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.

Risk selection of posts with licence plate data for the purpose of ANPR action

This page contains information about the algorithm 'Risk selection of posts with license plate data for the ANPR action'. This algorithm selects license plates of vehicles that the Tax and Customs Administration wants to recognise in actions with automatic license plate recognition (ANPR).

Last change on 4th of September 2025, at 18:41 (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

2004

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/risicoselectie-van-posten-met-kentekengegevens-ten-behoeve-van-de-anpr-actie/

Responsible use

Goal and impact

During traffic checks, cars whose owners have collection debts are taken off the road. The taxpayer is given the opportunity to pay his arrears. If necessary, the car can be impounded.

The license plates of passing cars are scanned by the ANPR camera. In the process, the algorithm selects the license plates of the cars. If the number plate appears in the file, the bailiff receives a notification "hit" and the number plate is passed on to the motorbike officer who pulls the car over at the next car park.

The bailiff then discusses the outstanding debts with the driver.

Considerations

Because of the large numbers of cars and the speed at which they drive by, it is impossible to assess the license plates without technical support. The algorithm supports in assessing the license plates. As a result, the assessment is more careful and efficient.

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. The algorithm detects and selects. The algorithm does not contain 24/7 "real-time " information. Therefore, the employee looks in the collection system on the spot for the latest up-to-date data. These may differ given the moment (time ) of the selection of the hit lists. It is the Inland Revenue employee who discusses the outstanding debts with the driver and makes the decision.


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 Administration regularly examines whether the data used are still necessary and may therefore be used.

  • Use of special personal data

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.

  • Safeguards

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

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

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. Recovery Act 1990
  6. Payroll Tax Act 1964:
  7. Income Tax Act 2001:
  8. Corporation Tax Act 1969:
  9. Turnover Tax Act 1968:
  10. General Provisions Citizens' Service Number Act:
  11. Archives Act 1995:
  12. Policy rule CBP guidelines ANPR

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/
  • Recovery Act 1990: https://wetten.overheid.nl/BWBR0004770/
  • 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/
  • CBP policy rule guidelines ANPR: https://wetten.overheid.nl/BWBR0033241/

Operations

Data

  1. Vehicle status data (export, scrapped, stolen, suspended, etc.)
  2. Vehicles with obligation signals VPS1 (cat catchers) and VPS2 (tax defaulters)
  3. Company stock vehicles in the company stock of RDW authorised dealers or importers
  4. Vehicles registered in the name of individuals with outstanding and recoverable tax debts

Links to data sources

  • Vehicle status data (export, scrapped, stolen, suspended, etc.): Copy Basisregistratie Voertuigen (CBV)
  • Vehicles with obligation signals VPS1 (cat catchers) and VPS2 (tax defaulters): Copy Basisregistratie Voertuigen (CBV)
  • Commercial vehicles in the stock of RDW authorised dealers or importers: Copy Basisregistratie Voertuigen (CBV)
  • Vehicles in the name of persons with outstanding and recoverable tax debt: Automatic Numberplate Recognition (ANR)

Technical design

The algorithm consists of selection rules that content experts have taken verbatim from laws and regulations.

The algorithm is not self-learning. That means it does not evolve as it is used.

External provider

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

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