Enhancing credit risk assessment models: insights from Scania Finance Korea's truck financing model

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School of Business | Bachelor's thesis
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Authors

Date

2024

Department

Mikkelin kampus

Major/Subject

Mcode

Degree programme

(Mikkeli) Bachelor’s Program in International Business

Language

en

Pages

32+11

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Abstract

This thesis presents a comprehensive examination of the factors used in the credit rating model employed by Scania Finance Korea, focusing on its application in the truck financing sector. The study identifies key variables that significantly influence creditworthiness. Utilizing linear regression and bootstrapped regression techniques, this thesis assesses the predictive capabilities of the factors. The findings highlight the importance of non-financial variables and the need for refining credit risk assessment methods to enhance their predictive accuracy and reliability.

Tämä tutkielma tarjoaa kattavan tarkastelun tekijöistä, joita käytetään Scania Finance Korean luottoluokitusmallissa, keskittyen sen soveltamiseen kuormaautorahoituksessa. Tutkimus tunnistaa keskeiset muuttujat, jotka vaikuttavat merkittävästi luottokelpoisuuteen. Käyttäen lineaarista regressiota ja bootstrap-regressiomenetelmiä, tämä tutkielma arvioi tekijöiden ennustekykyä. Löydökset korostavat ei-taloudellisten muuttujien tarvetta ja tarvetta tarkentaa luottoriskien arviointimenetelmiä niiden ennustetarkkuuden ja luotettavuuden parantamiseksi.

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Thesis advisor

Pham, Linh

Keywords

truck financing, factors in credit rating models, default, credit rating model

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Citation

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202405263586

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[kand] Kauppakorkeakoulu / BIZ