Discovering bank risk factors from financial statements based on a new semi‐supervised text mining algorithm

Volume: 59, Issue: 3, Pages: 1519 - 1552
Published: Feb 19, 2019
Abstract
This paper aims to comprehensively uncover bank risk factors from qualitative textual risk disclosures reported in financial statements, which contain a huge amount of information on bank risks. We propose a new semi‐supervised text mining approach named naive collision algorithm to analyse the textual risk disclosures, which can more accurately identify bank risk factors compared with the typical unsupervised text mining approach. We identified...
Paper Details
Title
Discovering bank risk factors from financial statements based on a new semi‐supervised text mining algorithm
DOI
Published Date
Feb 19, 2019
Journal
Volume
59
Issue
3
Pages
1519 - 1552
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.