Big Data Push Affects Personal Financial Decision-Making: Mechanisms, Controversies, and Governance Implications

Abstract

This paper analyzes the impact of push information on financial decision-making from the perspective of behavioral economics. Firstly, this article explores the effects of cognitive bias and introduces how various oversized data analysis methods can prevent “generalization” in promoting financial products. Secondly, this article analyzes from the perspective of emotional drive, mainly referring to the positive emotional impact of users’ financial decisions being pleasantly surprised by push information. Finally, this study focuses on the effects of decision bias on users’ long-term and short-term financial decisions. To address the current controversies and challenges, it will discuss how to solve the problem by analyzing data anonymization, user consent, and algorithm transparency. Finally, based on data analysis, the application of big data push in financial decision-making was discussed, and future research directions and policy recommendations were proposed in response to existing new challenges and opportunities, indicating the need to strengthen the combination of technological innovation and social benefits.