Payroll tax risk model - Monitoring correct qualification of employment relationships (TKA)

Dutch Tax and Customs Administration

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

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/risicomodel-loonheffingen-toezicht-op-juiste-kwalificatie-arbeidsrelaties-tka/

Responsible use

Goal and impact

The Tax Authority monitors the correct and complete withholding and remittance of payroll taxes. Payroll taxes are taxes and contributions that companies withhold as employers (wage tax and national insurance contributions) and pay on their employees' wages (employee insurance contributions and income-dependent health insurance contributions).

The Payroll Tax Risk Model helps Tax and Customs Administration staff monitor proper compliance with legislation relevant to payroll taxes. The TKA algorithm is designed to detect the use of additional workers who are not employees.

Considerations

When there is false self-employment, for example, no payroll taxes are wrongly paid. For example, false self-employment may occur when a company (as a principal) uses hired workers who actually work for this company in a dependent and/or subordinate relationship, which actually constitutes employment (working as an employee).

Sham self-employment has the following adverse consequences, among others:

• The sham self-employed person is less well protected than if this person had been an employee.
• The pseudo self-employed person can make unjustified use of corporate tax schemes.
• The client pays too little payroll taxes.
• Competition with companies (which do use salaried staff) is distorted.

For these reasons, the Tax Authority intensifies supervision of the correct qualification of employment relationships.

The algorithm TKA combines different types of data to detect indications of situations where there is third-party hiring. Based on these indications, clients can be contacted for additional questions to determine whether an investigation should be launched into the qualification of labour relations.

This algorithm allows the Tax and Customs Administration to use its limited supervisory capacity more efficiently. The use of the algorithm increases the chances of approaching the right client for an interview or investigation. The use of the algorithm will allow supervision to be carried out more efficiently and effectively than when detection and selection were done manually.

Through the results from the algorithm, the Tax Administration can also act proactively through, for example, additional education.

Human intervention

The initiation of supervisory action (calls, question letters, audit visit, etc.) to assess the risk of underpayment of payroll taxes is always done by a Tax Administration employee.

Risk management

For the development of algorithms, the Tax Administration has drawn up conditions, a quality framework. This contains rules and agreements that are followed when developing the algorithm. The conditions of the Audit Service Rijk (ADR) are leading in this respect. When changes are made to one of the algorithms, the Tax and Customs Administration checks whether the algorithms still meet the quality requirements.

The use of the relevant data is tested against the relevant legislation. The AVG prescribes that we should not use more data than necessary. This is called data minimisation. The Tax Authority regularly checks whether the data used is still necessary and therefore may be used. If this is not the case, the algorithm is adjusted and this data is also no longer used.

Legal basis

The collection and use of the data described above is regulated by the:

• 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
• Corporation Tax Act 1969
• Turnover Tax Act 1968
• General Provisions (Citizen Service Number) Act
• Archives Act 1995

Links to legal bases

• Algemene wet inzake rijksbelastingen: https://wetten.overheid.nl/BWBR0002320/
• 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/BWBR0040940/
• Wet op de Loonbelasting 1964: https://wetten.overheid.nl/BWBR0002471/
• Wet Inkomstenbelasting 2001: https://wetten.overheid.nl/BWBR0011353/
• Wet op de Vennootschapsbelasting 1969: https://wetten.overheid.nl/BWBR0002672/
• Wet op de Omzetbelasting 1968: https://wetten.overheid.nl/BWBR0002629/
• Wet algemene bepalingen Burgerservicenummer: https://wetten.overheid.nl/BWBR0022428/
• Archiefwet 1995: https://wetten.overheid.nl/BWBR0007376/

Operations

Data

• Identifying data (including BSN)
• Identifying company data (including tax number)
• Payroll tax return details
• Turnover tax return details (tax number and turnover)
• Corporation tax return details (tax number and various tax return and assessment details)
• Income tax return details (tax number and various tax return and assessment details)

Links to data sources

• Identificerende gegevens (o.a. BSN): Basisregistratie Personen (BRP)
• Identificerende bedrijfsgegevens (o.a. fiscaalnummer): Kamer van Koophandel
• Aangiftegegevens Loonheffingen: Belastingdienst
• Aangiftegegevens Omzetbelasting (fiscaalnummer en omzet): Belastingdienst
• Aangiftegegevens Vennootschapsbelasting (fiscaalnummer en diverse aangifte-, aanslaggegevens): Belastingdienst
• Aangiftegegevens Inkomstenbelasting (fiscaalnummer en diverse aangifte-, aanslaggegevens): Belastingdienst

Technical design

The algorithm consists of decision rules created in collaboration with content experts and lawyers.

The algorithm is not self-learning. This means that it does not evolve while being used.

External provider

The algorithm was developed by the Tax Administration and is also maintained internally. The decision rules are reviewed periodically and adjusted if necessary to remain compliant with laws and regulations.