Survey of Methods and Tools of Automation for Recognition and Matching Invoices and Bank Transactions

Striving to automate processes in enterprises forces the search for solutions that will improve and shorten the time of repetitive transactions. One of such areas is recognizing and matching invoices and bank transactions. The main purpose of the paper is to present a state of the latest research
on methods and tools of automation for recognition and matching invoices and bank transactions. Automatic assignment of bank transactions to invoices using advanced computer algorithms
is essential for efficient and accurate accounting processes in enterprises. This paper investigates contemporary models, methods, and automation tools pertinent to pattern recognition, specifically focusing on their applications in automating invoice and bank transaction matching processes in enterprise financial IT systems. It underscores the significance of automatically attributing bank transactions to correct invoices, enabling streamlining of accounting processes and error reduction. A wide space of approaches is explored, including text recognition, semantic analysis, machine learning algorithms etc. Automatically assigning bank transactions to invoices using advanced computer algorithms is essential for efficient and accurate accounting processes in enterprises. In addition, it saves time and costs and minimizes the risk of making mistakes. At the same time, enterprises must pay attention to the quality of input data, the protection of personal data and the continuous improvement and updating of computer algorithms to ensure effective automation of accounting processes.