Digital subprime: tracking the credit trackers

Abstract

This chapter introduces a phenomenon I call ‘digital subprime’. Digital subprime represents a frontier in lenders’ quest for predictive power, involving a growing group of technology startups who are entering subprime, payday lending markets in various countries and are lending at high rates of interest to borrowers who often have either poor or not credit histories. In this variant of consumer credit lending, diverse forms of data are processed through forms of algorithmic analysis in the attempt to better predict the repayment behaviour of individuals. This data often appears extremely mundane and to have very little to do with the credit product in hand. The chapter seeks to map the terrain of possibility represented by the diverse forms of data that are rendered accessible to lenders, partly as a basis for future research, and partly to highlight key developments in the present and future ontologies of money.