Research on measurement of supply chain finance credit risk based on Internet of Things

Abstract

This article first expounds the concept of supply chain finance and its credit risk, describes the hierarchical structure of the Internet of Things and its key technologies, and combines the unique functions of the Internet of Things technology and the business process of the inventory pledge financing model to design the supply chain financial model based on the Internet of Things. Then it studies the credit risk assessment under the supply chain financial model based on the Internet of Things, and uses the support vector machine algorithm and Logistic regression method to establish a credit risk measurement model considering the subject rating and debt rating. Finally, an example analysis shows that the credit risk measurement model has a high accuracy rate for determining whether small and medium-sized enterprises in the supply chain financial model based on the Internet of Things are trustworthy. This will facilitate the revision and improvement of the existing credit evaluation system and improve the accuracy of measuring the current financial risk of supply chain. This research adopts the Internet of Things to measure financial credit risk in supply chain and provides a reference for the following researches.

Can Supply Chain Finance help mitigate the financial disruption brought by Covid-19?

“…Furthermore, SCF benefits extensively from adopting digital technologies to make processes faster and cheaper and enable innovative solutions that can involve more companies at lower costs ( Caniato et al, 2016 ). Several technologies can be considered, such as Electronic Invoicing, Artificial Intelligence ( Moretto et al, 2018 ), or the Internet of Things ( Abbasi et al, 2019 ). However, all these opportunities are still under-investigated ( Caniato et al, 2019 ).…”

Strategy selection of inventory financing based on overconfident retailer

“…And the cost of sales effort is paid by the retailer's own funds. The overconfident retailer need to pay 1 2 ke 2 o + wq o (1 − ω). 5.…”

“…Zhu et al [36] applied six methods to predict the credit risk of small and medium-sized enterprises. Abbasi et al [1] established a credit risk measurement model considering subject rating and debt rating by using support vector machine algorithm and logistic regression method, so as to evaluate the credit risk of inventory financing mode. However, these studies only measure the risk of inventory financing, and do not discuss how to control or avoid the risk.…”

A supervised machine-learning method for optimizing the automatic transmission system of wind turbines

“…Linear Regression, Logistic Regression, Support Vector Machine, Naive Bayes, Random Forest, Decision Tree, Single-Layer Perceptron, Multi-Layer Perceptron, and K-nearest Networks are among the most popular Supervised Machine-learning Algorithms. (Abbasi et al, 2019) focused on financial-based risk assessment in supply chains while the Internet of things comes into consideration. For this purpose, they used Support Vector Machine and Logistic regression methods to rate the developed risk assessment model.…”