Predictive Analytics for Lending Club
How would you analyze a major financial institution like LendingClub's dataset to train models to predict the interest rates of the loans? Case Analysis of Predictive Analytics.
Lending Club is a peer-to-peer lending platform that allows individuals and small businesses to borrow money from investors. The company was founded in 2007 and is headquartered in San Francisco, California.
LendingClub's platform uses technology to assess borrowers' creditworthiness which helps determine the interest rate on the loan. Investors can browse the available loans on the platform and choose which loans to invest in based on factors such as credit rating, loan term, and loan purpose.
The dataset has information on a sample of 100,000 loans pulled from this website (the original dataset covers monthly loan data from 2007 to 2020). Also, while the original dataset has over 140 variables, the following sample has 39 variables, of which some are obtained at the lender's registration time (i.e., also known as loan origination time), and some at the month the loan information was pulled, specified by the term "current" in the description of the variable.