European banks’ business models as a driver of strategic planning: one size fits all

Purpose This paper aims to verify the presence of a management model that confirms or not the one size fits all hypothesis expressed in terms of risk-return. This study will test the existence of stickiness phenomena and discuss the relevance of business model analysis integration with the risk assessment process. Design/methodology/approach The sample consists of 60 credit institutions operating in Europe for 20 years of observations. This study proposes a classification of banks’ business models (BMs) based on an agglomerative hierarchical clustering algorithm analyzing their performance according to risk and return dimensions. To confirm BM stickiness, the authors verify the tendency and frequency with which a bank migrates to other BMs after exogenous events. Findings The results show that it is impossible to define a single model that responds to the one size fits all logic, and there is a tendency to adapt the BM to exogenous factors. In this context, there is a propensity for smaller- and medium-sized institutions to change their BM more frequently than larger institutions. Practical implications Quantitative metrics seem to be only able to represent partially the intrinsic dynamics of BMs, and to include these metrics, it is necessary to resort to a holistic view of the BM. Originality/value This paper provides evidence that BMs’ stickiness indicated in the literature seems to weaken in conjunction with extraordinary events that can undermine institutions’ margins

The impact of ECB loan valuation metrics on third-party loan pricing: A EU firm perspective

This paper delves into the implications for the bank behaviour about firm loan pricing conditions of the new direction undertaken by supervisory and regulatory authorities in the aftermath of the deterioration of the loan portfolio quality that hit EU banks. The 2014 AQR exercise embraces the new direction and extensively uses debt service coverage measures to assess a firm’s loan quality. We, therefore, check whether the DSCR has influenced debt pricing conditions by analysing a panel of 655 listed EU firms from 2009 to 2017. Our findings show that Z-score is unable to discriminate between high and low credit risk firms. The DSCR becomes significant only after 2014, highlighting the incremented importance of this ratio in the bank’s loan pricing determination. Our work contributes to the literature investigating third-party interdependencies with the interplay between lender-borrower relationship and loan pricing and further extends the literature on creditworthiness metrics beyond their mere default-prediction ability (Beaver, 1966; Houghton & Woodliff, 1987). Our results highlight the relevance of the DSCR in the bank’s loan pricing determination and inform firm managers about the drivers that influence the cost of debt thereby enhancing their operational and financial planning

A revision of Altman’s Z- Score for SMEs: suggestions from the Italian Bankruptcy Law and pandemic perspectives

As the pandemic urged further investigations on the prediction of firms’ financial distress, this study develops and tests an alternative measure to the alert system elaborated by the NCCAAE which combines the benefits of the Z-score’s multivariate discriminant model with the background employed to develop the NCCAAE’ predictors. Using a sample of 43 viable and 43 non-viable Italian SMEs, we first compare the financial distress predictive accuracy of the NCCAAE’s alert system to that of the traditional Z-score over the period 2015-2019. On the basis of the results, we elaborate and compare the revised versions of both approaches which align the traditional Z-score to the current socio-economic conditions and provide an alternative measure to the NCCAAE’s alert system which embeds a Z-score calculated using the ratios elaborated by the NCCAAE for the alert system. The analysis of the two baseline approaches showed complementary results as the Z-score overperformed the alert system when predicting the status of non-viable firms whereas the opposite emerged as regards viable firms. The revised version of both approaches pointed out an enhanced predictive accuracy with respect to baseline models. In particular, the complementary role of the Z-score has been integrated into the new alert system as major contribute to its enhancement which pointed it out as the best measure employed. We, therefore, contribute to the literature studying the financial distress prediction developments by elaborating an alternative measure to the alert system developed by the NCCAAE which combines the benefits of the Z-score’s multivariate discriminant function with the background employed to develop the NCCAAE’ predictors. Our analysis enriches the post-pandemic debate on refined financial distressed prediction methods by pointing out the limits of the alert system as designed by the NCCAAE and suggests an alternative and better performing measure that may be used by third-party bodies to predict financial distress

Economic Performance and Value Creation in the Lending Activities of Italian Banking Groups

performance, value creation, banking group, economic value added, G21, G32,