The Norms of Algorithmic Credit Scoring

The use of alternative data (i.e. not exclusively credit-related data) in combination with machine learning to assess consumer creditworthiness is growing rapidly in the banking industry, in such a way that could significantly affect consumers’ privacy and autonomy. This practice is described as ‘algorithmic credit scoring’.

Currently, regulators are confronted with the challenge of finding a fair equilibrium in the law, which is able to increase efficiency in credit markets, while protecting the consumer at the same time. As financial institutions, or more likely third party companies, pool together personal data and expand the information and knowledge available to them , people are trading in their freedom as consumers and citizens, as the credit services they will be receiving will be tailored as well as limited, on the basis of stringent measurable criteria that they will have contributed to create themselves in different (non credit-related) life contexts. 

If it is true that the market is increasingly relying on people’s social and behavioural data and that individualised, rights- and market-based mechanisms under existing data protection regulation are ineffective for protecting consumers' privacy and autonomy, then stricter limits on the processing of personal data in the context of consumer lending ought to be sought.

Since these profiling techniques are likely to be replicated across various sectors as a novel source for company growth, the findings of this research might easily extend to other industries.

About the speaker

Nikita Aggarwal

Nikita Aggarwal is a DPhil (PhD) candidate at the Faculty of Law, 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 and worked extensively on initiatives to reform the legal and policy frameworks for sovereign debt restructuring. She previously practiced as an associate with Clifford Chance LLP, where she specialized in EU financial regulation and sovereign debt restructuring. She earned an LLB (Hons) from the London School of Economics and Political Science.