Countering customs fraud and corruption with machine learning
This project addresses customs corruption in low- and middle-income countries by testing a machine learning algorithm to predict import tax evasion, significantly improving accuracy and reducing inspection delays. A randomised controlled trial measures the algorithm's impact and potential to enhance state capacity and tax revenue collection in Paraguay.
