@inproceedings{d092fa6059c94f49bccfcb80e3ca5f53,
title = "Features and methods for automatic posting account classification",
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, Classification, Machine learning",
author = "Zigmunds Beļskis and Marita Zirne and Mārcis Pinnis",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.",
year = "2020",
doi = "10.1007/978-3-030-57672-1\_6",
language = "English",
isbn = "9783030576714",
volume = "1243 CCIS",
series = "Communications in Computer and Information Science",
pages = "68--81",
booktitle = "Databases and Information Systems - 14th International Baltic Conference, DB and IS 2020, Proceedings",
}