KTH Matematik  

Matematisk Statistik

Tid: 13 december 2017 kl 10.00-11.00.

Seminarierummet F11, Lindstedtsvägen 22, plan 2, F-huset, KTH. Karta!

Föredragshållare: Felix Molin

Title: Cluster analysis of European banking data

Abstract: Credit institutions constitute a central part of life as it is today and has been doing so for a long time. A fault within the banking system can cause a tremendous amount of damage to individuals as well as countries. A recent and memorable fault is the global fiinancial crisis 2007-2009. It has affected millions of people in dierent ways ever since it struck. What caused it is a complex issue which cannot be answered easily. But what has been done to prevent something similar to occur once again? How has the business models of the credit institutions changed since the crisis? Cluster analysis is used in this thesis to address these questions. Banking-data were processed with Calinski-Harabasz Criterion and Ward's method and this resulted in two clusters being found. A cluster is a collection of observations that have similar characteristics or business model in this case. The business models that the clusters represents are universal banking with a retail focus and universal banking with a wholesale focus. These business models have been analyzed over time (2007-2016), which revealed that the credit institutions have developed in a healthy direction. Thus, credit institutions were more financially reliable in 2016 compared to 2007. According to trends in the data this development is likely to continue.

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Sidansvarig: Filip Lindskog
Uppdaterad: 25/02-2009