Modeling car loan prepayment using supervised machine learning | Zendy

Sara Zahi | Zendy; Boujemâa Achchab | Zendy

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Modeling car loan prepayment using supervised machine learning

Author(s) -

Sara Zahi,

Boujemâa Achchab

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.03.055

Subject(s) - computer science , categorical variable , prepayment of loan , machine learning , multinomial logistic regression , loan , logistic regression , artificial intelligence , multinomial distribution , supervised learning , variable (mathematics) , binomial regression , econometrics , finance , mathematics , mathematical analysis , artificial neural network , economics

Logistic regression is a widely used machine-learning model for predicting categorical outcomes. It uses a number of explanatory variables to predict the values of the target variable that can be either binomial or multinomial. It is used in a number of fields such as cancer detection problems, risk modeling and any subject that requires computing the probability of an event occurrence. In this paper, we propose to apply this supervised machine-learning model to study prepayment risk and its determinants concerning car loans based on a number of characteristics.

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