Reputation, Risk, Profit, and Indebtedness

This chapter examines the evolution of reputational and risk assessment in consumer credit, detailing the shift from interpersonal judgments to data-driven, profit-optimising systems. It begins by reviewing empirical studies of information asymmetry, focusing on the twin problems of adverse selection and moral hazard. While theory predicts these asymmetries constrain lending, the chapter finds that modern data analytics often enable the opposite: the targeting of price-insensitive borrowers with high-cost products. This can result in ‘advantageous selection,’ where vulnerable yet motivated borrowers accept rates disproportionate to their actual risk. The chapter then traces the historical shift from subjective, character-based judgments to statistical scoring, showing how these tools, combined with securitisation, to increase household debt burdens before the 2008 financial crisis. It also critiques the modern role of credit bureaux as brokers who monetise borrower engagement and finds post-crisis affordability rules are often too weakly defined to prevent significant harms. Ultimately, the chapter concludes that credit assessment has evolved from a trust-based function to a system of profit maximisation that deepens borrower vulnerability and increases systemic risk.