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master's thesis
Korištenje regresijskih metoda u kreditnom skoringu
Zagreb: University of Zagreb, Faculty of Science, 2019. urn:nbn:hr:217:964172
Rajčić, Jana
University of Zagreb
Faculty of Science
Department of Mathematics

Institutional repository: Repository of the Faculty of Science

Cite this document

Rajčić, J. (2019). Korištenje regresijskih metoda u kreditnom skoringu (Master's thesis). Zagreb: University of Zagreb, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:217:964172

Rajčić, Jana. "Korištenje regresijskih metoda u kreditnom skoringu." Master's thesis, University of Zagreb, Faculty of Science, 2019. https://urn.nsk.hr/urn:nbn:hr:217:964172

Rajčić, Jana. "Korištenje regresijskih metoda u kreditnom skoringu." Master's thesis, University of Zagreb, Faculty of Science, 2019. https://urn.nsk.hr/urn:nbn:hr:217:964172

Rajčić, J. (2019). 'Korištenje regresijskih metoda u kreditnom skoringu', Master's thesis, University of Zagreb, Faculty of Science, accessed 03 June 2024, https://urn.nsk.hr/urn:nbn:hr:217:964172

Rajčić J. Korištenje regresijskih metoda u kreditnom skoringu [Master's thesis]. Zagreb: University of Zagreb, Faculty of Science; 2019 [cited 2024 June 03] Available at: https://urn.nsk.hr/urn:nbn:hr:217:964172

J. Rajčić, "Korištenje regresijskih metoda u kreditnom skoringu", Master's thesis, University of Zagreb, Faculty of Science, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:217:964172

Metadata
TitleKorištenje regresijskih metoda u kreditnom skoringu
AuthorJana Rajčić
MentorSiniša Slijepčević (mentor)
Committee memberSiniša Slijepčević (predsjednik povjerenstva)
Committee memberMiljenko Huzak (član povjerenstva)
Committee memberVanja Wagner (član povjerenstva)
Committee memberBojan Basrak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Science
(Department of Mathematics)
Zagreb
Defense date and country2019-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Cilj ovog rada je bio upoznati se sa linearnom regresijom, te kako korištenjem regresijskih modela možemo odrediti klijentovu vjerojatnost otplaćivanja obveze na temelju prijašnjih podnositelja zahtjeva. Glavna pitanja su bila koliko bi trebao biti veliki uzorak s kojim radimo i kako uopće treba izgledati podjela na „dobre“ i „loše“ klijente, odnosno kako glasi definicija „dobrih“ i „loših“ klijenata, te je bilo potrebno odrediti razumnu povijest otplate. U radu smo spomenule neke od statističkih metoda za izgradnju kreditne bodovne kartice. Zaključak rada je da bez obzira koju definiciju „dobrih“, odnosno „loših“ odaberemo, ne postoji učinak na metodologiju kreditne bodovne kartice jer se ona zapravo razvija na temelju definicija.
Abstract (english)
The aim of this work was to introduce the notion of linear regression, and explain how one can, by using regression models, determine the probability of a customer to pay off an obligation, based on behavior of previous applicants. The main questions were on how large the sample for analysis should be, and how we should divide data into "good" and "bad" clients, i.e. what does the definition of "good" and "bad" clients looks like, and it was necessary to determine a reasonable history of repayment. In the thesis we mentioned some of the statistical methods for building credit score cards. The conclusion of the work is that no matter what definition of "good" or "bad" we choose, there is no effect on the methodology of credit score cards because it actually develops on the basis of definitions.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:217:964172
Study programmeTitle: Finance and Business Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-02-18 12:46:06