Analysts often refer to bank business models, but there is no established notion of what a bank business model is or how one model differs from another. In this paper, we lay out a method for classifying banks into distinct business models and apply this method to data on balance sheet ratios. We also study banks' performance in each model and relate performance to transitions across models.
A reliable way to identify bank business models is useful to both bank investors and policymakers. Depending on their business models, banks emphasise some activities over others. A good match between a model and available opportunities helps profitability, a key concern for stakeholders. More information about models gives supervisors more insight into banks' resilience and helps them identify broader risks in the banking system. Switching from one model to another can help an underperforming bank survive. Our classification method is mainly data-driven but also incorporates judgment in a systematic way. The data cover 178 banks from 34 countries over the period 2005-15. To focus on stable results, we filter out classifications that are sensitive to input data or the specific classification algorithm.
We identify four business models. Two involve commercial banks with large loan portfolios but with differences in their funding base: one is mainly retail-funded, through deposits, and the other wholesale-funded, through bonds and interbank markets. A third model emphasises trading activities, for which banks hold securities portfolios funded in the interbank and wholesale markets. The fourth, universal, banking model is a mix of the other three.
There are clear patterns in banks' performance and transitions from one business model to another. The two commercial banking models show lower cost-to-income ratios and more stable return-on-equity than the trading model. In a reversal of a pre-crisis trend, many banks moved away from wholesale-funded and into retail-funded banking after 2008. Over the entire sample period, banks that switched to the retail-funded model improved their return-on-equity by 2.5 percentage points on average compared to non-switchers. By contrast, the relative performance of banks switching into the wholesale-funded model deteriorated by 5 percentage points on average.
We allocate banks to distinct business models by experimenting with various combinations of balance sheet characteristics as inputs in cluster analysis. Using a panel of 178 banks for the period 2005-15, we identify a retail-funded and a wholesale-funded commercial banking model that are robust to the choice of inputs. In comparison, a model emphasising trading activities and a universal banking model are less robustly identified. Both commercial banking models exhibit lower cost-to-income ratios and more stable return-on-equity than the trading model. In a reversal of a pre-crisis trend, the crisis aftermath witnessed mainly switches away from wholesale-funded and into retail-funded banking. Over the entire sample period, banks that switched into the retail-funded model saw their return-on-equity improve by 2.5 percentage points on average relative to non-switchers. By contrast, the relative performance of banks switching into the wholesale-funded model deteriorated by 5 percentage points on average.
JEL classification: D20, G21, L21, L25
Keywords: balance sheet characteristics, cluster analysis, discriminant analysis, model transitions, bank performance
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