2 citations · 3 across the 8 of their papers we have counts for
8 papers
Communicating Credit Risk with Large Language Models: Evaluation of Explanations from Standard and Alternative Data-Based Models
Sahab Zandi, Noah Kostesku, Christophe Mues +2
Credit decisioning is a high-stakes task in which model outputs must be accurate and explainable to support compliant decisions. Although modern credit risk models such as eXtreme…
LLM-based Models for Detecting Emerging Topics in Service Feedback
Mahsa Tavakoli, Ruth Bankey, Cristián Bravo
Enhancing the analysis of service feedback is essential for public sector organizations, particularly tax administrations, where trust and compliance depend on fair and effective s…
Tabular Foundation Models for Credit Risk Prediction: A Dedicated Review and Empirical Comparison
Bart Baesens, Andreas Goethals, Stefan Lessmann +10
Predictive models are central to credit risk management, where the accuracy of default-probability and loss estimates affects the profitability of lending and the stability of the…
Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models: An Empirical Study using Environmental and Visual Predictors
Sherly Alfonso-Sánchez, Cristián Bravo, Kristina G. Stankova
Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constraining how this information can be…
A Multimodal Approach to SME Credit Scoring Integrating Transaction and Ownership Networks
Sahab Zandi, Kamesh Korangi, Juan C. Moreno-Paredes +3
Small and Medium-sized Enterprises (SMEs) are known to play a vital role in economic growth, employment, and innovation. However, they tend to face significant challenges in access…
Are causal effect estimations enough for optimal recommendations under multitreatment scenarios?
Sherly Alfonso-Sánchez, Kristina P. Sendova, Cristián Bravo
When making treatment selection decisions, it is essential to include a causal effect estimation analysis to compare potential outcomes under different treatments or controls, assi…
Large-scale Time-Varying Portfolio Optimisation using Graph Attention Networks
Kamesh Korangi, Christophe Mues, Cristián Bravo
Apart from assessing individual asset performance, investors in financial markets also need to consider how a set of firms performs collectively as a portfolio. Whereas traditional…
Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Prediction
Sahab Zandi, Kamesh Korangi, María Óskarsdóttir +2
Whereas traditional credit scoring tends to employ only individual borrower- or loan-level predictors, it has been acknowledged for some time that connections between borrowers may…