Machine Learning for Financial Planning: A Comparative Analysis of Traditional Approaches and New Technologies

Authors : Hadef Saqer Obaid Hamad Al Dhaheri

Volume/Issue : Volume 8 - 2023, Issue 10 - October

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This studyaimed to explain the evolving subject of financial planning by comparing established approaches with the emerging domain of machine learning (ML) technology. For the attainment of this goal, the data was collected from secondary sources and 83 sources were reviewed. It is found that the use of ML in financial planning procedures has emerged as a significant development in the constantly evolving financial environment. This paper undertakes a thorough comparison analysis to clarify the advantages and disadvantages of conventional financial planning and techniques that incorporate ML. The focus is on explaining the potential of machine learning algorithms (MLA) to improve precision, efficiency, and adaptability in the field of financial planning. Moreover, this paper delves into the complex problems and ethical considerations that arise from the integration of ML and the field of finance. The purpose of doing this comparative analysis is to offer significant insights into the evolution of financial planning practices, enabling them to effectively utilise advanced ML technology. The primary objective of this research is to provide valuable insights for professionals, scholars, and policymakers, enabling them to make well-informed choices on the effective incorporation of ML in the domain of financial planning.

Keywords : Financial planning, ML , Comparative Analysis, Traditional Approaches, Ethical considerations.


Paper Submission Last Date
31 - December - 2023

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In 1-2 Days

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