In the last years since 2007 the financial sector and especially the banking sector have often been the target for criticism. In 2013 the European Parliament passed the law for the further implementation of the Single Supervisory Mechanism (SSM) 1 . The aim of the SSM is to centralize the different national banking supervision in the body of the European Central Bank (ECB). In the course of the introduction of the SSM the ECB started the so called Asset Quality Review (AQR) in the fall of 2013 (see ). During the AQR the balance sheets of the 130 system-relevant banks in the Eurozone were audited and evaluated by their ability to survive economic shocks. The results were published on the 26th of october 2014. The main target for banking regulation has been the ratio of equity to riskweigthed assets. In this paper we introduced the definition of systemic banking performance by adding measures for the banks performance as financial intermediaries. We thought exclusively assessing the banks by their sustainability is not sufficient to guarantee an efficient working banking industry. We were looking for indicators from the banks balance sheet that are suitable to reflect the banks achievements in serving the economy. Therefore we used a panel of 70 European banks over 10 years, that were rated significant by the ECB and are under SSM-regulation (see ). We used a nonparametric approach (Data Envelopment Analysis) to track efficiency scores over 10 consecutive years. We used a slack based model together with the concept of super-efficiency to get highly discriminable efficiency scores. For the analysis of the efficiency growth we used the concept of the Malmquist index for DEA models. Further analyses regarding the sensibility of the efficiency score to changes in the input factors and composition of the sample were made to get a more detailed look on the bahaviour of the efficiency scores. A special focus was to see to what extent the financial crisis shows in the data. First we studied the data using descriptive statistics to illustrate the development in the banking sector over the years. Then we used panel regression models to try to identify which strategic variables are the determinants for banking efficiency in Europe. Due to the particular nature of DEA efficiency scores we used a robust covariance estimator, proposed by Driscoll and Kraay, for interference. To get stable results extreme bound analysis (Leamer) was implemented. This study was conducted during the project "Banking Performance in Euroland. Efficiency and the Impact of Strategic Variables: 2003-2012" at the Vienna University of Technology. The project was funded by the Jubiläumsfonds of the Austrian National Bank, Project nr 15495.