Trade credit management in wholesale companies based on statistical methods

Abstract

Study purpose. The paper shows the application of statistical methods for the trade credit management in the wholesale Russian companies. In this industry, the companies deal with a huge amount of customers, while trade credit is a common practice. As a result, fast and reasonable choice of trade credit terms becomes especially important for wholesale companies. The main study purpose is to provide the methods to choose the trade credit terms.Materials and methods. In this paper, the methods for trade credit management are based of the empirical research where binomial logistic model and discriminant analysis were used. The binomial logistic model was used to assess the customers’ reliability, his inclination to violate the terms specified in the contract. The delay period must be chosen when trade credit is provided. In the paper, the discriminant analysis was applied to make the decision. The discriminant functions allow choosing such a period of delay that will be broken with the least probability by the customer with certain financial and non-financial characteristics. The data used refer to 11 Russian companies from the wholesale industry and include 720 observations for 2016-2017.Results. As a result, the possibility of due repayment may be evaluated and the payment delay may be selected according to individual customers’ characteristics. Eight factors that characterize the liquidity of the purchaser, its profitability, turnover, and non-financial factors became significant to assess the reliability. In conclusion, the paper contains the practical example for four hypothetical purchasers with different characteristics. The higher the reliability of the customer, the more attractive conditions can be offered for him, depending on the propensity to risk of the wholesale company, as well as its financial opportunities.Conclusion. This article contains the model to evaluate the possibility of due repayment and algorithm to select the payment delay, which are based on the binomial logistic model and classification functions. Although there are a large number of methods to select the terms of trade credit, the majority of them have serious limitations. The most of methods are based only on the professional experience, while statistical analysis, in presence, is based on data of one company because of the confidentiality of necessary information. In contrast, this article is based on the empirical data and includes the delay period selection, which is slightly enlightened in the literature.