Professor Bart Baesens is a professor of Big Data & Analytics at KU Leuven (Belgium), and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on big data & analytics, credit risk modeling, fraud detection, and marketing analytics. He co-authored more than 250 scientific papers and 10 books some of which have been translated into Chinese, Japanese, Korean, Russian and Kazakh, and sold more than 40,000 copies of these books world-wide. Bart received the OR Society’s Goodeve medal for best JORS paper in 2016 and the EURO 2014 and EURO 2017 award for best EJOR paper. His research is summarized at www.dataminingapps.com. He also regularly tutors, advises and provides consulting support to international firms with respect to their analytics and credit risk management strategy. Bart is listed in the top 2% of Stanford University’s new Database of Top Scientists in the World. He was also named one of the World’s top educators in Data Science by CDO magazine in 2021 and has educated tens of thousands of data scientists across the globe in the fields of credit risk, fraud, marketing, ICT, HR and others. Bart also has his own ON-LINE learning BlueCourses platform which features courses on machine learning, credit risk, fraud, marketing, text analytics, deep learning, web scraping etc.
Sovereign credit risk modeling using machine learning: a novel approach to sovereign credit risk incorporating private sector and sustainability risks
The authors investigate the effect of spillover effects from private sector risks on sovereign debt risk and the impact of rising sustainability risks on sovereign credit risk using the XGBoost classification algorithm and model interpretability…