most citedExplainable Automated Machine Learning for Credit Decisions: Enhancing Human Artificial Intelligence Collaboration in Financial Engineering

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2026

Digital Ecosystems: Enabling Collaboration in a Fragmented World

Marc Schmitt

As geopolitical, organizational, and technological fragmentation deepens, resilient digital collaboration becomes imperative. This paper develops a spectrum framework of polycentri…

q-fin.RM2026

Algorithmic Monitoring: Measuring Market Stress with Machine Learning

Marc Schmitt

I construct a Market Stress Probability Index (MSPI) that estimates the probability of high stress in the U.S. equity market one month ahead using information from the cross-sectio…

q-fin.RM2026

Taming Tail Risk in Financial Markets: Conformal Calibration for Nonstationary Portfolio VaR

Marc Schmitt

Value-at-risk (VaR) forecasts drive trading constraints and capital allocation, yet realized exceedance rates concentrate in stress periods, when losses are largest. This paper stu…

q-fin.RM2024★ 2 cited

Explainable Automated Machine Learning for Credit Decisions: Enhancing Human Artificial Intelligence Collaboration in Financial Engineering

Marc Schmitt

This paper explores the integration of Explainable Automated Machine Learning (AutoML) in the realm of financial engineering, specifically focusing on its application in credit dec…

cs.HC2024

Human-Centered AI Product Prototyping with No-Code AutoML: Conceptual Framework, Potentials and Limitations

Mario Truss, Marc Schmitt

This paper addresses the complexities inherent in AI product prototyping, focusing on the challenges posed by the probabilistic nature of AI behavior and the limited accessibility…