We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Discovering bank risk factors from financial statements based on a new semi‐supervised text mining algorithm.
- Authors
Wei, Lu; Li, Guowen; Zhu, Xiaoqian; Li, Jianping
- 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 21 bank risk factors in total, which is far more than identified in previous studies. We further analyse the importance of each bank risk factor and how the importance of each risk factor changes over time.
- Subjects
FINANCIAL statements; DISEASE risk factors; FINANCIAL disclosure; BANKING industry; ALGORITHMS
- Publication
Accounting & Finance, 2019, Vol 59, Issue 3, p1525
- ISSN
0810-5391
- Publication type
Article
- DOI
10.1111/acfi.12453