Essays about: "defaults"
Showing result 1 - 5 of 64 essays containing the word defaults.
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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. Probability of Default Machine Learning Modeling : A Stress Testing Evaluation
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : This thesis aims to assist in the development of machine learning models tailored for stress testing. The main objective is to create models that can predict loan defaults while considering the impact of macroeconomic stress. READ MORE
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3. Modeling Credit Default Swap Spreads with Transformers : A Thesis in collaboration with Handelsbanken
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the aftermath of the credit crisis in 2007, the importance of Credit Valuation Adjustment (CVA) rose in the Over The Counter (OTC) derivative pricing process. One important part of the pricing process is to determine Probability of Defaults (PDs) of the counterparty in question. READ MORE
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4. Estimation of respiratory frequency from Heart Rate Variability
University essay from Lunds universitet/Matematisk statistikAbstract : In this master's thesis the ability to estimate the respiratory frequency from heart rate variability measurement is analyzed. The goal was to implement a solution that is easily transferable to real time. 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