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research-article

Financial risk prediction in supply chain finance based on buyer transaction behavior

Authors:

Fan LiAuthors Info & Claims

Volume 170, Issue C

https://doi.org/10.1016/j.dss.2023.113964

Published: 01 July 2023 Publication History

Abstract

Financial risk in supply chain finance (SCF) is defined as the possibility that suppliers fall into liquidity crisis due to delayed payment. Predicting financial risk is important for supply chain stability. In this paper, a financial risk prediction model is developed using XGBoost and then evaluated by applying buyer transaction behavior data. We further construct single and hybrid models, respectively, and compare their performance using receiver operating characteristic curve (ROC), area under the ROC curve (AUC), and F1-Score. Last, feature importance and partial dependence plots (PDPs) are employed for model interpretation. The results show that XGBoost model can effectively predict potential financial risks, and shed lights on managers' payment practice. This paper is one of the few studies that develop new models to examine financial risks in SCF empirically.

Highlights

•

Employ behavior data in mining the supply chain finance (SCF) risk, reflect the degree of delayed payments, and prove the rationality of the definition for the target risk.

•

Construct and compare single and hybrid machine learning models empirically with a sensitivity analysis.

•

Shed light on managers' understanding of SCF and promote their cooperation awareness by an interpretability analysis.

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Cited By

Coussement KAbedin MKraus MMaldonado STopuz K(2024)Explainable AI for enhanced decision-makingDecision Support Systems10.1016/j.dss.2024.114276184:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.dss.2024.114276
Zifla ERubini B(2024)Multi-criteria evaluation of health news storiesDecision Support Systems10.1016/j.dss.2024.114187180:COnline publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1016/j.dss.2024.114187

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Published In

cover image Decision Support Systems

Decision Support Systems Volume 170, Issue C

Jul 2023

88 pages

ISSN:0167-9236

Issue’s Table of Contents

Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 July 2023

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Cited By

Coussement KAbedin MKraus MMaldonado STopuz K(2024)Explainable AI for enhanced decision-makingDecision Support Systems10.1016/j.dss.2024.114276184:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.dss.2024.114276
Zifla ERubini B(2024)Multi-criteria evaluation of health news storiesDecision Support Systems10.1016/j.dss.2024.114187180:COnline publication date: 9-Jul-2024
https://dl.acm.org/doi/10.1016/j.dss.2024.114187

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