Startups use behavioural data and smartphone habits for credit scoring
In October 2018, the Singapore-based startup LenddoEFL was one of a group of microfinance startups aimed at the developing world that used non-traditional types of data such as behavioural traits and smartphone habits for credit scoring. Lenddo's algorithm uses numerous data points, including the number of words a person uses in email subject lines, the percentage of photos in a smartphone's library that were taken with a front-facing camera, and whether they regularly use financial apps on their smartphones. Lenddo believes these types of data have enabled it to build an algorithm that is a reliable predictor of credit-worthiness for those who lack formal credit histories. Once it's been proved in emerging economies in Africa, Asia, and Latin America, the company intends to bring the system to the US, where 30 million people lack access to bank accounts, credit cards, and loans. These systems raise concerns about privacy and the potential for bias to be introduced by the data fed into the AI. Other companies with similar operations include Myanmar-based Maha Agriculture and Newark, California-based Harvesting, which uses AI and satellite technology to identify eligible farmers and help them get loans.
Writer: Emily Bary
Publication date: 2018-10-09