“Privacy, Autonomy and Beyond: The Psychology of Financial AI Adoption”
by Oğuz Acar
Bayes Business School (University of London)
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Abstract
Artificial Intelligence (AI) algorithms are fundamentally transforming consumer finance. However, our knowledge on how consumers respond to AI-based financial products is limited. In this paper, we ask a novel question: what are the relative importance of psychological drivers of financial AI algorithm adoption? Drawing on two discrete choice experiments, we first show that psychological factors explain a larger percentage of adoption than the combined effect of price and performance. In addition, we find that auditability, a variable that is often neglected in prior literature, turns out to be a key psychological driver—a stronger predictor of adoption than more widely discussed AI features such as autonomy, personalisation, and understandability—and second only to privacy. Taken together, this study takes the first steps to shed light on relative importance of various psychological drivers—in contrast to past research that has focused on isolated impacts of individual factors—in the underexplored context of consumer financial decision making. Our simulations predicting adoption of AI-based financial products, as a function of its features, illustrates how practitioners could build on these insights.
