3 citations · 3 across the 6 of their papers we have counts for
6 papers
: Transparent and Fair Credit Risk Decisions through Semi-Structured Regressions
Victor Medina-Olivares, Stefan Lessmann, Jonathan Crook
Credit risk models increasingly need to combine predictive accuracy with transparent explanations and auditable fairness constraints. Logistic regression remains attractive because…
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…
Semi-structured multi-state delinquency model for mortgage default
Victor Medina-Olivares, Wangzhen Xia, Stefan Lessmann +1
We propose a semi-structured discrete-time multi-state model to analyse mortgage delinquency transitions. This model combines an easy-to-understand structured additive predictor, w…
Joint model for longitudinal and spatio-temporal survival data
Victor Medina-Olivares, Finn Lindgren, Raffaella Calabrese +1
In credit risk analysis, survival models with fixed and time-varying covariates are widely used to predict a borrower's time-to-event. When the time-varying drivers are endogenous,…
Detecting Consumers' Financial Vulnerability using Open Banking Data: Evidence from UK Payday Loans
Victor Medina-Olivares, Raffaella Calabrese
This paper examines whether repeated payday loan use, commonly known as the debt trap, harms borrowers' financial wellbeing. Using Open Banking data from 1,815 UK borrowers observe…
The Deep Promotion Time Cure Model
Victor Medina-Olivares, Stefan Lessmann, Nadja Klein
We propose a novel method for predicting time-to-event in the presence of cure fractions based on flexible survivals models integrated into a deep neural network framework. Our app…