The Evaluation of Trade Credit Insurance in Lithuanian Business Market as a Credit Risk Management Tool

Abstract

Abstract. In 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.

Research on Credit Algorithm of International Trade Enterprises Based on Blockchain

“…(3) Comparing the joint model based on blockchain and grey correlation model constructed in this paper with the traditional grey correlation model, it is found that the evaluation results of the improved grey correlation analysis model based on this paper are basically consistent with the tradition, which proves the accuracy of the international trade enterprise credit evaluation system based on blockchain technology and grey correlation analysis model constructed in this paper, and by comparing the results of the two models at the same time, it was found that the credit evaluation system of international trade enterprises based on blockchain technology and grey correlation analysis model constructed in this paper was superior to the traditional grey correlation model in terms of evaluation results, had a higher degree of identification, had more differentiated evaluation of enterprise credit, and could improve the accuracy of evaluation results. [27][28][29][30][31][32].…”

Analysis of companies’ bankruptcy in Poland as compared with the cost of protection under trade credit insurance

“…One of the methods of minimizing the negative effects of a situation when contractors are unable to meet their obligations is the use of trade credit insurance. Trade credit insurance protects the lender against the buyer's default risk, which may arise due to commercial and political risks, so the insurers mainly cover the short-term commercial risk (Lezgovko & Jakovlev, 2017). It should be noted, however, that due to its specific nature, trade credit insurance is dependent on the macroeconomic situation in the industry, which makes them extremely sensitive to any changes in business cycles, which in turn significantly increases their susceptibility to macroeconomic risk (Lisowski, 2014).…”

“…However, as I. Kwiecień (2010) points out, when it comes to corporate management standards, the decision to choose insurance as an instrument of risk management should be supported by an analysis of the risk occurring in the company's environment.…”

Factors Affecting the Credit Risk Management in the Banking Sector of Pakistan: Moderating Effect of Financial Technology

“…These approaches, which include statistical models, financial indicators, and credit rating systems, may evaluate the likelihood of default and potential credit losses. Strong credit risk assessment tools assist banks in making better lending decisions, using capital more efficiently, and maintaining appropriate provisioning levels (Lezgovko & Jakovlev, 2017).…”