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.
IPA risk model
- Publication category
- Impactful algorithms
- Impact assessment
- ...
- Status
- In use
General information
Theme
Begin date
Contact information
Responsible use
Goal and impact
Inspectors use the results of the risk model, along with other information, to determine which asbestos notifications pose the greatest risk and are therefore prioritised for inspection.
Considerations
The advantage of this risk model is that the inspector goes to places with the highest risks. This makes the deployment of inspectors more efficient. It also has an advantage for companies carrying out low-risk asbestos remediation. Their chances of facing an inspection are reduced.
Human intervention
The inspector assesses the results of the risk model. This allows him to choose the sites with the highest risk score.
Risk management
In principle, the Labour Inspectorate inspects every certified asbestos remediation company at least once every three years.
Inspections with IPA make up part of the total number of inspections carried out. Part of the inspections take place reactively. This means inspecting in response to reports from citizens and other supervisors. In addition, part of the remediation operations are randomly selected by the inspector. The results of these random inspections are in turn used to improve the reliability of IPA.
The risk model uses business information, including from the Chamber of Commerce. Therefore, there are measures for the security, access and quality of IPA. IPA is monitored frequently and assessed for these components every year.
Legal basis
The occupational health and safety legislation contains specific rules for reporting asbestos decontamination. These rules can be found in the Working Conditions Decree, chapter 4, section 5 'Additional regulations on asbestos'.
Links to legal bases
Impact assessment
Operations
Data
Data from notifications from the National Asbestos Tracking System, historical asbestos inspection data, data from the Chamber of Commerce Register and data from UWV Employment Records (pseudonymised: no personal names and a pseudo-BSN).
Links to data sources
- LAVS: https://www.asbestvolgsysteem.nl/lavs-web/
- Wat is het LAVS?: https://iplo.nl/thema/asbest/lavs/wat-is-lavs/
Technical design
The risk model uses a supervised machine learning model (random forest classifier), which analyses patterns in various data sources to predict the probability of incorrectly performed asbestos removal. This is done based on a dataset of past inspections and reports. In some of these inspections, the inspector found a violation. This information is used in training the model along with other data sources. The model calculates a risk score for each reported asbestos removal.
External provider
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