Essays about: "banking credit"
Showing result 1 - 5 of 124 essays containing the words banking credit.
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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. Credit Card Fraud Detection by Nearest Neighbor Algorithms
University essay from Göteborgs universitet/Institutionen för matematiska vetenskaperAbstract : As the usage of internet banking and online purchases have increased dramatically in today’s world, the risk of fraudulent activities and the number of fraud cases are increasing day by day. The most frequent type of bank fraud in recent years is credit card fraud which leads to huge financial losses on a global level. READ MORE
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3. Increasing explainability of neural network based retail credit risk models
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Due to their ’black box’ nature, Artificial Neural Networks (ANN) are not permitted for use in various applications. One such application is mortgage credit risk modeling. READ MORE
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4. Moral Hazard and Banking Risk, a Euro Area Analysis
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : The study investigates the effects of capital regulations on risk-taking within the Euro- zone banking sector from 2013 to 2019, specifically focusing on the impact of moral hazard stemming from bank charter value and ownership influence. Previous research suggests both bank charters and ownership influence can prompt different risk behaviours and po- tentially influence the effectiveness of capital regulations. READ MORE
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5. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. READ MORE