MODELING OF AUTOMATIC DATA RECONCILIATION PROCESSES IN ELECTRONIC PAYMENT SYSTEMS BASED ON NATURAL LANGUAGE PROCESSING METHODS
Abstract
The article is devoted to the actual problems of data reconciliation in electronic payment systems. The aim of the work is to develop a model for the process of data reconciliation in electronic payment systems based on natural language processing methods and ensure its integration into payment transaction processing systems. With the spread of electronic payment systems within the concept of Open Banking, the number of transactions, the variety of payment systems, and, accordingly, the complexity of reconciling payment data has increased dramatically. This is due to the fact that the data come from different sources and have a heterogeneous structure that is difficult to recover by formal methods. This increases the share of payments that have to be reconciled manually, which, in turn, leads to an increase in the costs of operating the payment system. Therefore, at present, research on the automation of reconciliation processes, based on the use of artificial intelligence methods, in particular, natural language processing, is becoming relevant. The existing approaches to a reconciliation of payment data are systematized and their genesis is analyzed. It turned out that in recent years the number of publications on reconciliation methods based on the analysis of big data and the use of semantic models has been growing, but a number of issues on building payment data reconciliation systems have not yet been disclosed. This concerns the integration of automatic reconciliation services into payment transaction processing systems. The main stages of payment data reconciliation, the differences between business and technical transactions, the main operations of the data reconciliation process, and reconciliation scenarios have been explored. A model of the reconciliation process in a company that is a Payment Service Provider (PSP) has been developed. A model for the operation of the service for automatic reconciliation of payment data and a scheme for its integration into the PSP information system has been developed. The problems of automatic data reconciliation are highlighted, namely: discrepancy between data exchange formats; a discrepancy in field names; data structure discrepancy; error in the content of the fields; different accuracy of numerical values; temporary gaps; splitting transaction amounts. The ways of solving these problems through the use of natural language recognition methods are outlined.
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