TY - JOUR
T1 - Banks' Business Strategies on the Edge of Distress
AU - Flori, Andrea
AU - Giansante, Simone
AU - Girardone, Claudia
AU - Pammolli, Fabio
N1 - Funding Information:
The authors are grateful for comments from the guest editors and two anonymous referees that have improved the paper. We also thank inputs from Ozlem Akin, Kim Cuong Ly, Pietro Perotti, Steven Ongena, participants of the Workshop on Bank Business Models at Cass Business School, and seminars at the University of Bath School of Management, University of Reading ICMA centre, IMT Lucca, Polytechnic University of Milan and University of Swansea.
Publisher Copyright:
© 2019, The Author(s).
PY - 2021/4/1
Y1 - 2021/4/1
N2 - The paper investigates the importance of banks’ business classification in shaping the risk profile of financial institutions on a global scale. We employ a rare-event logit model based on a state-of-the-art list of major global distress events from the global financial crisis. When clustering banks by their business strategies using a community detection approach, we show that (i) capital enhanced resilience only for traditional banks that were on average less capitalized than other banks; (ii) boosting ROE, usually associated with riskier exposures, improved resilience for stable funded and asset diversified banks; (iii) conversely, higher levels of ROA exacerbated banks’ vulnerability when associated with concentrated (not-diversified) investment structures; (iv) size in terms of total assets contributed to instability only for wholesale-funded institutions due to their high levels of unstable funding. Liquidity, on the contrary, reduced the institution likelihood of being in distress, regardless of its business classification. Although our findings refer to the recent financial crisis, they provide evidence that a tailored risk monitoring based on a proper peer group identification can facilitate banks’ distresses prediction.
AB - The paper investigates the importance of banks’ business classification in shaping the risk profile of financial institutions on a global scale. We employ a rare-event logit model based on a state-of-the-art list of major global distress events from the global financial crisis. When clustering banks by their business strategies using a community detection approach, we show that (i) capital enhanced resilience only for traditional banks that were on average less capitalized than other banks; (ii) boosting ROE, usually associated with riskier exposures, improved resilience for stable funded and asset diversified banks; (iii) conversely, higher levels of ROA exacerbated banks’ vulnerability when associated with concentrated (not-diversified) investment structures; (iv) size in terms of total assets contributed to instability only for wholesale-funded institutions due to their high levels of unstable funding. Liquidity, on the contrary, reduced the institution likelihood of being in distress, regardless of its business classification. Although our findings refer to the recent financial crisis, they provide evidence that a tailored risk monitoring based on a proper peer group identification can facilitate banks’ distresses prediction.
KW - Bank business strategies
KW - Bank distress
KW - Clustering
KW - Financial crisis
UR - http://www.scopus.com/inward/record.url?scp=85073976147&partnerID=8YFLogxK
U2 - 10.1007/s10479-019-03383-z
DO - 10.1007/s10479-019-03383-z
M3 - Article
VL - 299
SP - 481
EP - 530
JO - Annals of Operations Research
JF - Annals of Operations Research
SN - 0254-5330
IS - 1-2
ER -