Credit Risk Models Using Machine Learning Models

Loading...
Thumbnail Image

Date

2018

Journal Title

Journal ISSN

Volume Title

Publisher

MEF Üniversitesi, Fen Bilimleri Enstitüsü

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Journal Issue

Abstract

Credit scoring is an important subject in financial institutions, mainly in banks. I want to examine some machine learning techniques to find out a model that performs good in predicting or classifying the loaner person a good credit or a bad one by evaluating his/her demographic features as marital status, wealth, job seniority, monthly income and expenses.

Description

Keywords

Credit Ranking, Credit Scoring Models, Machine Learning, Support Vector Machine, Decision Tree Model, Linear Discrimant Analysis, Loan-to-Value Ration, Saving Capacity, Logistic Regression Model

Turkish CoHE Thesis Center URL

Fields of Science

Citation

Akman, Ö. (2018). Credit risk models using machine learning models, MEF Üniversitesi Fen Bilimleri Enstitüsü, İstanbul, Türkiye

WoS Q

Scopus Q

Source

Volume

Issue

Start Page

End Page

Page Views

189

checked on Dec 06, 2025

Downloads

213

checked on Dec 06, 2025

Google Scholar Logo
Google Scholar™

Sustainable Development Goals

SDG data is not available