When I led Business Development and Analytics for M-Changa, a mobile payments and crowdfunding fintech startup in East Africa, I worked with the Gates Foundation to understand if we could analyze giving patterns to surmise credit worthiness. For example, if I'm a village elder ("donor") in Kenya and I've used a crowdfunding platform to support a younger community member in a time of need (wedding, funeral, healthcare cost, etc), can we understand from this transactional data that the "donor" is indeed the village elder with higher social status? The answer is...it's really really hard, but it's absolutely possible. But this research opened my eyes to the world of using non-traditional data in alternative lending.
After escaping to graduate school after leaving M-Changa, I met Brandon, current student at Harvard and Wharton, who had extra cash when he was a banker and invested into a duplex house in Los Angeles. Realizing that the millennials out there needed more opportunities to invest, and real estate is a market that is ripe for innovation, Cash on the House was born to provide opportunity to the Brandon's of the world to invest in real estate.
After escaping to graduate school after leaving M-Changa, I met Brandon, current student at Harvard and Wharton, who had extra cash when he was a banker and invested into a duplex house in Los Angeles. Realizing that the millennials out there needed more opportunities to invest, and real estate is a market that is ripe for innovation, Cash on the House was born to provide opportunity to the Brandon's of the world to invest in real estate.
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ReplyDeleteI like your story because it involves you (not just a generic set of statements about a problem) and it has a key moment -- when you had an aha moment regarding the power of mobile data to change the game with regard to credit scoring. The Brandon link is interesting, too. Would be a very good dividend on your education to be able to employ yourself and to find a team!
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