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.
Automated pre-selection when auditing legal entities
- Publication category
- Impactful algorithms
- Impact assessment
- Field not filled in.
- Status
- In use
General information
Theme
Begin date
Contact information
Link to publication website
Responsible use
Goal and impact
By using the algorithm, the Law on Audit of Legal Entities is carried out efficiently. The algorithm provides a proper and automated pre-selection of the legal entities to be analysed further manually.
The impact on citizens and legal entities is that the algorithm carries out an analysis of legal entities and associated natural persons. This includes criminal data.
What is the impact on citizens and legal entities? Do they notice anything from the monitoring?
Only the legal entities with an increased risk of abuse of the legal entity come to an employee as a file. Most of the analyses are removed again without human intervention. Removal of the analyses takes place automatically after the set cleaning deadlines.
Considerations
The use of the algorithm has the advantage of minimising the impact for citizens and legal entities, and employees only need to analyse a limited number of relevant files in more detail. The pre-selection by the algorithm is therefore necessary to implement the law in practice.
The consideration of relevant forms of fraud that the algorithm looks at is based on social developments and in contact with customers mentioned in the Wcr and Decree on the Control of Legal Persons (Bcr).
Human intervention
Within Justis, the TRACK department is responsible for implementing the Control of Legal Entities Act. Employees of department TRACK, in consultation with the recipients of the risk reports, determine which types of fraud are relevant in the risk analysis of legal persons. This is input for the deployment of the algorithm.
The TRACK department has built up expertise on the specific types of fraud, such as keeping track of current knowledge and experience in a fraud area, and the fraud profile associated with the fraud area. The algorithm, which implements the automated part of the profile, is clear to the employee and the employee has tested that it leads to the desired investigation-worthy files.
Risk management
The pre-selection done by the algorithm is continuously monitored, as the files are the starting point for further analysis by the employee. In addition, TRACK department receives feedback from the customers who have received a risk notification.
This input is used to periodically adjust, improve and extend the algorithm.
Legal basis
The algorithm is used for the implementation of the Control of Legal Entities Act when making the 'Risk Notification' product. This Act and the accompanying Explanatory Memorandum (House of Representatives, session year 2008-2009, 31 948, no.3) describe the manner in which supervision is to be carried out. The risk notifications are made for the customers in the Netherlands stipulated in the Act.
Links to legal bases
Operations
Data
The algorithm uses data from a number of sources established by law: the Commercial Register (HR), the Basic Registration of Persons (BRP), the Judicial Documentation System (JDS) and the Central Insolvency Register (CIR).
Technical design
The algorithm uses two techniques:
- Simple decision tree, which uses data from the four sources.
- Linear regression, which maximises the distinction between relevant and irrelevant analyses of legal entities based on experience data.
External provider
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