Why do banks fail? An investigation via text mining - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Cogent Economics and Finance Année : 2023

Why do banks fail? An investigation via text mining

Résumé

This study aims to investigate the material loss review published by the Federal Deposit Insurance Corporation (FDIC) on 98 failed banks from 2008 to 2015. The text mining techniques via machine learning, i.e. bag of words, document clustering, and topic modeling, are employed for the investigation. The pre-processing step of text cleaning is first performed prior to the analysis. In comparison with traditional methods using financial ratios, our study generates actionable insights extracted from semi-structured textual data, i.e. the FDIC's reports. Our text analytics suggests that to prevent from being a failure; banks should beware of loans, board management, supervisory process, the concentration of acquisition, development, and construction (ADC), and commercial real estate (CRE). In addition, the primary reasons that US banks went failure from 2008 to 2015 are explained by two primary topics, i.e. loan and management.
Fichier principal
Vignette du fichier
Why do banks fail An investigation via text mining.pdf (4.91 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-04223185 , version 1 (03-06-2024)

Licence

Identifiants

Citer

Hanh Hong Le, Jean-Laurent Viviani, Fitriya Fauzi. Why do banks fail? An investigation via text mining. Cogent Economics and Finance, 2023, 11 (2), pp.2251272. ⟨10.1080/23322039.2023.2251272⟩. ⟨hal-04223185⟩
22 Consultations
6 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More