AI, ML, and competition dynamics in financial markets

Paul A Grout

Oxford Review of Economic Policy, 2021, vol. 37, issue 3, 618-635

Abstract: There is a common assumption that the adoption of AI and ML in financial markets will make markets more competitive and reduce consumer prices. This paper argues, however, that this is far from obvious and identifies when increases in competition are unlikely to arise. There are several key messages. It is argued that, in contrast to the experience in bigtech markets, the widespread use of AI and ML at the sector-wide level is unlikely to lead to any significant short-term changes in concentration in financial markets. In the longer term, however, the question of whether there will be more concentration will depend on the balance of two opposing forces. On the one hand, rapid acceleration of the nascent merging of the boundaries between bigtech and financial markets could increase concentration; but on the other, action around the significant tightening of bespoke regulations, notably regulatory mandated data sharing, could push in the opposite direction. At the micro-market level, it is also argued that the impact of adopting AI and ML will be very sensitive to the specifics of the market (e.g. the impact of any consequent reduction of asymmetry of information is highly sensitive to the underlying asymmetry).

Keywords: credit markets; Big Data; machine learning; fintech; banking (search for similar items in EconPapers)
Date: 2021
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