FINTECH LENDING CREDIT SCORING MODEL WITH BAYESIAN LOGISTIC REGRESSION APPROACH
FinTech Lending or Peer-to-peer Lending is a financial service provider that allows lenders and borrowers to meet online. FinTech Lending has been a solution to get easier loan application process for borrowers who do not meet the loan requirements at the Bank. Hence, a credit scoring system is n...
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| Main Author: | |
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| Format: | Final Project |
| Language: | Indonesia |
| Subjects: | |
| Online Access: | https://digilib.itb.ac.id/gdl/view/64836 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | FinTech Lending or Peer-to-peer Lending is a financial service provider that
allows lenders and borrowers to meet online. FinTech Lending has been a solution
to get easier loan application process for borrowers who do not meet the loan
requirements at the Bank. Hence, a credit scoring system is necessary to minimize
credit risk. This research is focused on building a model which can predict whether
the loan applicants will default or not. The model is expected to maintain the simple
characteristics of Fin Tech Lending. The prediction of whether the loan will default
or not is based on a Logistic Regression and Bayesian Logistic Regression model
with JO variables. ln addition to predicting loan behavior, this research aims to
view the effect of each variables to the loan behavior. The result shows no
significant difference on the performance from all the models. However, the
Bayesian Logistic Regression model with informative prior requires longer
duration to compute and perform below the Bayesian Logistic Regression model
without informative prior. |
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