With the advent of the era of Big Data, machine learning techniques are widely used in many technologies and industries. In machine learning, neural networks are used to recognize relationships between data. In this paper, neural networks are developed to support accounting processes. The neural networks use the texts from the bank statements as input for the neural network to predict the debit and credit account as well as the value-added tax percentage on the account bank statement. Fifteen different neural network models were built and evaluated based on accuracy and loss. The best-found neural network model is described in detail. The paper also discusses issues of data quality and pre-processing techniques.

JEL Classifications: C45; D83; M41.

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