Cristián Bravo Roman


Associate Professor
Canada Research Chair in Banking and Insurance Analytics
Ph.D. University of Chile, 2013
Office: WSC 209
Phone: ext. 87665
Email: cbravoro@uwo.ca


Research Areas

    Credit Scoring
    Artificial Intelligence
    Profit-driven Analytics

Graduate Students Supervision

    Matthew Stevenson (U. of Southampton, UK)
    Kameswara Korangi (U. of Southampton, UK)
    David Barrera-Ferro (U. of Southampton, UK)

 Research Funding Source(s)

    Tier 2 Canada Research Chair in Banking and Insurance Analytics, NSERC 

 Publications

 Journal papers

Stevenson, M. (*) and Bravo, C. (2019) Advanced turbidity prediction for operational water supply planning, Decision Support Systems 119 (5): 72-84.

Óskarsdóttir, M. (*), Bravo, C., Verbeke, W., Sarraute, C., Baesens, B., Vanthienen, J. (2019). The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics. Applied Soft Computing 74: 26 – 39. (2nd most downloaded paper in journal) Garrido, F. (*), Verbeke, W., and Bravo, C. (corr). (2018). A Robust Profit Measure for Binary Classification Model Evaluation. Expert Systems with Applications 92:  154-160.

Maldonado, S., Bravo, C., López, J., Pérez, J. (2017) Integrated framework for profit-based feature selection and SVM classification in credit scoring Decision Support Systems 104: 113 – 121.

Óskarsdóttir, M. (*), Bravo, C., Verbeke, W., Sarraute, C., Baesens, B., Vanthienen, J. (2017) Social Network Analytics for Churn Prediction in Telco: Model Building, Evaluation and Network Architecture. Expert Systems with Applications 85 (1):  204-220.

Maldonado, S., Pérez, J., Bravo, C. (2017). Cost-based feature selection for Support Vector Machines - An application in credit scoring. European Journal of Operational Research 261:  2.  656–665.

Bravo, C. and Maldonado, S. (2015). Fieller Stability Measure: a novel model-dependent backtesting approach. Journal of the Operational Research Society 66 (11): 1895 - 1905.

Chong, M. (*), Bravo C., and Davison, M. (2015). How Much Effort Should Be Spent to Detect Fraudulent Applications When Engaged in Classifier-Based Lending? Intelligent Data Analysis 19 (S1): S87 – S101.

Van Vlasselaer, V., Bravo, C. (corr), Caelen, O., Eliassi-Rad, T., Akoglu, L., Snoeck, M., and Baesens, B. (2015). APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions. Decision Support Systems 75:  38-48. (Top 5 cited paper in journal since 2015) Bravo, C., Thomas, L. C., and Weber, R. (2015). Improving credit scoring by differentiating defaulter behaviour. Journal of the Operational Research Society 66(5): 771-778.

Verbraken, T., Bravo, C., Weber, R. and Baesens, B. (2014) Development and application of consumer credit scoring models using profit-based classification measures. European Journal of Operational Research 238(2): 505 – 513.

Bravo, C., Maldonado, S. and Weber, R. (2013). Granting and Managing Loans for Micro-Entrepreneurs: New Developments and Practical Experiences”. European Journal of Operational Research 227(2): 358 – 366.

Brown, D., Famili, F., Paass, G., Smith-Miles, K., Thomas, L. C., Weber, R., Baeza-Yates, R., Bravo, C., L'Huillier, G. and Maldonado, S. (2011). Future Trends in Business Analytics and Optimization”. Intelligent Data Analysis 15: 6. 1001-1017.

Bravo, C., Lobato, J.L., L’Huillier, G. and Weber, R. (2010) Probability Estimation for Multiclass Problems Combining SVM’s and Neural Networks. Neural Networks World 20(4): 475-489.

 Books

Verbeke, W., Baesens, B., Bravo C. (2017) Profit Driven Analytics. Wiley. NY, USA. 

 Book Chapters

Biron, M. (*) and Bravo, C. (2014). On the Discriminative Power of Credit Scoring Systems Trained on Independent Samples. In: Data Analysis, Machine Learning and Knowledge Discovery. Eds: Myra Spiliopoulou, Lars Schmidt-Thieme, and Ruth Janning.  247-254.

Bravo, C. and Weber, R. (2011, November). Semi-Supervised Constrained Clustering with Cluster Outlier Filtering. Proceedings of the XVI Iberoamerican Congress on Pattern Recognition, CIARP 2011. Lectures Notes in Computer Science 7042. 347-354.

Bravo, C., Figueroa, N., & Weber, R. (2010, July). Modeling pricing strategies using game theory and support vector machines. In: Industrial Conference on Data Mining. Lecture Notes in Artificial Intelligence: Advances in Data Mining. Vol. 6717: 323-337. Springer Berlin Heidelberg.

 Indexed Conference Papers

Óskarsdóttir, M. (*), Bravo, C., Sarraute, C., Baesens, B., & Vanthienen, J. Credit scoring for good: enhancing financial inclusion with smartphone-based microlending. In Proceedings of the Thirty Ninth International Conference on Information Systems, San Francisco, USA. 2018.

Óskarsdóttir, M. (*), Bravo, C., Verbeke, W., Sarraute, C., Baesens, B., and Vanathien, J. A comparative study of social network classifiers for predicting churn in the telecommunication industry In: Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining San Francisco (US):  IEEE. 2016.

Bravo, C., Figueroa, N. and Weber, R. “Game Theory and Data Mining Model for Price Dynamics in Financial Institutions”. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010). 1-8. 2010.

Bravo, C., Lobato, J.L., L’Huillier, G. and Weber, R. “A Hybrid System for Probability Estimation in Multiclass Problems Combining SVMs and Neural Networks”. In: HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems. 649-654. 2008.