Research on Generative Artificial Intelligence for Virtual Financial Robo-Advisor

Zengyi Huang; Chang Che; Haotian Zheng; Chen Li

doi:10.54097/30r2kk80

Authors

Zengyi Huang
Chang Che
Haotian Zheng
Chen Li

DOI:

https://doi.org/10.54097/30r2kk80

Keywords:

Artificial Intelligence (AI); Robo-advisers (RAs); Wealthfront; Investment Performance.

Abstract

This research explores the intersection of artificial intelligence and finance, focusing on the emergence of intelligent investment advisers, commonly known as Robo-advisers (RAs). These RAs utilize robust computer models and artificial intelligence algorithms to deliver personalized asset management investment plans for users. Notably, Wealthfront is highlighted as a prominent platform in this field, offering automated investment management services aimed at optimizing investment returns. The study investigates the impact of users' past investment performance on their adoption of intelligent advisers, considering factors such as previous defaults and recent investment performance. It reveals that frequent adjustments to the use of intelligent advisers may hinder long-term investment objectives, emphasizing the importance of consistent usage to fully capitalize on their benefits. Furthermore, the research emphasizes the significance of transparency, user-friendly interaction design, and tailored financial services to foster user trust and enhance the optimization of intelligent advisers' design.

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