Several studies have shown that poverty results in part from financial exclusion. Indeed, some people don’t have access to financial services due to their profiles, which in turn limits their opportunities for growing and leaving poverty. This is a big issue in particular in emerging countries where financial institutions are rare and often restricted to wealthy citizens.
Traditional financial institutions usually make the choice of granting access to credits to an individual based on few characteristics, past revenues and the expectations of repayment. This method tries to limit credit risks, but also prevents some categories of citizens to have access to these services.
DemystData, a New York based company launched in 2010, tackles the problem in a elegant manner. It uses richer data – social media, telecommunication information, online sources, etc. – to create a more complete risk profile associated with an individual. This way, some people which used to be excluded from financial systems now have access to the financial tools they deserve. By linking “unbanked” citizens to financial institutions it’s a win-win relationship: banks gain customers while ex-unbanked citizens benefit from financial services.
Although I imagine that not every single individual will receive this opportunity, I believe that it is really helpful in limiting financial exclusion and thus limiting poverty in the world.
Real Impact Analytics, a Luxembourg based company (but present in 5 different countries around the world) launched in 2009 seems to go a step further in applying data science for social good. Indeed, the data for good team applies this process to emerging markets. In developing countries, the share of unbanked people is even greater and the marge of improvement is huge. Their privileged sort of data – data from telecom operators – is used to address the issue and contribute to financial inclusion of areas affected by severe poverty.