Understanding Kiva Loan Defaults

STA 440 - Case Studies

By Aidan Gildea, Belle Xu, Isabella Swigart, and Rob Wilds in Data Science Data Analysis Survival Analysis

January 30, 2023

About

As part of the course STA 440: Case Studies, we explored the relationship between and geographic factors and both the risk of default and time to default, as well as predicting the probability of default using Kiva loan data from 2005 to 2012. By constructing both logistic regression and parametric accelerated failure time models, we provided concrete recommendations to prospective Kiva lenders on how to identify loans with lower risk of default and longer times to default.

You can view the project code on Github.

Posted on:
January 30, 2023
Length:
1 minute read, 86 words
Categories:
Data Science Data Analysis Survival Analysis
Tags:
hugo-site
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