An Enhanced Credit Risk Evaluation by Incorporating Related Party Transaction in Blockchain Firms of China

Ying Chen, Lingjie Liu () and Libing Fang
Additional contact information
Ying Chen: School of Management and Engineering, Nanjing University, 22 Hankou Road, Nanjing 210093, China
Lingjie Liu: Treasury Department, CITIC Group Corporation, 10 Guanghua Road, Beijing 100020, China
Libing Fang: School of Management and Engineering, Nanjing University, 22 Hankou Road, Nanjing 210093, China

Mathematics, 2024, vol. 12, issue 17, 1-23

Abstract: Related party transactions (RPTs) can serve as channels for the spread of credit risk events among blockchain firms. However, current credit risk-assessment models typically only consider a firm’s individual characteristics, overlooking the impact of related parties in the blockchain. We suggest incorporating RPT network analysis to improve credit risk evaluation. Our approach begins by representing an RPT network using a weighted adjacency matrix. We then apply DANE, a deep network embedding algorithm, to generate condensed vector representations of the firms within the network. These representations are subsequently used as inputs for credit risk-evaluation models to predict the default distance. Following this, we employ SHAP (Shapley Additive Explanations) to analyze how the network information contributes to the prediction. Lastly, this study demonstrates the enhancing effect of using DANE-based integrated features in credit risk assessment.

Keywords: related party transaction; credit risk evaluation; network embedding (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/17/2673/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/17/2673/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:17:p:2673-:d:1465986

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().