Baesens, Bart

Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research

Lessmann, S., Baesens, B., Seow, H.-V., & Thomas, L. C. (2015) · European Journal of Operational Research

Financial Distress and Bankruptcy PredictionImbalanced Data Classification Techniques

Cited by 1,284

Benchmarking state-of-the-art classification algorithms for credit scoring

Baesens, B., Van Gestel, T., Viaene, S., Stepanova, M., Suykens, J., & Vanthienen, J. (2003) · Journal of the Operational Research Society

Financial Distress and Bankruptcy PredictionImbalanced Data Classification Techniques

Cited by 904

New insights into churn prediction in the telecommunication sector: a profit driven data mining approach

Verbeke, W., Dejaeger, K., Martens, D., Hur, J., & Baesens, B. (2012) · European Journal of Operational Research

Customer churn and segmentationCustomer Service Quality and Loyalty

Cited by 462

Comprehensible credit scoring models using rule extraction from support vector machines

Martens, D., Baesens, B., Van Gestel, T., & Vanthienen, J. (2007) · European Journal of Operational Research

Explainable Artificial Intelligence (XAI)Data Mining Algorithms and Applications

Cited by 448

An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models

Huysmans, J., Dejaeger, K., Mues, C., Vanthienen, J., & Baesens, B. (2011) · Decision Support Systems

Explainable Artificial Intelligence (XAI)Data Mining Algorithms and Applications

Cited by 425

Data mining techniques for software effort estimation: a comparative study

Dejaeger, K., Verbeke, W., Martens, D., & Baesens, B. (2012) · IEEE Transactions on Software Engineering

Software Engineering Techniques and PracticesSoftware Engineering Research

Cited by 224

Development and application of consumer credit scoring models using profit-based classification measures

Verbraken, T., Bravo, C., Weber, R., & Baesens, B. (2014) · European Journal of Operational Research

Financial Distress and Bankruptcy PredictionImbalanced Data Classification Techniques

Cited by 179

Data engineering for fraud detection

Baesens, B., Höppner, S., & Verdonck, T. (2021) · Decision Support Systems

Imbalanced Data Classification TechniquesPrivacy-Preserving Technologies in Data

Cited by 170

Gotcha! Network-based fraud detection for social security fraud

Van Vlasselaer, V., Eliassi-Rad, T., Akoglu, L., Snoeck, M., & Baesens, B. (2017) · Management Science

Complex Network Analysis TechniquesBenford’s Law and Fraud Detection

Cited by 164

Social network analysis for customer churn prediction

Verbeke, W., Martens, D., & Baesens, B. (2014) · Applied Soft Computing

Customer churn and segmentationCustomer Service Quality and Loyalty

Cited by 164

Predicting tax avoidance by means of social network analytics

Lismont, J., Cardinaels, E., Bruynseels, L., De Groote, S., Baesens, B., Lemahieu, W., & Vanthienen, J. (2018) · Decision Support Systems

Corporate Taxation and AvoidanceTaxation and Legal Issues

Cited by 51

Profit‐Driven Business Analytics: A Practitioner's Guide to Transforming Big Data into Added Value

Verbeke, W., Baesens, B., & Bravo, C. (2017) · Wiley eBooks

Big Data and Business IntelligenceSupply Chain and Inventory Management

Cited by 16