Earlier this month I posted an analysis of which countries most need Kiva.org’s microfinance services (based on their poverty rates) and which countries are getting them (based on Kiva’s actual lending data). This analysis provides an opportunity to update my ranking of Kiva in-country microfinance banking institutions from last fall, to include “relative need”. Read more
Mapping meets microlending, two of my favorite topics! Having previously ranked the quality of Kiva microloan partners (and now, for several months, having used the rankings to steer my own loans), I thought I would do some quick and dirty visualization of the results. As a bonus I’ve churned out some visualizations of worldwide Kiva lending, poverty rates, and the relative penetration of Kiva into the neediest countries in the world. Read more
This entry is a bit overdue; at the time of our nomadic homestay trip to Mongolia in 2009, NASA was just beginning a period of significant “disruption”, and I never found the time upon return to write or post about it. However, it was one of the most transformative trips of my life. I hope in this post I can capture in some small way the incredible beauty of both the landscape and the people of Mongolia.
First, a few words from “Badger” Byambatogtoh, the cutest kid in Bulgan Aimag:
Earlier this year (and a little behind the times) I got turned on to Kiva.org, the “social clearinghouse” for matching pools of small ($25 a pop) lenders with individual borrowers in developing countries. Kiva’s process of pairing lenders with borrowers is described here. Kiva fills a critical niche in breaking the lending process down into bite size chunks for lenders, screening and qualifying “in-country” partners (the actual lending institutions, to whom Kiva’s members effectively provide collateral). I have been wanting a way to help identify the most “solid” of the in-country partners to lend with; in the “study” shared here, I have scraped a large amount of microfinance institution performance data and combined them into figures of merit, to attempt to somewhat objectively rank the Kiva partners.