Add to ORKGIn this thesis, peer-to-peer lending is explored and analyzed with the objective of fitting a model to accurately predict if borrowers default on their loans or not. The foundation for the thesis is a dataset from LendingClub, a peer-to-peer lending platform based in San Francisco, USA. Detailed information of borrowers’ financial history, personal characteristics and the specifics of each loan is used to predict the probability of default for the various loans in the portfolio. Methods used include elastic net regularization of logistic regression, boosting of decision trees, and bagging with random forests. The results are compared using accuracy metrics and a profitability measure, before a final model selection is carried out.Masteroppg...
In this thesis, we provide a method for lenders to reduce defaults on consumer loans in the Norwegia...
The emergence of P2P(Peer-to-peer) lending has opened up a popular way for micro-finance, and the fi...
This paper presents the Conditional Probability of Default (CoPoD) methodology for modelling the pro...
In this thesis, peer-to-peer lending is explored and analyzed with the objective of fitting a model ...
The ability of financial institutions to detect whether a customer will default on their credit card...
Masters Degree. University of KwaZulu-Natal, Durban.Loan lending has become crucial for both individ...
Credit-lending companies have resorted to the use of Machine Learning algorithms in the recent past ...
In the United States, stagnant interest rates, bank skepticism after the financial crisis and the ri...
Despite recent developments financial inclusion remains a large issue for the World's unbanked popul...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep ...
Estimating default risk has been a major challenge in credit-risk analysis. Financial institutions a...
This thesis has explored the field of internally developed models for measuring the probability of d...
This study aims to explore the possibility of a financial entity to produce a predicted model of def...
In this thesis, we provide a method for lenders to reduce defaults on consumer loans in the Norwegia...
The emergence of P2P(Peer-to-peer) lending has opened up a popular way for micro-finance, and the fi...
This paper presents the Conditional Probability of Default (CoPoD) methodology for modelling the pro...
In this thesis, peer-to-peer lending is explored and analyzed with the objective of fitting a model ...
The ability of financial institutions to detect whether a customer will default on their credit card...
Masters Degree. University of KwaZulu-Natal, Durban.Loan lending has become crucial for both individ...
Credit-lending companies have resorted to the use of Machine Learning algorithms in the recent past ...
In the United States, stagnant interest rates, bank skepticism after the financial crisis and the ri...
Despite recent developments financial inclusion remains a large issue for the World's unbanked popul...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
Logistic regression (LR) and support vector machine algorithms, together with linear and nonlinear d...
Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep ...
Estimating default risk has been a major challenge in credit-risk analysis. Financial institutions a...
This thesis has explored the field of internally developed models for measuring the probability of d...
This study aims to explore the possibility of a financial entity to produce a predicted model of def...
In this thesis, we provide a method for lenders to reduce defaults on consumer loans in the Norwegia...
The emergence of P2P(Peer-to-peer) lending has opened up a popular way for micro-finance, and the fi...
This paper presents the Conditional Probability of Default (CoPoD) methodology for modelling the pro...