Public Procurement AI: Detecting Corruption Patterns with Explainable Machine Learning

Key Points

• The research aims to identify patterns of corruption in public procurement using explainable machine learning techniques.
• Utilized machine learning algorithms to analyze procurement data.
• Implemented explainable AI to interpret the model's decisions.
• Assessed the effectiveness of the system in detecting corruption patterns.
• Successfully identified key corruption patterns with high accuracy.
• Demonstrated that explainable AI methods improved stakeholder trust in predictions.
• Highlighted significant cases of potential corruption for further investigation.