AI-driven NLP approach for Domiciliary Fiscal Administration

Authors

  • P. Gnaneswari Research Scholar, Department of Commerce and Management Studies (DCMS), Andhra University, Visakhapatnam
  • S. Rajani Department of Commerce and Management Studies, Gayathri Vidya Parishad, Rishikonda, Visakhapatnam
  • Ravi Jaladi Department of Commerce and Management Studies (DCMS), Andhra University, Visakhapatnam.

Keywords:

Socioeconomic Factors, Household Financial Management, Artificial Intelligence, Financial Decision-Making, Income Levels, Education

Abstract

This research paper delves into the intricate relationship between socioeconomic factors and household financial management, employing artificial intelligence (AI) as a powerful analytical tool. In the contemporary landscape of personal finance, understanding how income levels, education, employment, and other socioeconomic variables influence financial decisions is imperative for fostering economic stability and inclusivity. The study investigates the multifaceted impact of these factors on various aspects of household finances, striving to unravel patterns and disparities. To facilitate a nuanced analysis, the research integrates cutting-edge AI technologies, leveraging machine learning and predictive modelling. These AI-driven approaches aim to provide a comprehensive understanding of the intricate interplay between socioeconomic factors and financial outcomes. The study not only explores the challenges faced by households in managing their finances but also assesses the effectiveness of AI in enhancing financial decision-making processes. The objectives of this research are threefold: first, to investigate and delineate the influence of socioeconomic factors on household finances; second, to rigorously assess the effectiveness of AI in financial analysis, including its predictive capabilities and personalized insights; and third, to provide actionable recommendations for improving household financial management based on the findings. By combining socioeconomic analysis with advanced AI methodologies, this research endeavors to contribute valuable insights to academia, policymakers, and financial practitioners. The outcomes are expected to shed light on strategies for addressing financial inequalities and empowering individuals and households to make informed and sustainable financial decisions in an evolving economic landscape.

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References

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Smith, A., & Jones, B. (2018). Income, financial literacy, and financial decision-making. Journal of Financial Counseling and Planning, 29(1), 101-114.

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Published

24.03.2024

How to Cite

Gnaneswari, P. ., Rajani, S. ., & Jaladi, R. . (2024). AI-driven NLP approach for Domiciliary Fiscal Administration . International Journal of Intelligent Systems and Applications in Engineering, 12(18s), 76–89. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4953

Issue

Vol. 12 No. 18s (2024)

Section

Research Article

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