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International Baltic Conference on Databases and Information Systems

DB&IS 2020: Databases and Information Systems pp 68–81Cite as

Features and Methods for Automatic Posting Account Classification

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1243)

Abstract

Manual processes in accounting can introduce errors that affect business decisions. Automation (or at least partial automation of accounting processes) can help to minimise human errors. In this paper, we investigate methods for the automation of one of the processes involved in invoice posting – the assignment of account codes to posting entries – using various classification methods. We show that machine learning-based methods can reach a precision of up to 93% for debit account code classification and even up to 98% for credit account code classification.

Keywords

  • Accounting
  • Machine learning
  • Classification

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Acknowledgements

The research has been supported by the ICT Competence Centre (www.itkc.lv) within the project “2.6. Research of artificial intelligence methods and creation of complex systems for automation of company accounting processes and decision modeling” of EU Structural funds, ID n\(^{\circ }\) 1.2.1.1/18/A/003.

Author information

Authors and Affiliations

  1. Tilde, Vienibas Gatve 75A, Riga, 1004, Latvia

    Zigmunds Beļskis, Marita Zirne & Mārcis Pinnis

  2. University of Latvia, Raiņa blvd 19-125, Riga, 1586, Latvia

    Mārcis Pinnis

Authors
  1. Zigmunds Beļskis
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  2. Marita Zirne
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  3. Mārcis Pinnis
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Corresponding author

Correspondence to Mārcis Pinnis .

Editor information

Editors and Affiliations

  1. Department of Computer Systems, Tallinn University of Technology, Tallinn, Estonia

    Dr. Tarmo Robal

  2. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Hele-Mai Haav

  3. Department of Software Science, Tallinn University of Technology, Tallinn, Estonia

    Jaan Penjam

  4. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Prof. Dr. Raimundas Matulevičius

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Beļskis, Z., Zirne, M., Pinnis, M. (2020). Features and Methods for Automatic Posting Account Classification. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_6

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  • DOI: https://doi.org/10.1007/978-3-030-57672-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57671-4

  • Online ISBN: 978-3-030-57672-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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