02842ntm a22005057i 4500 000610694 CZ-PrVSE 20190915095738.0 m d cr n|||||||||| 190915s2019 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Houšková, Helena ISIS:107209 dis Modely pravděpodobností odchodu klientů finančních institucí eng Models of Churn Probabilities of Clients of Financial Institutions / Helena Houšková 2019 ?? stran : digital, PDF soubor Vedoucí práce: Michal Černý Diplomová práce (Ing.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2019 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2019 The aim of this thesis is to create models that will predict the probability of client churn during mortgage refixation from a year to six months in advance using three different methods. Separate models are made for the clients who applied for the loan directly in the bank and for those that applied through a broker. The reason is different churn rate in these two groups as well as possibility tu use additional variables for the second group of clients. The used methods are logistic regression, regression tree and random forest. Models are compared with each other as well as with the model that is currently used in the bank. To compare the models the Gini coefficient and the confusion matrix are used. For both groups of clients, the best model is the random forest, which has the highest Gini coefficient on the test sample. Způsob přístupu: Internet ekonometrie a operační výzkum [obor dipl. práce] diplomové práce fd132022 czenas master's theses eczenas client churn probability regression tree logistic regression random forest Černý, Michal mzk2005275013 ths Formánek, Tomáš ISIS:46723 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/68019/podrobnosti VŠKP v InSIS https://aleph.vse.cz/neverejny_soubor_prace.pdf Hlavní práce https://insis.vse.cz/zp/68019/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/68019/posudek/oponent/63839 Oponentura https://insis.vse.cz/zp/68019/podrobnosti dc:identifier NEPOSILAT VSKP vse68019 190911 68019