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dc.contributor.advisorKondova, Galia
dc.contributor.authorMerker, Samuel
dc.contributor.authorGäumann, Alexander
dc.contributor.otherFirma: Anavant| Kontakt: Roland Hänni| PLZ/ Ort: Zürich
dc.date.accessioned2015-09-02T07:33:48Z
dc.date.available2015-09-02T07:33:48Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/11654/4871
dc.description.abstractThis paper analyzes Swiss banks on their efficiency by using a non-parametric method called Data Envelopment Analysis (DEA). Doing so, the research team was also interested in having an understanding of the impact of the banks' efficiency triggered by the financial crisis in 2007. (Beitrag ist nur für FHNW Mitarbeitende sichtbar)
dc.language.isoen_UK
dc.accessRightsAnonymous
dc.subjectData Envelopment Analysis (DEA)
dc.subjectEfficiency
dc.subjectIntermediation approach
dc.subjectProduction approach
dc.subjectFuture value drivers
dc.subjectCantonal Banks
dc.subjectNeue Aargauer Bank
dc.subject.ddc658 - General Management
dc.subject.ddc330 - Wirtschaft
dc.titleSwiss Banks' Efficiency and future Value Drivers
dc.type11 - Studentische Arbeit
dc.audienceSonstige
fhnw.StudentsWorkTypeBachelor
fhnw.publicationStateUnveröffentlicht
fhnw.ReviewTypeKein Peer Review
fhnw.InventedHereYes
fhnw.ConfidentLevelStaff
fhnw.leadThis paper analyzes Swiss banks on their efficiency by using a non-parametric method called Data Envelopment Analysis (DEA). Doing so, the research team was also interested in having an understanding of the impact of the banks' efficiency triggered by the financial crisis in 2007.
fhnw.initialPositionSince the financial crisis in 2007, many banks have experienced decreasing margins and are therefore eager to use their valuable inputs in the most efficient way. In order to anaylze efficiency, the research team spent time reading annual reports and picking out relevant data. Additionally, for understanding the method used, the authors researched the internet and literature for explanations. Once theory was understood and all data was gathered, the research team began interpreting the results.
fhnw.procedureThe research team had to gather all relevant data, therefore annual reports of banks in the sample were read. Meanwhile, theories in the field of DEA were considered as well as former works in the field. After a first efficiency analysis, all people involved in the paper agreed on separating the timeframe in two periods, namely one before the crisis and one after the crisis. This step helped avoiding distortions due to the crisis. Also banks were classified in groups according to their asset size. So, banks of same size were comapred with each others.
fhnw.resultsThe paper helps the Neue Aargauer Bank to see how they performed in terms of efficiency compared to their peers. Furthermore, it shall assist decision makers in their choices for improving efficiency within the organization. The analysis showed that banks were generally more efficient before the crisis and that small banks (measured by mean total assets) perform better than big organizations. The research team also noticed discrepancies between both approaches used, one scoring higher efficiency rates than the other. Comparing banks within groups, it was surprising to see that bigger banks have higher average scores than groups with small institutions. Furthermore, it has enabled the research team to draw some hypothesises, which are based on comparisons of DEA scores and the relevant data in annual reports.
fhnw.IsStudentsWorkYes


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