Publications in peer-reviewed journals 

[1] Alves, C.F., Citterio, A., & Marques, B. P. (2023). Bank-specific capital requirements: Short and long-run determinants. Finance Research Letters, 52, 103558. (download)

This paper studies the determinants of the Pillar 2 capital requirements (P2R) of banks directly supervised by the ECB between 2016 and 2021. Drawing on the ECB's Supervisory Review and Evaluation Process (SREP) to identify the list of potential drivers of P2R, we estimate the impact on P2R by employing a method that separates long-run from short-run determinants. Our results suggest that in (i) the long-run, the P2R is mostly driven by credit risk, funding risk, and governance, whereas (ii) profitability and market risk seem to be the main short-run determinants of P2R. Furthermore, we find evidence that suggests the supervisor incorporates proportionality in the P2R decisions. Effectively, our sensitivity analyses show considerable differences in the long-run determinants of P2R according to the level of capital, size, and access to market funding of supervised entities. 

[2] Marques, B. P., & Alves, C.F. (2022). Transnational banking supervision, distance-to-distress and credit risk: the SSM case. Applied Economics Letters, forthcoming (download)

We assess the impact of adopting a transnational supervisor on the distance-to-distress and credit risk of large and complex banks, exploring the establishment of the Single Supervisory Mechanism (SSM) in 2014 as a quasi-natural experiment. Using a differences-in-differences approach, we compare SSM banks vis-à-vis banks with a similar size and complexity operating in European countries outside the SSM. Our results suggest that adopting a transnational supervisor increases the distance-to-distress, particularly for banks operating in countries with larger banking sectors, higher market concentration and greater supervisory discretion. We also show that SSM banks reduced loan loss reserves and NPLs significantly more than non-SSM banks, but only among the most capitalized banks – which is consistent with the notion that well-capitalized banks are better able to weather haircuts induced by credit risk reduction initiatives. Interestingly, we find that SSM banks from countries with greater supervisory discretion saw their NPLs increase in the first years of the SSM, which could reflect the elimination of national idiosyncrasies in credit risk accounting. In general, the evidence presented in our paper suggests that transnational supervision bears a superior ability to increase the distance-to-distress, reduce credit risk, and harmonize supervisory practices among large and complex banks.

[3] Marques, B. P., & Alves, C.F. (2021). The profitability and distance to distress of European banks: do business choices matter? The European Journal of Finance, 27(15), 1553-1580. (EJF download) (WP version)

This paper examines which business choices are more likely to increase the profitability and distance to distress of banks, and whether changing business model pays off. We find that the profitability and distance to distress increase with the use of customer deposits and equity, and decrease with size; also, the top performers tend to have a high relationship banking orientation and/or operate a retail focused business model. Furthermore, we document that income diversification only bears a positive impact on the distance to distress of banks highly focused on relationship banking, and size only bears a negative effect on the profitability of these banks as well; additionally, only banks with a low relationship banking orientation significantly benefit from customer deposits. With respect to the effects of business model changes, we find that shifts from the retail diversified funding model to either the retail focused or the large diversified models improve profitability in the medium term. Finally, we find evidence that large diversified banks benefited from internal capital markets during the twin financial crisis by tapping into low-cost funding from subsidiaries. Our results are robust to changes to our baseline model that account for endogeneity and persistency issues. 

[4] Marques, B. P., & Alves, C.F. (2020). Using clustering ensemble to identify banking business models. Intelligent Systems in Accounting, Finance and Management, 27(2), 66-94. (ISAFM download) (WP version) 

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. 

Working papers

[1] Marques, B. P., & Alves, C.F. (2021).  Business model diversity and banking sector resilience. FEP Working Paper. (download)

What is the impact of the diversity of business models operating in a banking sector and its resilience? Literature offers mixed predictions: while one strand of literature puts emphasis on the virtues of diversity due to lower contagion, an opposing strand suggests that nudging banks to choose diverse diversification strategies (which tend to be individually sub-optimal) may be ‘a worse remedy than the disease’. This paper provides several contributions to this discussion: (i) the development of a two-step measure of business model diversity, based on the application of clustering techniques on a set of business model variables at the bank level, followed by their aggregation at the country level, (ii) the specification of a 3SLS model that explicitly considers the interactions of business model diversity with diversification and market power in explaining banking sector resilience, (iii) the breakdown of the baseline results per type of financial system (i.e. bank vs market-based), and (iv) the analysis of the diversity and composition of optimal country-level portfolios of banking business models. In general, our results suggest that more resilient banking sectors tend to be more diverse (i.e., assets are well distributed across different bank types), less revenue diversified and exhibit more market power than less resilient ones. Additionally, a deeper dive tells us that such relationship between diversity and resilience seems to occur chiefly in market-based systems. Finally, the analysis of efficient portfolios confirms that a similar level of diversity may induce different resilience responses according to the type of financial system, which we attribute to the ‘ecosystem'.

[2] Citterio, A., Marques, B. P., & Tanda, A. (2022). The early days of neobanks in Europe: identification, performance, and riskiness. Working Paper. 

This paper identifies banks that are born with a digital business model (“neobanks”) and examines their performance and riskiness vis-à-vis traditional incumbents. We propose a novel approach to identify neobanks, based on non-financial data, hand-collected from different sources, and document the existence of 55 neobanks in 17 European countries. Our findings show that, on average, neobanks perform worse and are riskier than their incumbent peers. On one hand, neobanks seem to adequately price the risk of lending to high-risk borrowers and record staff efficiencies. On the other hand, they charge significantly lower fees and commissions and record higher non-staff expenses. Further analysis suggests that such non-staff inefficiencies disappear when we consider banks that are older than 8 years or that offer at least 3 types of products. Our findings are robust to endogeneity concerns and changes to our baseline specification.