#3160. Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

October 2026publication date
Proposal available till 11-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Finance;
Business, Management and Accounting (all);
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Abstract:
Mapping financial transfers to the corresponding accounts is important in accounting. The research examines the ways machine-learning-based systems automate this process using word embeddings with character-level features to process transaction texts. The analysis of 473 companies examines the transaction texts or rely on a lexical bag-of-words text representation. A single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.
Keywords:
accounting; finance; financial transactions; multiclass classification; random forest method; word embedding

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