Support of Accounting by Bank Statement Classification Using Neural Networks

ABSTRACT 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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Publication Details

Journal
Journal of Emerging Technologies in Accounting
Published
2024-10-25
DOI
https://doi.org/10.2308/jeta-2022-073
Citations
2
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.98
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article

Support of Accounting by Bank Statement Classification Using Neural Networks

Thomas Hanne, Kit Fai Wong
2 citations
Journal of Emerging Technologies in Accounting
Stock Market Forecasting Methods
0.98
article

Support of Accounting by Bank Statement Classification Using Neural Networks

Thomas Hanne, Kit Fai Wong
article en
2 citations

Abstract

ABSTRACT 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.

Journal of Emerging Technologies in AccountingVol. 22(1)
FHNW University of Applied Sciences and Arts Northwestern Switzerland (CH)
Openalex Percentile: Top 21%
Stock Market Forecasting Methods
0.98
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Support of Accounting by Bank Statement Classification Using Neural Networks — Thomas Hanne, Kit Fai Wong · Journal of Emerging Technologies in Accounting (2024) | TGRS Research Map | TGRS