Primjena linearne regresije i strojnog učenja u izradi kreditnog skoringa u bankarstvu

master's thesis

• Title (english): Application of linear regression and machine learning in credit scoring in banking
• Author: Marko Gavrić
• Mentor: Siniša Slijepčević (mentor)
• Committee member: Siniša Slijepčević (predsjednik povjerenstva)
• Committee member: Miljenko Marušić (član povjerenstva)
• Committee member: Hrvoje Planinić (član povjerenstva)
• Committee member: Vjekoslav Kovač (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2023-07-14, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics

Abstract

Ovaj diplomski rad proučava problematiku izračuna kreditnog skoringa pomoću prediktivnih modela strojnog učenja. U početku uvodimo osnovne koncepte vjerojatnosti i statistike nužne za daljnje razumijevanje rada. U nastavku rada upoznajemo prediktivne modele, poput jednostavnih regresijskih modele i kompleksnijih modela strojnog učenja. Za kraj rada pokazujemo primjenu navedenih modela u bankarstvu, točnije pri izračunu kreditne sposobnosti klijenta, te navodimo primjer iz prakse u kojem se proučava prediktivna moć transakcijskih podataka tekućeg računa za izračun kreditnog rizika.

Abstract (english)

This thesis examines the issue of credit scoring calculation using predictive models in machine learning. We begin by introducing the basic concepts of probability and statistics, which are necessary for further understanding of the thesis. In the subsequent sections, we explore predictive models such as simple regression models and more complex machine learning models. Finally, we demonstrate the application of these models in the banking sector, specifically in assessing a client’s creditworthiness. We also provide a practical example where the predictive power of transactional data from a current account is studied for credit risk calculation.

• Keywords: vjerojatnost; statistika; ediktivni modeli; jednostavni regresijski modeli; modeli strojnog učenja; kreditna sposobnost klijenta
• Language: croatian
• URN:NBN: urn:nbn:hr:217:996528
• Study programme: Title: Mathematical Statistics; Study programme type: university; Study level: graduate; Academic / professional title: sveučilišni magistar matematike (sveučilišni magistar matematike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Embargoed access; Embargo expiration date: 2024-07-15
• Created on: 2024-02-09 10:56:57