Difference between revisions of "ANLY482 AY2017-18 T2 Group 22"

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Kiva is an online crowdfunding platform which extends financial services in the form of loans to the poor and financially excluded people around the world, who are otherwise unable to raise funds from financial institutions and banks given their financial capacity and background. Since its inception, Kiva lenders have provided over $1 billion USD in loans to over 2 million people. In order to set investment priorities and better inform lenders, Kiva wishes to better understand the demographics of its borrowers and their poverty levels.
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Kiva is an online crowdfunding platform which extends financial services in the form of loans to the poor and financially excluded people around the world, who are otherwise unable to raise funds from financial institutions and banks given their financial capacity and background. Since its inception, Kiva lenders have provided over $1 billion USD in loans to over 2 million people.  
  
 
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As the bulk of loan records are from the Philippines, this project covers the use of geospatial analysis and statistical techniques, specifically Kernel Density Analysis and Exploratory Spatial Data Analytics techniques aimed at studying how geographical locations affect the presence and concentration of loans, and how loans are dispersed across geography based on different industry sectors, and how the spatial patterns differ across the different cities and municipalities within the Visayas.
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Revision as of 16:25, 15 April 2018



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ANLY482 Main Page


Company Background
Kivalogo.png

Kiva is an online crowdfunding platform which extends financial services in the form of loans to the poor and financially excluded people around the world, who are otherwise unable to raise funds from financial institutions and banks given their financial capacity and background. Since its inception, Kiva lenders have provided over $1 billion USD in loans to over 2 million people.

Objectives
Kivalogo.png

As the bulk of loan records are from the Philippines, this project covers the use of geospatial analysis and statistical techniques, specifically Kernel Density Analysis and Exploratory Spatial Data Analytics techniques aimed at studying how geographical locations affect the presence and concentration of loans, and how loans are dispersed across geography based on different industry sectors, and how the spatial patterns differ across the different cities and municipalities within the Visayas.