Web21 de jan. de 2011 · This filter is the easiest way to improve your ROI and so it is the first and most important filter. Loan Size < $20,000. This one is self-explanatory. We filter out all loans of $20,000 or more. This makes logical sense because the higher the loan, the higher the payment and presumably the more difficult it is to pay back. Open Credit Lines >= 5 Web24 de out. de 2014 · My Lending Club filter (higher risk loans) Lending Club grades: E, F, & G Goal: 10-11% ROI See this filter on NSR. Filter criteria: Inquiries: 0; Annual …
Updated: Super Simple High Return Filter Strategies For Lending …
WebSee the open credit lines section before for more on this, but this is to catch people who quickly open and close credit lines. There can be legitimate reasons for this being high, especially since accounts stay on the report for 7 years + 180 days (delinquent and collected accounts) or 10 years (accounts closed in good standing), but too many credit lines on … WebRelated to open credit. Open-end credit means credit extended by a creditor under an agreement in which:. Company Credit Facility means the Credit Agreement, dated as of … emily bibby
LendingClub/Data-Cleaning.md at master · elsalmi/LendingClub
WebProsper is America's first marketplace lending platform. Get a personal loan at a low rate. Prosper is America's ... Create a custom filter set to find loans you want to invest in. Select up to 10 individual listings to place as a one-time ... Open Credit Lines . 0 10+ 0 10+ Total Credit Lines . 0 10+ 0 10+ Revolving Credit Balance . $0 $10000 ... WebLending Club purely focuses on borrowers with high creditworthiness. By far, the largest amount of loans are given to borrowers with employments lengths of 10+ years, which would indicate a more predictable borrower and fall in line with Lending Club’s policy. Lending Club assigns a loan grade to each loan for investors to know the quality of ... Web6 de dez. de 2024 · Successfully designed and validated a logistic regression model with a precision of 98% and 89% accuracy on the Lending Club dataset to predict “Loan-Status”, and successfully classified a potential credit loan borrower into fully paid or charged-off. - GitHub - abbeycite/Credit-Loan-Risk-Management-Analysis-with-Logistic-Regression.: dr abby loch