Kiva Project Overview
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Our objective is to understand the different factors affecting important variables of Kiva’s loans, such as the loan amount and quantity, the rate of funding of the loan, the duration of the loan term and the repayment period. Our project objective is to understand the different features of each loan, such as the sectors and activity type for the loan, the gender breakdown, how the trends differ over time and how these variables vary across different countries and regions.
Our team will attempt to use geospatial analysis to find out the how the characteristics of borrowing activities in different geographical locations differ from each other, and analyze how the different attributes of the loan vary across time for each geographical region. Geospatial analysis will allow us to build maps and make the relationships between the other attributes and geolocation data understandable and insightful. From there, we will be able to obtain more accurate trend analysis to our objectives, such as the duration of loan term and the repayment period.
There are 4 main data files we received for our exploration and analysis. The primary file we used for analysis is kiva_loans.csv, which contains the main important variables of each loan, such as:
- Funded amount of the loan
- Loan amount of the loan
- Sector which the loan is used for, such as agriculture, education
- Activity which the loan is being used to fund
- Country and Region where the loan is being used in
- Currency which the loan is being disbursed in
- Time which the loan was posted, funded and disbursed
- The term/duration of the loan in months before repayment
- Tags associated with the loan
- The repayment interval type, such as whether repayment was done weekly, monthly, irregularly or in bullet
The remaining files loan_theme_ids, loan_themes_by_region and kiva_mpi_region_locations provide secondary information. Those which are of use to us include:
- World region/continent which the country resides in
- Latitude and longitude of the region (we are using the GADM map to obtain more in-depth geographical information, and obtain a more precise latitude and longitude)
- Loan theme type of the loan
- Percentage of borrowers that are in rural areas for particular field partners
