This chapter explores the scope of consumer credit, including lending, debt advice, and types of credit. It discusses the increasing digitization, datafication, and disintermediation of consumer credit markets. The chapter also delves into the use of credit scoring algorithms, alternative data for credit scoring, and the role of big data and machine learning in determining creditworthiness.
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In today's episode, I talk to Nikita Aggarwal about the legal and regulatory aspects of AI and algorithmic governance. We focus, in particular, on three topics: (i) algorithmic credit scoring; (ii) the problem of 'too big to fail' tech platforms and (iii) AI crime. Nikita is a DPhil (PhD) candidate at the Faculty of Law at Oxford, as well as a Research Associate at the Oxford Internet Institute's Digital Ethics Lab. Her research examines the legal and ethical challenges due to emerging, data-driven technologies, with a particular focus on machine learning in consumer lending. Prior to entering academia, she was an attorney in the legal department of the International Monetary Fund, where she advised on financial sector law reform in the Euro area.
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September 18, 2020 1:09 pm
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John Danaher
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