Turnover tax Absenteeism Prevention and Attendance (OMV)

Dutch Tax and Customs Administration

The algorithms OBVP and OBVA support Inland Revenue employees in combating sales tax return omissions. OBVP focuses on preventing failure to file or late filing of returns. OBVA deals with entrepreneurs who have not filed a return when they were obliged to do so.

Last change on 8th of April 2025, at 9:12 (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/omzetbelasting-verzuimpreventie-en-verzuimaanpak-obv/

Responsible use

Goal and impact

• 'Sales tax absenteeism prevention (OBVP)' and 'Sales tax absenteeism approach (OBVA)'

Most businesses file sales tax (also known as VAT) returns. Sales tax returns are filed for a specific period of time, monthly, quarterly or annually. If the return is not filed on time, it is a declaration default. The OBVP algorithm uses a number of indicators to estimate the probability that the return will not be filed. In case of a high probability of default, a company is called by an employee. Attention is then drawn to the obligation to file a return and, if necessary, they are explained how to file a return.

The algorithm OBVA periodically makes an overview of the declaration absenteeism. It distinguishes between different groups. Starters who miss their first return are treated differently from entrepreneurs who have failed to file a return three times or more. Starters are called to explain how to file their returns. In case of repeated omissions, depending on the situation, the company will receive a letter with the intention of withdrawing the OB number. No new returns are then issued, which prevents future retrospective assessments and fines.

Considerations

Both algorithms help proactively address sales tax return defaults. With OBVP, companies can be called before the tax return deadline to prevent absenteeism. To do so, the algorithm looks at past patterns to predict which companies might not file their returns on time. OBVA makes it possible to target each group appropriately. Treatment signals are generated efficiently, effectively and consistently so that staff can focus on execution.

Human intervention

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

Both algorithms create treatment signals. The employee decides whether to contact the company because of such a signal. Decisions that may have an impact on the company are always made by the employee.

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 proper administration 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 regular intervals, 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 State Tax Act
• Citizen Service Number (General Provisions) Act
• Turnover Tax Act 1968
• Archives Act 1995
• Corporation Tax Act 1969
• General Administrative Law Act
• General Data Protection Regulation
• General Data Protection Regulation Implementation Act

Links to legal bases

• Algemene wet inzake rijksbelastingen: ttps://wetten.overheid.nl/BWBR0002320/
• 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/
• Wet op de Vennootschapsbelasting 1969: https://wetten.overheid.nl/BWBR0002672/
• 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/

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. By processing as little personal data as possible, the risk of direct discrimination is reduced.Employees involved in developing and managing the algorithms receive training on data protection and bias.

Operations

Data

• Identifying data
• Company data (including contact details)
• Turnover tax (OB) return and assessment data
• Supervision data (ongoing audits)
• Corporate income tax (VPB) declaration data
• Objection data
• Results of previous calls

Links to data sources

• Identificerende gegevens: Basisregistratie Personen (BRP)
• Bedrijfsgegevens (o.a. contactgegevens): Kamer van Koophandel / Handelsregister (NHR)
• Aangifte- en aanslaggegevens Omzetbelasting (OB): Belastingdienst
• Toezichtgegevens (lopende controles): Belastingdienst
• Aangiftegegevens vennootschapsbelasting (VPB): Belastingdienst
• Bezwaargegevens: Belastingdienst
• Resultaten eerdere belacties: Belastingdienst

Technical design

The algorithm OBVP is a statistical model trained with past absenteeism data. The algorithm is a learning algorithm: the algorithm has been trained by staff using past data to discover correlations. The algorithm is evaluated periodically and updated if necessary. For an update, the algorithm is re-trained.

The algorithm OBVA consists of business rules created by content experts based on laws, regulations and expertise. Both algorithms create signals that are handled by employees.

The algorithms are not self-learning. That means they do not evolve as they are used.

External provider

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