Natural Language Processing
Forecasting
Knowledge management
The Department of Work and Social Economy (WSE) deals with large volumes of data across employment, social economy and inspection services. As the amount and complexity of this data grew, WSE saw an opportunity to use data science and AI to support its teams and turn data into practical insights.
The Department of Work and Social Economy (WSE) monitors the proper use of employment support measures in Flanders—like service vouchers and training incentives. A key part of that mission is inspecting for misuse and fraud.
Rather than seeing data as a challenge, WSE saw an opportunity. By analysing existing data sources more intelligently, they could predict where fraud was likely to happen—and prioritise inspections accordingly.
1
Smarter fraud detection with data-driven inspection triggers.
2
Higher inspection efficiency by focusing on high-risk cases.
3
Scalable internal improvements with automated analysis tools.
Team Vectr.Consulting worked closely with WSE’s internal data team to develop fraud detection models tailored to their context. These AI-driven tools help inspectors:
This lets inspectors shift their focus to the cases that matter most—resulting in faster follow-up and more effective enforcement.
WSE is now exploring AI-powered risk scoring, combining past insights with new data to proactively highlight potential fraud. It’s a move from random checks to smart, predictive inspection—and a major leap forward in public service efficiency.
Beyond fraud detection, WSE is applying the same smart approach to other areas. For example:
These tools don’t just help inspectors—they make daily operations smoother and smarter for everyone.
.jpg)
%20copy.webp)
