Leveraging Artificial Intelligence and Machine Learning for Enhancing Automated Financial Advisory Systems: A Study on AIDriven Personalized Financial Planning and Credit Monitoring

Abstract

The bulk of literature to date in the area of automated financial advice systems focuses on the accuracy and consistency, compliance, and reliability of technology-based robo-advisory systems. However, in line with the call for pioneering research on personalization and improved reliability through technology development, this study intends to address these major needs unmet with the existing research. Hence, the study focuses on the development of AI-driven personalized financial planning and credit monitoring systems consisting of a future financial plan algorithm and a future credit activity monitoring mechanism. Through the implementation and subsequent use of a quantitative research method and the analysis of structured data received from 112 online participants, the findings provided insights into: (i) how the system-driven disclosure of future plans can enhance the perceived performance of automated financial advisory systems, and (ii) to what extent a future credit activity monitoring mechanism could increase user trust in technology-based financial advice services.

In the Research Communities, above-average to high importance is attached to the studies on the development and implementation of AI-powered personalization systems and technological advancements that enhance the robustness and reliability of automated financial advice services. The large part of the subsequent development in automation in this area will, in line with this perspective on the importance of research issues, focus on the development of the AI-driven future financial plan creation and future credit activity monitoring mechanism. Closing the literature gap on the AI-driven financial plans design and the future monitoring of credit activity will allow a broader understanding of automated financial advice systems for a better-quality design of such tools. Providing insights into the willingness to adopt these tools among potential stakeholders, the research will contribute to the literature related to the adoption of AI and ML in the provision of financial services to a better understanding of the societal impacts of these systems.