Improving Accuracy in Fraud Detection in Public Companies Financial Reports Using Natural Language Processing

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Angela Kurniawan, Laudya Yudha, Armanto Witjaksono
DOI: 10.5281/zenodo.18872345
Cited by: 0

Abstract

This dataset contains textual data used to analyze potential fraud in public companies’ financial reports. The data were collected from publicly available corporate reports and processed for Natural Language Processing (NLP) analysis.

Fields of Study & Subjects

Auditing Earnings Management Governance Benford’s Law and Fraud Detection Topic Modeling

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
31 January 2026
Language
EN
Document type
Dataset