This paper investigates the influence the environmental conditions have on the cost-efficiency of French and Spanish banking industries. We propose a new methodology for cross-country comparisons of efficiency using a parametric approach. In particular, the specific environmental conditions of each country play an important role in the definition and specification of the common frontier of different countries. Our results suggest that, without environmental variables, the cost-efficiency scores of Spanish banks are quite low compared to those of the French banks. However, when environmental variables are included in the model, the differences between both banking industries are reduced substantially. Overall, our results demonstrate that environmental variables contribute significantly to the difference in efficiency scores between the two countries.

The recent banking crisis has revealed the existence of strong resiliency factors in the retail banking business model. On average, retail banks suffered less than other financial institutions from unexpected market changes. This paper proposes a new methodology to measure retail banks’ business risk, which is defined as the risk of adverse and unexpected changes in banks’ profits coming from sudden changes in the banks’ activities. This methodology is based on the efficiency frontier methodology, and, more specifically, on the duality property between the directional distance function and the profit function. Using the distance function to compute banks’ profitability, we take the distance to the frontier of best practices as a measure of profit inefficiency, i.e. of unexpected losses related to underperformance. In this approach, shifts in the efficiency frontier induced by adverse shocks to banks’ volumes serve as a measure of business risk. This measure of profit volatility allows a measurement to be made of the impact of volume changes on banks’ profits. This method is applied to a database containing half yearly regulatory accounting reports over the 1993–2011 period for a sample of quite all French banks running a retail banking business model. Our results verify a low level of business risk in retail banking, thus confirming the resiliency of the retail banks’ business model.

We use a one-factor credit risk model to provide new estimates of stationary default probabilities and asset correlations in two large samples of French and German Small and Medium-sized Enterprises. Results show that, on average, SMEs are riskier than large businesses; and the asset correlations in the SME population are very weak (1–3% on average) and decrease with size. On average, the relationship between PDs and asset correlations is not negative, as assumed by Basel II, but positive, especially at the industry level, in the two countries. It is also possible to distinguish different segments inside the SMEs’ population: at least between very small and small SMEs and large SMEs.

This paper is devoted to the credit risk modeling issues of small commercial loans portfolios. We propose specific solutions dealing with the most important peculiarities of these portfolios: their large size and the limited information about the financial situation of borrowers. We then compute the probability density function of futures losses and VaR measures in a portfolio of 220.000 French SMEs. We also compute marginal risk contributions in order to discuss the loan pricing issue of small commercial loans and to compare the capital requirements derived from our model with those derived from the New Ratings-Based Basel Capital Accord.

European banks hold 10% of their total assets in portfolios that give rise to unrealised gains and losses which, under Basel III, may no longer be removed from banks’ regulatory capital. Using a sample of European banks, and taking advantage of the different regulatory treatment afforded, under Basel II, to such gains and losses across jurisdictions and instruments and over time, we find evidence that: a) the inclusion of unrealised gains and losses in regulatory capital ratios increases their volatility; b) the total or partial inclusion in regulatory capital of unrealised gains and losses on fixed-income securities reduces the volume of debt at fair value, thus potentially affecting the demand for liquid long-term securities (most of which are currently government bonds); and c) the higher the proportion of gains on debt instruments allowed in regulatory capital, the higher the regulatory Tier 1 capital ratio, thus affecting banks’ capital buffer strategy.