Selection book examinations for dual students of the Dutch professional body of accountants

Dutch Tax and Customs Administration

This page provides information about the algorithm that selects book examinations for dual students. This algorithm selects from the entrepreneurial population of SME entities that meet certain criteria.

Last change on 4th of September 2025, at 18:40 (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

01-2019

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/selectie-boekenonderzoeken-voor-duaal-studenten-van-de-nederlandse-beroepsorganisatie-van-accountants-nba/

Responsible use

Goal and impact

The primary purpose of this work process is for dual students to gain experience in book audits. These book examinations must meet NBA criteria. In particular, these criteria are intended to impart a certain level of complexity to the book audits. This complexity consists of tax resources, the tax importance, the typology of the company. In addition, a company must not have had an audit in the past 7 years.

The reason for using an algorithm in SAS (Statitical Aanalysis System) (instead of manual) are:

• Efficiency: Large data sets are processed for population delineation;
• Accuracy: The algorithm avoids human error in selecting units.
• Reproducibility: The selection can be repeated exactly with the same settings.
• Transparency: The method used is clearly documented and verifiable.

This algorithm selects appropriate items from the population of SMEs. A random sample is taken from these posts. From this sample, depending on the location of the dual student, year of study and desired typology, the posts are distributed among the dual students. Some of these entities are given a book audit. The audit assignment for all entities is the same.

The purpose of the algorithm is to select suitable entities for a book examination in accordance with the requirements of the NBA (Dutch professional association of accountants).

Considerations

By using the algorithm, appropriate entities can be efficiently selected that meet the NBA's criteria, which can be passed on to the dual students for consideration.

Human intervention

Human intervention in the Inland Revenue context involves a competent and knowledgeable employee playing a substantial role in decision-making.

The algorithm makes a selection of entities where dual students can carry out book audits.

When the audit assignments of the book examinations are entered into the system, an employee still performs a variety of manual checks. The clerk decides whether a book examination will follow.

The audit and its outcome (an assessment) are carried out by an employee.

Risk management

• Privacy and AVG

The use of data should be 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

No special personal data are used in the algorithm. These are not relevant for selecting posts suitable for dual students.

• 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 is used than necessary.

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/

Operations

Data

1. Personal and entity data, branch and tax liability companies.
2. VPB tax return data for determining the VPB tax interest
3. Turnover data for determining the fiscal interest OB
4. Wage data for determining tax interest LH and number of employees.
5. Book audits initiated after 2018

Links to data sources

• Personal and entity data, industry and tax liability companies.: BvR (Belastingdienst)
• VPB tax return data for determining VPB tax interest: ABS (Belastingdienst)
• Turnover data for determining OB tax interest: OOB (Belastingdienst)
• Wage data for determining tax interest LH and number of employees.: FLG (Belastingdienst)
• Book examinations instituted after 2018: IVAB(Belastingdienst)

Technical design

The algorithm consists of selection rules drawn up by content experts from both the Inland Revenue and NBA based on a number of specific criteria. The outcome of the algorithm is the determination of the entrepreneurial SME population that lend themselves to training the dual students on auditing skills. Entities are randomly selected from this population.

The algorithm is not self-learning. This means that the algorithm does not develop itself during its use.

External provider

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