Human–AI Collaboration in Personal Investing: The Roles of Trust, Risk Perception, and Financial Confidence

Abstract

The study extends to Human-AI Collaboration in Personal Investing, and the impact that the other three variables of trust, risk perception and financial confidence have on investors' actions in an AI-driven financial environment. The study aims to evaluate the belongings of increased implementation of investment platforms driven by artificial intelligence on investor attitudes and behaviours, and to understand what factors are creating a good “fit” between human investors and AI systems (including a measure of financial system confidence, awareness of investment risk, and trust in AI systems). The study method used is empirical that includes descriptive statistics, correlation statistics, and hypothesis testifying and other study variables are described and analyzed. Making of demography profile and analysis of the study variables became an important part of the study and seen as empirical and descriptive statistics, correlation analysis and hypothesis testing.  For retail investors, financial institutions, FinTech, and policy makers, the study is relevant for the chances and challenges that come with the use of AI in investments. The study aims to tackle the identified gap, which is related to human–AI interaction in the context of personal investing. The results aim to give evidence-based understanding of the factors affecting investment decisions made with the help of AI and suggestions for the advantages and disadvantages of enhancing AI-enabled investment platforms. Further study can expand this study to a wider and more varied investor base and be more comprehensive when incorporating other behavioural and technological issues.