Harvard Business Law Review
While safety concerns are at the forefront of the debate about driverless cars, such concerns seem to be less salient when it comes to the increasingly sophisticated algorithms driving the financial system. This Article argues, however, that a precautionary approach to sophisticated financial algorithms is justified by the potential enormity of the social costs of financial collapse. Using the algorithm-driven fintech business models of robo-investing, marketplace lending, high frequency trading and token offerings as case studies, this Article illustrates how increasingly sophisticated algorithms (particularly those capable of machine learning) can exponentially exacerbate complexity, speed and correlation within the financial system, rendering the system more fragile. This Article also explores how such algorithms may undermine some of the regulatory reforms implemented in the wake of the Financial Crisis to make the financial system more robust. Through its analysis, this Article demonstrates that the algorithmic automation of finance (a phenomenon I refer to as “driverless finance”) deserves close attention from a financial stability perspective. This Article argues that regulators should become involved with the processes by which the relevant algorithms are being created, and that such efforts should begin immediately – while the technology is still in its infancy and remains somewhat susceptible to regulatory influence.
Hilary J. Allen,
Available at: https://digitalcommons.wcl.american.edu/facsch_lawrev/695