Essays about: "Credit scoring models"
Showing result 1 - 5 of 17 essays containing the words Credit scoring models.
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1. The Power of Credit Scoring: Evaluating Machine Learning and Traditional Models in Swedish Retail Banking
University essay from Göteborgs universitet/Graduate SchoolAbstract : In this paper, we investigate and compare different credit scoring models, with special attention paid to machine learning approaches outperforming traditional models. We explore a recently proposed method called the PLTR model, which is a combination of machine learning and traditional logistic regression. READ MORE
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2. Explainable Artificial Intelligence and its Applications in Behavioural Credit Scoring
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Credit scoring is critical for banks to evaluate new loan applications and monitor existing customers. Machine learning has been extensively researched for this case; however, the adoption of machine learning methods is minimal in financial risk management. READ MORE
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3. Credit Scoring Based on Behavioural Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Credit modelling has traditionally been done by credit institutes based on financial data about the individuals requesting the credit. While this has been sufficient in lowering risk in developed economies with plenty of financial data it is inefficient in developing economies and fails to reach the unbanked population. READ MORE
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4. Deep Learning Approach for Time- to-Event Modeling of Credit Risk
University essay from KTH/Matematisk statistikAbstract : This thesis explores how survival analysis models performs for default risk prediction of small-to-medium sized enterprises (SME) and investigates when survival analysis models are preferable to use. This is examined by comparing the performance of three deep learning models in a survival analysis setting, a traditional survival analysis model Cox Proportional Hazards, and a traditional credit risk model logistic regression. READ MORE
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5. Credit Scoring using Machine Learning Approaches
University essay from Mälardalens universitet/Akademin för utbildning, kultur och kommunikationAbstract : This project will explore machine learning approaches that are used in creditscoring. In this study we consider consumer credit scoring instead of corporatecredit scoring and our focus is on methods that are currently used in practiceby banks such as logistic regression and decision trees and also compare theirperformance against machine learning approaches such as support vector machines (SVM), neural networks and random forests. READ MORE
