CUI Lahore Repository

CREDIT DEFAULT RISK

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dc.contributor.author Ijaz, Subiyel
dc.contributor.author Ahmad, Muhammad
dc.contributor.author Qureshi, Talha Khalid
dc.date.accessioned 2020-11-26T09:30:29Z
dc.date.available 2020-11-26T09:30:29Z
dc.date.issued 219-12-17
dc.identifier.uri http://repository.cuilahore.edu.pk/xmlui/handle/123456789/1748
dc.description.abstract In this project we have developed a solution to help banking staff to analyze applicant’s data and predict how much applicant is capable of repaying the loan. We have trained a machine learning model using 5 different algorithms to predict credit default risk with 70% accuracy rate. We have also created our very own restful API which will help other developers to make similar recommender systems using our services. This will help an institute to choose better customers from which they can get most profit out and minimize the risk of loss. en_US
dc.language.iso en en_US
dc.subject Computer Science en_US
dc.title CREDIT DEFAULT RISK en_US
dc.type Thesis en_US


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