A Machine Learning Algorithm for Supplier Credit Risk Assessment Based on Supply Chain Management

Abstract

In today’s complex and ever-changing world, a distribution network in lending impact analysis is an evaluation of a client’s procedures, rules, and financial well-being to evaluate as considerable risk and it provides to the contracting company. A creditor’s capability to pay the current lender’s obligations is considered while doing a lender’s threat assessment. Traditionally, it refers to the concern that the borrower may not be able to collect the sequence and interest. The challenges in lenders’ threat assessment are a lack of adequate data storage and retrieval, problematic delays caused by a lack of access to the relevant data at the right time, extended lead times that lead their shipments at risk, and demand for speedier deliveries. This paper introduces a machine learning-based linear regression algorithm (ML-LRA) for supplier credit risk (SCR) assessment based on supply chain management (SCM) in credit risk frameworks that depend significantly on modeling ML. Regression models are logistical constraints that can be used to simulate the impacts of multiple variables on a customer’s creditworthiness. The chain of distribution forecasting tool assesses specific decisions based on assumptions in variability. As a result of the findings in this study, it can be assumed that ML-LR approaches have a significant role in a variety of business processes such as supplier selection, risk prediction along with the supply chain, and demand and sales estimation. Finally, the study’s consequences for the most critical constraints and obstacles are examined to enhance the supply chain management system and ensure overall system sustainability.

A Comprehensive Survey of Cybersecurity Threats, Attacks, and Effective Countermeasures in Industrial Internet of Things

“…A further contribution in the article [114,115] provides a dynamic and self-adapting supply chain system that AI, ML, and genuine expertise drive4. This strategy intends to create a blueprint for Industry 4.0 supply chains of small and medium-sized businesses (SMEs), who frequently do not have the assets to manage digital security risks successfully.…”

“…Numerous investigations primarily focus on supply chain attack risk prevention strategies. [112][113][114][115][116].…”

Machine Learning-Based Risk Management of Credit Sales in Small and Midsize Business

“…Small businesses are particularly vulnerable to bad debts and financial instability because of the particular challenges associated with managing a diversified client base and transactions. Traditional risk assessment techniques, which need vast amounts of data, are insufficient in this complicated environment [1]. Examine the exciting subject of machine learning and ask us to imagine a simple program that could predict potential defaults with remarkable accuracy using massive quantities of customer behavior data.…”

Retracted: A Machine Learning Algorithm for Supplier Credit Risk Assessment Based on Supply Chain Management

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”