Banking business models and the nature of financial crisis

Hryckiewicz, Aneta; Kozłowski, Łukasz

doi:10.1016/j.jimonfin.2016.10.008

Cited by 54 publications

(45 citation statements)

References 31 publications

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“…The fourth and final method consists of employing hard clustering algorithms (Ayadi et al ., 2011; Ayadi and De Groen, 2015; Roengpitya et al ., 2014, 2017; Hryckiewicz and Kozłowski, 2017; Martín‐Oliver et al ., 2017). For instance, Martín‐Oliver et al .…”

Section: Literature Review On Methods Used To Identify Banking Businementioning

confidence: 99%

Using clustering ensemble to identify banking business models

Marques

Alves

2020

Intell Sys Acc Fin Mgmt

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Summary The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.

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Section: Literature Review On Methods Used To Identify Banking Businementioning

confidence: 99%

Using clustering ensemble to identify banking business models

Marques

Alves

2020

Intell Sys Acc Fin Mgmt

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“…They also may offer specialized services for their clients, their depositors or their borrowers. Heterogeneity across banking business models has a decided effect on bank risk and return, financial health, and system stability (Ayadi et al., ; Hryckiewicz & Kozlowski, , and Vander Vennet & Mergaerts, )…”

Section: Literature Review and Backgroundmentioning

confidence: 99%

“…Hryckiewicza and Kozlowskib () established how four distinct banking business models affected global bank profitability and risk during the recent financial crisis. Ayadi () and Avadi et al.…”

mentioning

confidence: 99%

Credit union business models

Stowe

2018

Financial Market

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Credit union decisions on how funds are raised and invested and what services to provide are guided by their business models and should be reflected by credit union financial statements. We use cluster analysis to group credit unions using common size financial statement variables such that the financial statements are similar within credit union groups and distinct across groups. This allows the assignment of credit unions to groups by knowing their essential elements but without predefining the groups. In this paper, we present six credit union strategic groups differentiated from each other by their asset‐liability management choices and the services they provide members. Identifying the various credit union groups provides a clearer picture of their business models and the economic roles that different credit unions play.

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“…On the other hand, banks' complexity and size have increased considerably in recent years ©International Monetary Fund. Not for Redistribution (Hryckiewicz and Kozlowski, 2017). Borio andDrehmann (2009) andSong, Thakor (2010) argued that banks have become more closely connected to capital markets and the performances of the two sectors are mutually connected with one another.…”

Section: Banksmentioning

confidence: 99%

“…Borio andDrehmann (2009) andSong, Thakor (2010) argued that banks have become more closely connected to capital markets and the performances of the two sectors are mutually connected with one another. In some countries (e.g., Belgium, the Netherlands, and Switzerland), the size of the banks has exceeded the size of the country in terms of GDP (Hryckiewicz and Kozlowski, 2017). The main feature of the banking sector compared to the two other sectors is that it encompasses the foreign exchange market which buys and sells currencies needed by the economy.…”

Section: Banksmentioning

confidence: 99%

Portfolio Inflows and Real Effective Exchange Rates: Does the Sectorization Matter?

Ouedraogo

2017

IMF Working Papers

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Banking business models and the nature of financial crisis

Cited by 54 publications

References 31 publications

Using clustering ensemble to identify banking business models

Using clustering ensemble to identify banking business models

Credit union business models

Portfolio Inflows and Real Effective Exchange Rates: Does the Sectorization Matter?

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