Harnessing AI for personalized financial coaching: A pathway to financial inclusion and empowerment for women in the United States
1 University of Virginia Darden School of Business, Charlottesville, VA, USA.
2 Cornell University, SC Johnson Business School, Ithaca, NY, USA.
3 Johns Hopkins Carey Business School, Baltimore, MD, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 23(02), 1356–1367
Publication history:
Received on 08 July 2024; revised on 15 August 2024; accepted on 17 August 2024
Abstract:
Artificial intelligence (AI) is increasingly recognized as a transformative tool in financial services, offering the potential to address persistent financial inclusion issues, particularly for women. In the United States, women face significant barriers to financial literacy and economic participation, often exacerbated by systemic biases and limited access to tailored financial education. This article explores the application of AI-driven personalized financial coaching to empower women economically and enhance financial inclusion. Through a comprehensive analysis of current AI tools and case studies, this study examines how AI can provide customized financial advice that aligns with women's unique needs and goals, overcoming traditional barriers such as accessibility and cultural factors. The ethical considerations associated with AI, including data privacy, algorithmic bias, and the potential for unequal access to technology, are critically discussed. The findings suggest that AI-driven financial coaching not only holds promise for closing the financial literacy gap but also for fostering greater financial autonomy among women, ultimately contributing to broader socio-economic development in the U.S. This study provides a foundation for further research into the development of inclusive AI technologies and their role in promoting financial equity.
Keywords:
AI; Financial Inclusion; Personalized Financial Coaching; Women’s Empowerment; Financial Literacy; United States
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0