Financial Performance Analysis of European Banks using a Fuzzified Self-Organizing Map

Due to the recent wave of bank failures, stress tests have been conducted on banks within the European Union. The stress tests, however, only consider the adequacy of a bank’s capital ratios, whereas the general financial performance of individual banks is disregarded. In this paper, we use the Self-Organizing Map (SOM) to perform a visual multidimensional and temporal financial performance analysis of European banks. Weaddress several problems concerning financial performance analysis. We deal with the problem of selecting suitable financial ratios by performing dimensionality reduction using PCA. We also deal with difficult data using outlier trimming and normalization techniques, and use the SOM for imputing missing values. Weuseadecision-framework forchoosing thefinalmodel, based upon asetof mapand clustering qualitymeasures. Inaddition, weimplement a second-level fuzzified Wardclustering for visualization purposes and for assessing the crispness of thesolution. The result is a visual SOM model for financial performance analysis of European banks. Due to the recent wave of bank failures, stress tests have been conducted on banks within the European Union. The stress tests, however, only consider the adequacy of a bank’s capital ratios, whereas the general financial performance of individual banks is disregarded. In this paper, we use the Self-Organizing Map (SOM) to perform a visual multidimensional and temporal financial performance analysis of European banks. Weaddress several problems concerning financial performance analysis. We deal with the problem of selecting suitable financial ratios by performing dimensionality reduction using PCA. We also deal with difficult data using outlier trimming and normalization techniques, and use the SOM for imputing missing values. Weuseadecision-framework forchoosing thefinalmodel, based upon asetof mapand clustering qualitymeasures. Inaddition, weimplement a second-level fuzzified Wardclustering for visualization purposes and for assessing the crispness of thesolution. The result is a visual SOM model for financial performance analysis of European banks.