Service Number Act
  • Archives Act 1995


Links to legal bases

  • • Algemene wet inzake rijksbelastingen: https://wetten.overheid.nl/jci1.3:c:BWBR0002320&z=2023-01-01&g=2023-01-01
  • • Algemene wet bestuursrecht: 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: https://wetten.overheid.nl/jci1.3:c:BWBR0022428&z=2018-07-28&g=2018-07-28
  • • Wet op de Loonbelasting 1964: https://wetten.overheid.nl/jci1.3:c:BWBR0022428&z=2018-07-28&g=2018-07-28
  • • Wet Inkomstenbelasting 2001: https://wetten.overheid.nl/jci1.3:c:BWBR0022428&z=2018-07-28&g=2018-07-28
  • • Wet algemene bepalingen Burgerservicenummer: https://wetten.overheid.nl/jci1.3:c:BWBR0022428&z=2018-07-28&g=2018-07-28
  • • Archiefwet 1995: https://wetten.overheid.nl/jci1.3:c:BWBR0007376&z=2022-05-01&g=2022-05-01

Operations

Data

  • Identifying data
  • Identifying data
  • Identifying data
  • Policy data
  • Payroll tax return details
  • Income tax return details

Links to data sources

  • Identificerende gegevens: Basisregistratie Personen (BRP)
  • Identificerende gegevens : BVR (Belastingdienst)
  • Identificerende gegevens : vPGA
  • Polisgegevens: UWV
  • Aangiftegegevens Loonheffingen: Belastingdienst
  • Aangiftegegevens Inkomstenheffing: 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 it does not develop itself during its use.

External provider

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

Similar algorithm descriptions

  • Algorithm that helps assess whether a corporate tax return should be processed automatically or manually.

    Last change on 13th of November 2024, at 12:11 (CET) | Publication Standard 1.0
    Publication category
    Impactful algorithms
    Impact assessment
    Field not filled in.
    Status
    In use
  • The purpose of the algorithm is to automatically scan license plates for the purpose of parking enforcement

    Last change on 10th of December 2024, at 14:16 (CET) | Publication Standard 1.0
    Publication category
    Impactful algorithms
    Impact assessment
    DPIA
    Status
    In use
  • Predicting busy car parks is a European collaborative project aimed at developing a Mobility Analytics as a Service (MAaaS) toolkit. The aim is to efficiently manage, analyse and visualise large amounts of mobility data. Specifically, it involves predicting parking garage fill rates.

    Last change on 8th of January 2025, at 11:24 (CET) | Publication Standard 1.0
    Publication category
    Impactful algorithms
    Impact assessment
    Field not filled in.
    Status
    In use
  • This algorithm Supervision of correct qualification of labour relations (TKA) is part of the risk model Payroll Taxes. It helps Tax and Customs Administration staff supervise correct and complete withholding and remittance of payroll taxes. TKA helps Tax and Customs Administration staff respond to potentially incorrectly qualified employment relationships.

    Last change on 5th of November 2024, at 19:07 (CET) | Publication Standard 1.0
    Publication category
    Impactful algorithms
    Impact assessment
    Field not filled in.
    Status
    In use
  • This algorithm automatically makes a decision on an application to purchase parking credit for visitors. If the applicant receives informal care, then the respective applicant is entitled to a higher parking credit. If granted, the applicant can use the scheme immediately. If rejected, the applicant is given an explanation as to why.

    Last change on 11th of July 2024, at 12:04 (CET) | Publication Standard 1.0
    Publication category
    Impactful algorithms
    Impact assessment
    DPIA
    Status
    In use