
Nové metody ve schvalování úvěrů
Rychnovský, Michal ; Arlt, Josef (advisor) ; Pecáková, Iva (referee) ; Veselý, Petr (referee)
This thesis contributes to the field of applied statistics and financial modeling by analyzing mathematical models used in retail credit underwriting processes. Specifically, it has three goals. First, the thesis aims to challenge the performance criteria used by established statistical approaches and propose focusing on predictive power instead. Secondly, it compares the analytical leverage of the established and other suggested methods according to the newly proposed criteria. Third, the thesis seeks to develop and specify a new comprehensive profitabilitybased underwriting model and critically reflect on its strengths and weaknesses. In the first chapter I look into the area of probability of default modeling and argue for comparing the predictive power of the models in time rather than focusing on the random testing sample only, as typically suggested in the scholarly literature. For this purpose I use the concept of survival analysis and the Cox model in particular, and apply it to a real Czech banking data sample alongside the commonly used logistic regression model to compare the results using the Gini coefficient and lift characteristics. The Cox model performs comparably on the randomly chosen validation sample and clearly outperforms the logistic regression approach in the predictive power. In the second chapter, in the area of loss given default modeling I introduce two Coxbased models, and compare their predictive power with the standard approaches using the linear and logistic regression on a real data sample. Based on the modified coefficient of determination, the Cox model shows better predictions. Third chapter focuses on estimating the expected profit as an alternative to the risk estimation itself and building on the probability of default and loss given default models, I construct a comprehensive profitability model for fixterm retail loans underwriting. The model also incorporates various related riskadjusted revenues and costs, allowing more precise results. Moreover, I propose four measures of profitability, including the riskadjusted expected internal rate of return and return on equity and simulate the impact of the model on each of the measures. Finally, I discuss some weaknesses of these approaches and solve the problem of finding default or fraud concentrations in the portfolio. For this purpose, I introduce a new statistical measure based on a predefined expert critical default rate and compare the GUHA method with the classification tree method on a real data sample. While drawing on the comparison of different methods, this work contributes to the debates about survival analysis models used in financial modeling and profitability models used in credit underwriting.


Step by step credit risk model construction
Rychnovský, Michal ; Hanzák, Tomáš (referee) ; Charamza, Pavel (advisor)
Nazev pracc: Postnpna vyslavba modelu ohoduoconi kroditniho ri/,ika Autor: Michal Ryclmovsky Katedra: Kaledra pravdepoelobnejsti a maternal icke statistiky Vedouci bakalafske pracc: RNDr. Pavel Charam/a, CSc. Email vedouciho: pavol.charani/a''^media research.ex Abstrakt: Ciloni toto pracc je pfibli/it podstatu vvstavby skoringovych mo eleln. Popisnjeme zde metodu logisticke regrese, odhaelovani jejich paramotrn a testovani jcjicli vy/,nanmosti. Na /aklado, proiiioiniych odds ratio potoin zavadimo indei>endence model jako odhad podminone saneo s]>laceni klienta.. Tento ... dale zoljecnHJinne pfidavanini vah jedmjtlivyni sku])inani a ka tegoriini charakt.eristik klienta.. Ta.kto pficha/Jnie k WOE niodeln a jjlnemu logistickemn niodeln. Vennjeine se take nicfeni divcr/ilikacni schopnosti ino deln pomoci Lorenxovy kfivky a Somerovy d statistiky jako odhadu Giuiho koeficientn. Nakonec a])likujeine popsane nietody na praktiekon vystavbn yk(')riiigovych niodeln a na realnych dateeh porovnanie vhodnost a di\erx,ifi kacni scho])nost pi'edstavovanych niodelu. Soneast.i ])race je take vystup na. int.ernetovon encyklo]>edii \\ikiiiedia. Klicova slova: kreditni rixiko, skoringove niodely, logisticka. 1'egrese. Title: Step by step credit risk model construction Author: Michal Rychnovsky Department: Department...


Mathematical Models for LGD
Rychnovský, Michal ; Zvára, Karel (referee) ; Charamza, Pavel (advisor)
The aim of the present work is to describe possible models for LGD estimation and to test them on the real data. Besides common linear and logistic regression models we aim to describe the methods using running and censored observations  based on the Cox model and the twostep regression. This work first briefly outlines the principle of the capital requirement according to the Basel II. Then, individual methods are described and finally applied to the real banking data.


Scoring Models in Finance (Skóringové modely ve financích)
Rychnovský, Michal ; Zouhar, Jan (advisor) ; Kalčevová, Jana (referee)
The aim of the present work is to describe the application of the logistic regression model to the field of probability of default modeling, and provide a brief introduction to the scoring development process used in financial practice. We start by introducing the theoretical background of the logistic regression model; followed by a consequent derivation of three most common scoring models. Then we present a formal definition of the Gini coefficient as a diversification power measure and derive the Somerstype formulas for its estimation. Finally, the key part of this work gives an overview of the whole scoring development process illustrated on the examples of real business data.
