Predict risk of Long Term Unemployment

One in six unemployed people in Switzerland are unemployed for a period longer than 12 months and are considered long term unemployed. The longer a person has been without a job, the less placeable the person is on the job market and the higher the costs are. By knowing early who falls in which category (e.g. long term unemployment), targeted measures can be taken to support the corresponding people better in their search for a job.

Labor ministries have a wealth of historic data on unemployment, the people affected by it, and the efforts by the people to get out of it and find a job. The knowledge contained within that dataset can be harnessed using Machine Learning. By building a ML model using this training data, unemployment counselors can apply it to assess and classify the risk for long term unemployment of freshly unemployed people. This knowledge helps the counselors to decide on the right measures to effectively support unemployed people.

Modulos AutoML makes the creation of effective ML models easy and accessible to domain experts. The platform and the ML models can furthermore also be deployed on-premise, making them well suited for the analysis of potentially sensitive data.