Logistics enterprise's trade credit risk management in big data era

AbstractIn today’s trade, the vast majority of commercial transactions in both domestic and international trade are concluded by applying trade credit terms. The aim of this article is to analyse the trade credit insurance and, according to the methodology, to evaluate it as a credit risk management tool in the context of Lithuanian business market. The authors have proposed a methodology that combines theoretical and practical research methods. First of all, with assistance of qualitative analysis, the alternative external credit risk management tools were examined. Such analysis allows not only to identify the advantages, disadvantages and benefits of researched risk management tools but also to assess the efficiency and rationality of trade credit insurance in the context of alternative methods. In order to carry out an assessment in the practical aspect, considering the lack of statistical data, it was decided additionally to perform an expert evaluation. After performing an assessment of trade credit insurance, it was concluded that in international trade, with a large buyer portfolio and high sales volume, the trade credit insurance becomes the most effective and rational way to manage credit risk, which eliminates the losses because of the debtor’s insolvency or bankruptcy, manages countries and sector’s risks and helps to discipline the debtor, what determines the decline in overdue accounts frequencies, amounts and volumes.

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Trade Credit Risk Management: The Role of Executive Risk-Taking Incentives

Journal of Business Finance &amp Accounting ◽

10.1111/jbfa.12130 ◽

2015 ◽

Vol 42 (9-10) ◽

pp. 1188-1215 ◽

Cited By ~ 3

Author(s):

Anna Elsilä

Keyword(s):

Risk Management ◽

Credit Risk ◽

Risk Taking ◽

Trade Credit ◽

Credit Risk Management

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Big Data Credit Report in Credit Risk Management of Consumer Finance

Wireless Communications and Mobile Computing ◽

10.1155/2021/4811086 ◽

2021 ◽

Vol 2021 ◽

pp. 1-7

Author(s):

Lu Gao ◽

Jian Xiao

Keyword(s):

Risk Management ◽

Big Data ◽

Credit Risk ◽

Consumer Finance ◽

Credit Risk Management ◽

Fusion Model ◽

Gradual Improvement ◽

Credit Reporting ◽

Finance Industry ◽

Depth Analysis

Traditional consumer finance is a modern financial service method that provides consumer loans to consumers of all classes. With the gradual improvement of China’s credit reporting system, big data credit reporting has effectively made up for the lack of traditional credit reporting and has been widely used in the consumer finance industry. In this context, the in-depth analysis of the specific application of big data credit reporting in the credit risk management of consumer finance and the strengthening of the research on the application of big data credit reporting in the credit risk management of consumer finance are urgently needed to be resolved in the economic and financial theoretical and practical circles’ problem. This article mainly studies the research on credit risk management of consumer finance by big data. The experimental results of this paper show that the model has a good forecasting ability, can distinguish between normal loan customers and default loan customers, and is suitable for practical personal credit risk control business. The prediction accuracy of the default model of the fusion model is 97.14%, and the default rate corresponding to the actual business is 2.86%. By combining the risk items such as the blacklist and gray list in the Internet finance industry, the bad debt rate and illegal usury can be well controlled to meet industry supervision.

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An Empirical Study on Influencing Factors of Trade Credit Risk Management Performance in China

2010 International Conference on Management and Service Science ◽

10.1109/icmss.2010.5577026 ◽

2010 ◽

Author(s):

Bin Dai ◽

En-hua Liu

Keyword(s):

Risk Management ◽

Empirical Study ◽

Credit Risk ◽

Influencing Factors ◽

Trade Credit ◽

Credit Risk Management ◽

Management Performance

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Credit Risk Management of Consumer Finance Based on Big Data

Mobile Information Systems ◽

10.1155/2021/8189255 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Huibo Wang

Keyword(s):

Risk Management ◽

Big Data ◽

Credit Risk ◽

Consumer Finance ◽

Credit Risk Management ◽

Healthy Development ◽

Risk Management Process ◽

Core Concepts ◽

Credit Scores ◽

Definition Of

In recent years, China’s consumer finance has developed rapidly, but the foundation is unstable, and the industry has serious problems of violent competition, excessive credit, and fraud. Therefore, we should attach great importance to the healthy development of consumer finance, especially the management of its credit risk. The application of big data credit investigation can provide early warning of potential risks and prevent the risk of excessive credit investigation. This paper starts with the definition of basic core concepts, such as traditional credit investigation, big data credit investigation, and consumer finance, analyzes the performance and causes of consumer finance credit risk, and combs in detail the relevant theories of the application of big data credit investigation in consumer finance credit risk management. The application of big data credit investigation has optimized the risk management process of consumer financial institutions, deepened the concept of Internet consumer finance, improved the risk management system, created a diversified credit information system, and strengthened the innovation of Internet consumer finance products and services. For example, credit scores provide the most intuitive quantification of consumer credit risk. For consumers with different levels of credit scores, different credit approval processes can be matched. For customers with high scores, the work process can be simplified without affecting the work results. It can reduce the workload of employees by 20% and increase the accuracy of customer credit risk prediction by 16%.

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