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A Quantitative Analysis of Default Risk Using Machine Learning and SHAP Value Interpretation Cover

A Quantitative Analysis of Default Risk Using Machine Learning and SHAP Value Interpretation

Proceedings of the International Conference on Business Excellence
Volume 18 (2024): Issue 1 (June 2024)
By:   
Open Access
|Jul 2024
Authors

Authors

Coralia Tanasuica Zotic

tanasuicacoralia22@stud.ase.ro

Academy of Economic Studies, Doctoral School of Economic Cybernetics and Statistics (SDCSE), Bucharest, Romania
DOI: https://doi.org/10.2478/picbe-2024-0020 | Journal eISSN: 2558-9652
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Language: English
Page range: 233 - 245
Published on: Jul 3, 2024
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Machine learning,
Model interpretability,
Payment Default Prediction,
Clustering,
Propensity to pay,
Bad debt,
Analytics
Related subjects:
Business and economics,
Political economics,
Political economics, other,
Business management,
Business management, other,
Industrial chemistry,
Energy harvesting and conversion

© 2024 Coralia Tanasuica Zotic, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 18 (2024): Issue 1 (June 2024)
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