<![CDATA[Financial technology is an industry that utilizes technology to support the financial system and the delivery of financial services more effectively and efficiently.One type of financial technology is peer-to-peer lending. To get a peer-to-peer loan, the company should collect data such as annual income, credit history, work history, and others, the companies perform screening on applications made by borrowers. The results of screening are applications that are accepted and rejected with should be done rapidly and accurately. The machine learning approach is suitable to overcome this problem and can predict the factors that influence loan approval using the feature importance. This study wants to predict the factors that influence loan approval using the Lending Club dataset. The stages of the research method used include data understanding, feature extraction, data pre-processing, exploratory data analysis (EDA), modeling, and insight. The modeling process uses the random forest algorithm because it runs efficiently on large amounts of data. The evaluation model used in the modeling process is recall with quite high result, namely 0.97. Insight obtained from all stages, there are five major determining factors, namely annual income, monthly payments of the borrower, interest rates, investor funds, and the length of work.]]>
Copyrights © 2022
