EBA欧洲银行-Discusssant_2_Oana-Toader_11页_488kb

报告摘要

Summary of "Bank Business Model Migrations in Europe: Determinants and Effects"

Core Content

This document presents an analysis of business model (BM) migrations among European banks, focusing on the determinants and effects of such changes on bank performance. The study utilizes a large dataset comprising 3,287 banks from 32 EEA countries and Switzerland, with 22,787 bank-year observations from 2005 to 2016. The objective is to identify the factors driving business model changes and assess their impact on bank performance.

Business Model Classification

The authors classify banks into five distinct business model categories using a cluster analysis based on the methodology from Ayadi and de Groen (2014) and Ayadi et al. (2016). These categories are:

Focused retail
Diversified retail (type 1)
Diversified retail (type 2)
Wholesale
Investment

The classification is based on a set of variables, which include profitability, cost efficiency, capitalization, risk appetite, and credit portfolio quality. A detailed list of variables used in the cluster analysis should be provided for transparency.

Evaluation of Business Model Changes

The study identifies that about 10% of the sample migrated during the study period, resulting in approximately 1,400 changes. The transition matrix is used to evaluate the changes in BM over time, considering factors such as bank size, ownership structure, and membership in the European Banking Authority (EBA).

Determinants of BM Switches

Using logit regression, the authors identify the main drivers of business model changes, including:

Low profitability
High risk
High capitalization

Additionally, the study finds that banks that received state aid during the financial crisis are more likely to change their business model. This suggests that state intervention played a significant role in enabling or facilitating the transition.

Effects of BM Changes on Performance

The impact of business model changes on performance is evaluated using propensity score matching, a method that helps isolate the effect of migration by controlling for observable differences between migrating and non-migrating banks. Key findings include:

Migration positively affects bank performance in the year following the change.
Migrating banks tend to have lower profitability, lower cost efficiency, higher capitalization, and higher risk appetite compared to non-migrating banks.
Migrating banks also show lower credit portfolio quality, as indicated by a higher loan loss provision ratio.

Additional Findings

Banks that adopt focused retail or wholesale business models are less willing to migrate, suggesting a certain stability in these models.
During the financial crisis, banks that changed their business model were typically smaller, involved in M&A operations, and had received state aid or had been nationalized.
The sample distribution by country and year shows significant fluctuations, particularly between 2009 and 2010, indicating changes in the banking landscape during the crisis.

Methodological Notes

The methodology is well-documented and includes detailed robustness checks.
The absence of regulatory standards in the identification strategy is noted as a potential limitation.
The macroeconomic environment should be considered when analyzing the drivers of BM changes, as it can influence both the decision to migrate and the subsequent performance outcomes.
The SNL classification (e.g., commercial banks, savings and loans banks, cooperative banks, public banks) should be more clearly linked to the BM classification to enhance the interpretation of results.

Conclusion and Policy Implications

The study provides a tractable framework for understanding the dynamics of business model changes in European banking, with strong policy implications. It highlights the importance of profitability, risk, and capitalization in driving migrations and suggests that state aid and M&A activity are critical enablers of such transitions. The results also indicate that business model changes can improve performance, particularly in the short term.