Consumer credit in comparative perspective

We review the literature in sociology and related fields on the fast global growth of consumer credit and debt and the possible explanations for this expansion. We describe the ways people interact with the strongly segmented consumer credit system around the world—more specifically, the way they access credit and the way they are held accountable for their debt. We then report on research on two areas in which consumer credit is consequential: its effects on social relations and on physical and mental health. Throughout the article, we point out national variations and discuss explanations for these differences. We conclude with a brief discussion of the future tasks and challenges of comparative research on consumer credit.Accepted manuscrip

A Tale of Two Markets: How Lower-end Borrowers Are Punished for Bank Regulatory Failures in Nigeria

In 2009, the Nigerian banking system witnessed a financial crisis caused by elite borrowers in the financial market. Regulatory response to the Nigerian crisis closely mirrored the international response with increased capital and liquidity thresholds for commercial banks. While the rise of consumer protection on the agenda of prudential supervisors internationally was logical in that consumer debt was the main cause of the global recession, the Nigerian banking reforms of 2009 disproportionately affected access by poorer consumers, who ironically had little to do with the underlying causes of the crisis. As lending criteria become more stringent, poorer consumers of credit products are pushed into informal markets because of liquidity-induced credit rationing. Overall, consumer protection is compromised because stronger consumer protection rules for the formal sector benefits borrowers from formal institutions who constitute the minority of borrowers in all markets. While the passage of regulation establishing credit bureaux and the National Collateral Registry will, in theory, ease access to credit especially by lower-end borrowers, the vast size of the informal market continues to compound the information asymmetry problem, fiscal policies to tackle structural economic issues such as unemployment and illiteracy remain to be initiated, and bank regulators continue to pander to elite customers with policy responses that endorse too big to fail but deems lower-end consumers too irrelevant to save. The essay concluded that addressing the wide disparity in access to credit between the rich and poor through property rights reforms to capture the capital of the informal class, promoting regulation to check loan concentration, and stimulating competition by allowing Telecommunication Companies (TELCOs) and fintech companies to carry on lending activities because of their superior knowledge of lower-end markets will facilitate greater access. The risk of systemic failure deriving from consumer credit in Nigeria is insignificant compared to the consumer vulnerabilities resulting from the exposure of consumers to unregulated products in the informal market

Construction, Concentration, and (Dis)Continuities in Social Valuations

I review and integrate recent sociological research that makes progress on three interrelated questions pertaining to social valuation: (a) the degree of social construction relative to objective constraints; (b) the degree of concentration in social valuations at a single point in time; and (c) the conditions that govern two broad forms of temporal discontinuity—(i) fashion cycles, especially in cultural expression and in managerial practices, and (ii) bubble/crash dynamics, as witnessed in such domains as authoritarian regimes and financial markets. In the course of the review, I argue for the importance of identifying how objective conditions constrain social construction and suggest two contrarian mechanisms by which this is accomplished—valuation opportunism and valuation entrepreneurship—and the conditions under which they are more or less effective

When to rebuild or when to adjust scorecards

Data-based scorecards, such as those used in credit scoring, age with time and need to be rebuilt or readjusted. Unlike the huge literature on modelling the replacement and maintenance of equipment there have been hardly any models that deal with this problem for scorecards. This paper identifies an effective way of describing the predictive ability of the scorecard and from this describes a simple model for how its predictive ability will develop. Using a dynamic programming approach one is then able to find when it is optimal to rebuild and when to readjust a scorecard. Failing to readjust or rebuild a scorecard when they aged was one of the defects in credit scoring identified in the investigations into the sub-prime mortgage crisis

Predicting the Future: Art and Algorithms

Predictive algorithms are replacing the art of human judgement in rapidly growing areas of social life. By offering pattern recognition as forecast, predictive algorithms mechanically project the past onto the future, embracing a peculiar notion of time where the future is different in no radical way from the past and present, and a peculiar world where human agency is absent. Yet, prediction is about agency, we predict the future to change it. At the individual level, the psychological literature has concluded that in the realm of predictions, human judgement is inferior to algorithmic methods. At the sociological level, however, human judgement is often preferred over algorthms. We show how human and algorithmic predictions work in three social contexts—consumer credit, college admissions and criminal justice—and why people have good reasons to rely on human judgement. We argue that mechanical and overly successful local predictions can result in self-fulfilling prophecies and, eventually, global polarization and chaos. Finally, we look at algorithmic prediction as a form of societal and political governance and discuss how it is currently being constructed as a wide net of control by market processes in the USA and by government fiat in China.1. Introduction 2. The statistical versus clinical prediction debate 3. Three main technological developments enabling algorithmic predictions 4. Pattern recognition versus prediction 5. Why one should be skeptical 6. Credit 7. The science of scoring 8. Agency 9. College admission 10. Crime 11. The world of algorithmic government 12. Conclusion Footnotes Reference