Machine learning is an exciting technology with plenty of potential applications in social impact business. But as Jacob Winiecki at BFA points out, the hype around the approach may make it tempting to jump in without first determining if it's the right tool for the job. He offers a clear run-down of how machine learning actually works in practice, along with three concrete steps for how a PAYGo enterprise can implement the technology, based on the work BFA’s FIBR Project has done with ZOLA, a leading PAYGo solar operator in Africa.
High-tech innovations like artificial intelligence, automation and the cloud are dramatically changing the nature of work. Some believe these changes will lead to massive job losses, while others imagine a future with plentiful and satisfying careers in industries we’ve yet to imagine. MIT’s Solve initiative is looking for solutions that ensure that no one is left behind by technology. Hala Hanna encourages innovators and entrepreneurs to enter Solve’s Work of the Future Challenge, which is open until July 1.
Catalyst Fund – a unique accelerator model that provides direct and tailored technical assistance to complement a startup’s skill sets – spent the past year working directly with early-stage fintech businesses in emerging markets. Here are some of the lessons they gathered, both on the tech side and the customer side. A key takeaway: Trust is slowly built but easily destroyed.
Investment in predictive algorithms for credit scoring is a no-brainer for sophisticated digital financial service providers. Brick-and-mortar financial institutions that are just beginning to explore technology applications should follow suit, according to BFA, because credit scoring optimizes three business layers that improve the overall bottom line.