Algorithmic tenancies and the ordinal tenant: digital risk-profiling in England's private rented sector

Abstract

This paper examines digital tenant risk-profiling tools in England's Private Rented Sector (PRS) and their influence on housing access and fairness. Based on qualitative data from 50 interviews and a survey of PRS landlords drawn from a larger project, the study analyses adoption patterns, algorithmic biases and the implications for tenant rights. Issues such as data privacy, discrimination, and exclusionary practices affecting marginalised groups are highlighted. The research underscores how digital platforms reshape landlord-tenant relationships and broader housing market dynamics in the light of recent, broader, theorisations of what sociologists Marian Fourcade and Kieran Healy have conceptualised as an emerging ordinal society. In this article, we argue that the logic of such metrics and data-informed algorithmic systems has led to the emergence of an ordinal tenant.