Digital Twin Modeling of Financial Advisors using AI for Hyperpersonalized Wealth Management

Abstract

The idea of a digital twin-capable robo-advisor for individual financial planning is the subject of this study. A digital twin-based interactive and interpretative model was constructed using an exploratory study to assess some of the important aspects to think about while building the next generation financial advice robo-advisor. Its primary function is to evaluate the current state of affairs and, after analysing the available data, to provide a framework that may guide further studies. Publications such as books, journals, case studies, and magazines were combed through for relevant information. The purpose of this research is to evaluate digital twins (DTs) as a potential new standard for intelligent financial advisers (robo-advisors) that may aid in the development and implementation of FinTech services and solutions that are uniquely suited to each individual client. DT-enabled robo-advisors may improve financial management and well-being. When DT is turned on, a robo-advisor stops being ad hoc and starts providing users with a full-fledged, ever-changing financial consulting service. The study sheds light on finance robo-advise with DT abilities, which can optimise intelligent investments and bring about transformation.