Essays about: "Credit Risk Scorecard"

Found 4 essays containing the words Credit Risk Scorecard.

  1. 1. The value of detailed product information in credit risk prediction : A case study applied to Klarna’s Pay Later orders in Sweden

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Mimmi Andersson; Louise von Sydow Yllenius; [2022]
    Keywords : Credit Risk Management; Consumer Credit; BNPL; Credit Scoring; Alternative Data; Product Category; Product Type; Responsible Lending; e-commerce; Kreditriskbedömning; BNPL; konsumenkredit; alternativ data; produktkategori; produkttyp; hållbar kreditgivning; onlinehandel;

    Abstract : In this study we propose to enhance the predictive power of a Buy Now, Pay Later (BNPL) consumer credit scorecard by leveraging detailed product information. The object of analys is in this study is Klarna Bank AB, which is the largest retail finance provider in Sweden. READ MORE

  3. 2. Prediction of Credit Risk using Machine Learning Models

    University essay from Uppsala universitet/Signaler och system

    Author : Philip Isaac; [2022]
    Keywords : Credit Risk; Credit Risk Scorecard; Machine Learning; Artificial Intelligence; AI; Logistic Regression; eXtreme Gradient Boosting; ROC-AUC; Binning; Cross-Validation; Correlation;

    Abstract : This thesis aims to investigate different machine learning (ML) models and their performance to find the best performing model to predict credit risk at a specific company. Since granting credit to corporate customers is a part of this company's core business, managing the credit risk is of high importance. READ MORE

  4. 3. High-risk Consumer Credit Scoring using Machine Learning Classification

    University essay from Lunds universitet/Matematisk statistik

    Author : Max Mjörnell; Ludvig Levay; [2019]
    Keywords : Machine learning; Scorecard modelling; Logistic regression; Support Vector Machine; Decision Tree; Random Forest; k-Nearest Neighbors; Artificial Neural Network; Voting ensemble; SHAP; LIME; Average Precision score; Feature engineering; Mathematics and Statistics;

    Abstract : The use of statistical models in credit rating and application scorecard modelling is a thoroughly explored field within the financial sector and a central component in a credit institution’s underlying business model. The aim of this report was to apply and compare six different machine learning models in predicting credit defaults for high-risk consumer credits, using a data set provided by a Swedish consumer credit institute. READ MORE

  5. 4. Reject Inference in Online Purchases

    University essay from KTH/Matematisk statistik

    Author : Lennart Mumm; [2012]
    Keywords : ;

    Abstract : Abstract   As accurately as possible, creditors wish to determine if a potential debtor will repay the borrowed sum. To achieve this mathematical models known as credit scorecards quantifying the risk of default are used. READ MORE