Identifying contextual content-based risk drivers for advanced risk management strategies

Shirley Hsueh-Li Huang, Guo-Hsin Hu and Ming-Fu Hsu

Research in International Business and Finance, 2025, vol. 73, issue PB

Abstract: This research proposes a profound contextual topic identifier that incorporates topic modelling and a word embedding technique to discover and quantify corporate risks from its self-identified risk disclosures and examines the association between each risk type and operating performance via artificial intelligence (AI) technique. Via topic modelling adoption, we are able to discover the most essential risks confronted by corporates in the near future and evaluate how they respond to these risks. To gain deeper insight, the study performs a bidirectional encoder representation from transformers (BERT) (one type of word embedding approach) to extract and quantify the semantic features embedded into each risk disclosure. The results show that operating performance significantly and positively relates to corporate-specific risks. This study offers solid and direct support for authorities that set accounting principles to encourage firm managers to add a new section on risk factors in annual reports.

Keywords: Artificial intelligence; Risk management; Decision making; Text mining; Word embedding (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0275531924004367
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:73:y:2025:i:pb:s0275531924004367

DOI: 10.1016/j.ribaf.2024.102643

Access Statistics for this article

Research in International Business and Finance is currently edited by T. Lagoarde Segot

More articles in Research in International Business and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().