Authors :
Hadef Saqer Obaid Hamad Al Dhaheri
Volume/Issue :
Volume 8 - 2023, Issue 10 - October
Google Scholar :
https://tinyurl.com/4mte928m
Scribd :
https://tinyurl.com/y5nzwbxz
DOI :
https://doi.org/10.5281/zenodo.10088726
Abstract :
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.
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.