Research

Here you can find the list of the papers of the group.

Journal Papers (published or accepted)

Alfonso-Sanchez, S., Solano, J., Correa-Bahnsen, A., Sendova, K., Bravo, C. (2024). Optimizing Credit Limit Adjustments Under Adversarial Goals Using Reinforcement Learning. European Journal of Operational Research 315(2): 802-817. [ArXiV, Journal]

Bonacic, M., López-Ospina, H., Bravo, C., Pérez, J. (2024) Efficient portfolio construction through entropy maximization and fuzzy logic. Mathematics 12(13):1921. [Journal]

Brito, M. P., Stevenson, M., & Bravo, C. (2023). Subjective machines: Probabilistic risk assessment based on deep learning of soft information. Risk Analysis 43(3): 516-529.[Journal]

Muñoz-Cancino, R., Bravo, C., Ríos, S. A., & Graña, M. (2023). On the dynamics of credit history and social interaction features, and their impact on creditworthiness assessment performance. Expert Systems with Applications 218: 119599. [SSRN, Journal]

Muñoz-Cancino, R., Bravo, C., Ríos, S., and Graña, M. (2023) On the combination of graph data for assessing thin-file borrowers’ creditworthiness. Expert Systems with Applications 213 (Part A): 118809. [ArXiV, Journal]

Korangi, K., Mues, C., Bravo, C. (2023) A transformer-based model for default prediction in mid-cap corporate markets. European Journal of Operational Research 308(1): 306-320. [ArXiV, Journal]

Stevenson, M., Mues, C., & Bravo, C. (2022). Deep residential representations: Using unsupervised learning to unlock elevation data for geo-demographic prediction. ISPRS Journal of Photogrammetry and Remote Sensing, 187, 378-392. [ArXiV, Journal]

Óskarsdóttir, M. & Bravo, C. (2021). Multilayer Network Analysis for Improved Credit Risk Prediction. Omega 105: 102520. [ArXiV, Journal]

Stevenson, M., Mues, C., & Bravo, C. (2021). The value of text for small business default prediction: A deep learning approach. European Journal of Operational Research 295 (2): 758-771. [ArXiV, Journal]

Roa, L., Correa-Bahnsen, A., Suarez, G., Cortés-Tejada, F., Luque, M. A., & Bravo, C. (2020). Super-App Behavioral Patterns in Credit Risk Models: Financial, Statistical and Regulatory Implications. Expert Systems with Applications 169: 114486. [ArXiV, Journal]

Lazo, D., Calabrese, R., Bravo, C. (2020) The Impact of Borrower Behaviour, Sectorial Variables and Modelling Techniques on Credit Risk Assessment in the Agribusiness Sector. The Journal of Credit Risk 16 (4): 119-156. [Self-Archive, Journal]

Barrera-Ferro, D., Brailsford, S., Bravo, C. and Smith, H. (2020) Improving healthcare access management by predicting patient no-show behaviour. Decision Support Systems 138: 113398. [ArXiV, Journal]

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

Óskarsdóttir, M., Bravo, C., Verbeke, W., Sarraute, C., Baesens, B., Vanthienen, J. (2018). 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. [ArXiV, Journal] (2nd most downloaded paper in journal since 2018)

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. [Self-Archive, Journal]

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. [Self-Archive, Journal]

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. [Self-Archive, Journal]

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. [Self-Archive, Journal]

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. Edition in Chinese, published by Tsinghua University Press in February 2019. 6000 copies sold worldwide to date.

 

Journal Papers (under review)

Tavakoli, M., Chandra, R., Tian, F., Bravo, C. Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams. Revised and Resubmitted. [ArXiV]

Tiukhova, E., Penaloza, E., Óskarsdóttir, M., Baesens, B., Snoeck, M., Bravo C. INFLECT-DGNN: INFLuencer prEdiCTion with Dynamic Graph Neural Networks. Revised and Resubmitted. [ArXiV]

Zandi, S., Korangi, K., Mues, C., Óskarsdóttir, M., Bravo, C. Attention-based dynamic multilayer graph neural networks for loan default prediction. Revised and Resubmitted. [ArXiV]

Zhou, J., Davison, M., Bravo, C. The Gender and Ethnic Diversity of Boards and the Cost of Corporate Bond Issuance. Submitted [SSRN]

 

Book Chapters

Miasnikof, P., Shestopaloff, A. Y., Bravo, C., & Lawryshyn, Y. (2023, November). Empirical Study of Graph Spectra and Their Limitations. In International Conference on Complex Networks and Their Applications (pp. 295-307). Cham: Springer Nature Switzerland. [Publisher]

Miasnikof, P., Shestopaloff, A. Y., Bravo, C., & Lawryshyn, Y. (2022, November). Statistical network similarity. In International Conference on Complex Networks and Their Applications (pp. 325-336). Cham: Springer International Publishing. [Publisher, Self-Archive]

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 Ibero-American 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

Tuikhova, E., Penaloza, E., García, H., Correa-Bahnsen, A., Óskarsdóttir, M., Baesens, B., Snoeck, M. and Bravo, C. (2022). Influencer Detection with Dynamic Graph Neural Network. In: Proceedings of the NeurIPS 2022 Temporal Graph Learning Workshop. NeurIPS Foundation, USA, 7 pages.

Muñoz-Cancino, R., Bravo, C., Ríos, S. A., Graña, M. (2022). Assessment of Creditworthiness Models Privacy-Preserving Training with Synthetic Data In: Proceedings of the 17th International Conference Hybrid Artificial Intelligent Systems 375–384 Lecture Notes in Computer Science 13469 Springer.

Miasnikof, P., Shestopaloff, A. Y., Bravo, C., & Lawryshyn, Y. (2022). Statistical network isomorphism. Proceedings of The Eleventh International Conference on Complex Networks and their Application. Accepted for publication. Available as arXiv preprint arXiv:2206.10074.

Bravo, C. and Óskarsdóttir (2020). Evolution of Credit Risk Using a Personalized Pagerank Algorithm for Multilayer Networks.  In Proceedings of the Third KDD Workshop on Machine Learning in Finance, joint with 26th ACM SIGKDD Conference on Knowledge Discovery in Databases (KDD MLF 2020).  ACM, New York, NY, USA, 8 pages. (Selected as one of the six Spotlight Papers of the workshop)

Óskarsdóttir, M., Bravo, C., Sarraute, C., Baesens, B., & Vanthienen, J. (2018) 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.

Óskarsdóttir, M., Bravo, C., Verbeke, W., Sarraute, C., Baesens, B., and Vanathien, J. (2016) 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.

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

Bravo, C., Lobato, J.L., L’Huillier, G. and Weber, R. (2008) 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.

 

Policy Papers

Bravo, C., Calabrese, R., Lessmann, S., Mues, C., & Óskarsdóttir, M. (2023). Credit Risk and Artificial Intelligence: On the Need for Convergent Regulation. Available at SSRN 4615412. [SSRN, Top 10 most downloaded paper in Banking Regulation and Investment Decision Making Dec 2023–Feb 2024 @ SSRN]