THE USE OF ECONOMIC AND MATHEMATICAL MODELING FOR THE MANAGEMENT OF ACCOUNTS RECEIVABLE

In conditions of a difficult economic situation in the Russian reality, companies have to deal not only with the search for potential customers, sales and promotion of their goods, but also with overdue payments from debtors.

Accounts receivable is the sum of debts owed to the organization from legal entities or individuals as a result of economic relations between them, or, in other words, the diversion of funds from the organization’s turnover and their use by other organizations or individuals.

The tendency of the presence and increase of accounts receivable leads to the actual immobilization of a part of current assets, which is the reason for the decrease in financial stability and solvency of enterprises. In this regard, the actual problem is the development of measures to manage receivables.

The company “Robert Bosch”, which belongs to the category “Production, trading and manufacturing companies”, was selected as the analyzed enterprise. The data presented in the balance sheet of the LLC Robert Bosch for 2015-2017 were analyzed and also it was calculated some indicators: the indicator of average receivables, the turnover ratio of accounts receivable and the period of turnover of receivables.

According to the balance sheet, the average receivables at the end of 2017 is 4 034 502 thousand rubles. At the same time, it is worth noting that according to the analysis of the dynamics of revenue and the dynamics of average receivables, it can be seen that, in fact, the share of receivables in current revenue as of 2017 is 15 %, which means that the company lost 15 % of its share proceeds from the total.

Figure 1 graphically presents dynamics of revenue and dynamics of average receivables for the analyzed period.

Figure 1. Dynamics of revenue and dynamics of average accounts receivable for the analyzed period

In order to improve the receivables management process in LLC Robert Bosch, it is proposed to introduce regulations for work with overdue receivables and develop a scale of fines and remunerations for the counterparties of the enterprise.

To start with, it is necessary to develop a scale of penalties for overdue receivables.

Considering two options for penalties, namely, 0.1% for each day of overdue payment and a penalty taking into account the refinancing rate, it was concluded that 0.1% for each day of overdue payment is a better option.

Table 1 presents a fragment of the modeling of penalties for 20 debtors. The current date was the date of January 9, 2019.

Table 1.

Fragment of the modeling of penalties for debtors

As we see, due to a simulation model, we managed to establish debtors. If in the simulation model we set a condition that when a debt exceeds 35,000 rubles the company goes to court, then it turns out that the company can go to court about the status of 13 debtors.

Total, taking into account fines for January 9, 2019, we should receive in total 919866 from 20 debtors.

In addition to the scale of penalties, the scale of rewards should also be developed.

The scale of rewards is distributed as follows:

1-10 days before payment – 0.06 %

11-20 days before payment –  0.1 %

21-30 days before payment –  0.5 %

31-40 days before payment – 1 %

More than 40 days before payment – 1.23 %

Simulation results are presented in table 2.

Table 1.

Fragment of reward scale modeling

Total it turns out that the company will have to pay its debtors a fee in the amount of 847,245 for premature payment of shipments.

Thus, the data of these simulation tables can be used by the company to motivate debtors to make early payments.

Also, the developed tables save the data, which will allow further tracking of debtors and making decisions regarding changes in the schemes of penalties and remuneration due to modeling.

Undoubtedly, these tables will also help to effectively manage receivables.

Bibliography:

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