An early prediction model on systemic risk under global risk: Using FinBERT and temporal fusion transformer to multimodal data fusion framework

Xiao Jin and Shu-Ling Lin

The North American Journal of Economics and Finance, 2025, vol. 76, issue C

Abstract: Several United States banks went bankrupt in 2023, and the total scale exceeded the subprime 2008 mortgage crisis. Thus, determining how to better predict banks’ systemic risks is crucial. While past research used quantitative data and statistical methods, rarely incorporated qualitative data, and lacked research exploring the impact of public confidence on systemic risk.

Keywords: Systemic risk; Public confidence; BERT; Transformer; Multimodal; Natural language processing (search for similar items in EconPapers)
JEL-codes: G01 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:76:y:2025:i:c:s1062940825000014

DOI: 10.1016/j.najef.2025.102361

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