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  3. CreHos: Novel Machine Learning Algorithms and Alternative Data Sources for Better Credit Risk Assessment for the Hospitality Sector CreHos: Novel Machine Learning Algorithms and Alternative Data Sources for Better Credit Risk Assessment for the Hospitality Sector

CreHos: Novel Machine Learning Algorithms and Alternative Data Sources for Better Credit Risk Assessment for the Hospitality Sector

The goal of this project is to develop a novel credit risk assessment solution and methodology for the hospitality sector and small and mid-size enterprises (SMEs).

Brief information

School:

Business

Status:

Ongoing

Period:

01.01.2022 - 30.06.2026

Overview

The goal of this project is to develop a novel credit risk assessment solution and corresponding methodology for the hospitality sector and small and mid-size enterprises (SMEs) in general which (i) is based on interpretable machine learning methods, (ii) uses novel, alternative data sources, (iii) models spatial correlation, and (iv) allows for making multi-period forecasts.

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Facts

Type of project

Forschung

Internal organisations involved
  • Institute of Financial Services Zug (IFZ)
Funding
  • Innosuisse - HSLU als Hauptforschungspartnerin (Main Research Partner)
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Persons involved: internal

Project manager
  • Fabio Sigrist
Member of project team
  • Simon Broda
  • Pascal Kündig
  • Andrea Thomas Nava

Publications

  • Article, review; peer reviewed (3)

    • Kündig, Pascal & Sigrist, Fabio (03.12.2024). Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models. Journal of the American Statistical Association, 1-14. doi: 10.1080/01621459.2024.2410004

    • Leuenberger, Nicola & Sigrist, Fabio (2023). Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities. European Journal of Operational Research, 2023(3), 1390-1406.

    • Sigrist, Fabio (2023). Latent Gaussian Model Boosting. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023, 1894-1905.

Brief information

School:

Business

Status:

Ongoing

Period:

01/01/2022 - 06/30/2026

Project Head

Prof. Dr. Fabio Sigrist

Lecturer

+41 41 757 67 61

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