Models and algorithm for analyzing the register of debtors of an energy supply company based on the Loginom low-code platform

Purpose of research. Analysis of system relationships and identification of patterns between the characteristics of a subscriber of an energy supply company and the amount of his receivables based on data analysis models and tools of the Loginom low-code platform.

Methods. A classification of areas for the analysis of accounts receivable in power supply companies is given. It is shown that the study of accounts receivable situations in the context of the state of the organization and an individual debtor is possible on the basis of the data of the accounting system. For a detailed analysis of the register of debtors, it is necessary to consolidate data on subscribers, payments, as well as on objects of civil law. The choice of methods for analyzing the register of debtors of an energy supply company is substantiated. The process of creating a portrait of debtors is described. Problems of the initial data are revealed. The requirements for technologies and tools for the automation of analytical processes are formulated.

Results. A data processing scenario based on the low-code Loginom platform has been developed, which includes 6 logical blocks (notes) and 2 submodels. The Outlier Editing submodel is designed to improve the quality of the source data. The "Debtor Portrait" submodel based on correlation analysis and data clustering helps to obtain information for compiling a debtor portrait. With the help of cluster silhouettes, it is proposed to assess the quality of the constructed model "portrait of the debtor". Using the ABC analysis handler, subscribers with low payment discipline were ranked into categories. Analytical processes for making management decisions in relation to debtors of an energy supply company have been built.

Conclusion. An algorithm for the analytical process of working with debtors of an energy supply company has been developed. The information and analytical system "Debtor Analysis" based on the Loginom low-code platform was implemented. Tools for making management decisions based on the results of the analysis of the register of debtors have been implemented.

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