Role of AI Tools in Enhancing Financial Inclusion through Digital Banking

Abstract

Artificial intelligence (AI) has emerged as a disruptive force in the financial sector, especially in the creation of digital banking services that promote financial inclusion. Financial inclusion, which seeks to give all segments of society access to affordable financial services, has historically been hampered by geographic distance, a lack of financial literacy, and high service fees. However, the application of AI in digital banking has fundamentally altered the delivery of financial services, making them more accessible, efficient, and customer-focused. This study explores the potential benefits of artificial intelligence (AI) tools such as machine learning, natural language processing, and predictive analytics in facilitating digital banking access for underserved and unbanked populations. The study also examines the ways in which AI-powered technologies have improved customer satisfaction, reduced risk, and fostered inclusive growth. Credit scoring algorithms, fraud detection systems, and chatbots are a few examples of these innovations. After analyzing current trends, challenges, and opportunities, the study concludes that artificial intelligence (AI) is a critical enabler of sustainable financial inclusion in the digital age.

Introduction

Artificial Intelligence (AI) has revolutionized the global financial sector, particularly through digital banking, which plays a vital role in promoting financial inclusion. Financial inclusion refers to providing equitable access to financial services such as credit, savings, and insurance. In many developing countries, traditional banking faces barriers like limited infrastructure, low financial literacy, and socioeconomic inequality. AI technologies—especially machine learning (ML), natural language processing (NLP), and data analytics—are helping bridge this gap by enabling personalized, accessible, and efficient digital banking solutions.

AI applications such as chatbots, virtual assistants, and AI-based credit scoring allow banks to serve previously unbanked populations. Chatbots provide multilingual 24/7 customer support, while AI-driven credit models evaluate creditworthiness using alternative data (e.g., mobile usage, transactions, and social behavior), enabling microloans for individuals lacking formal financial history. Collaboration between FinTech firms and banks has expanded digital financial services to rural and low-income groups, reducing costs and enhancing inclusion.

However, challenges such as algorithmic bias, data privacy, low digital literacy, and technological limitations persist. To ensure equitable access, a holistic approach combining ethical AI, digital education, and regulatory oversight is essential.

The literature review indicates that AI enhances inclusive finance by enabling data-driven insights, customer engagement, risk assessment, and fraud prevention. Yet, existing studies lack sufficient empirical analysis of AI’s direct impact on financial inclusion, especially in developing economies like India.

The research methodology adopts a mixed-methods approach (quantitative and qualitative) involving 180 participants—150 digital banking customers and 30 banking professionals. Data were gathered via surveys and interviews, with statistical analysis (correlation and regression) and thematic analysis applied.

Key findings include:

• High awareness and usage of AI chatbots (85% awareness, 70% usage).

• Strong positive correlation (r = 0.78, p < 0.01) between AI adoption and financial inclusion.

• Regression analysis showing AI usage explains 61% of inclusion variance (R² = 0.61).

• Hypotheses confirming that AI enhances inclusion, credit access, and adoption through trust and literacy.

Respondents overwhelmingly agreed that AI tools improve banking access, transaction security, and service efficiency. Nonetheless, gaps remain in rural digital literacy, data security, and algorithmic transparency.

In discussion, the study concludes that AI tools significantly strengthen financial inclusion by improving service accessibility, personalization, and trust—especially for underserved populations. Yet, achieving sustainable and equitable growth requires addressing ethical and infrastructural challenges.

Conclusion

According to the study\'s findings, artificial intelligence can significantly accelerate financial inclusion through innovative digital banking. AI technologies improve efficiency, security, and accessibility, making financial services more accessible to needy and unbanked groups. In particular, chatbots, AI-based credit scoring, and predictive analytics have helped to increase financial engagement. But in order to fully utilize AI, issues like algorithmic fairness, data privacy, and digital illiteracy must be resolved. To guarantee that AI-driven financial inclusion is moral, just, and long-lasting, policymakers, banks, and FinTech companies must cooperate. The integration of AI technologies with digital banking will continue to transform the financial inclusion landscape in the upcoming years as they grow and become easier to use, bringing society closer to the objective of universal access to financial services.

References

[1] Bose, S., & Dutta, A. (2022). Artificial Intelligence in Financial Services: Enhancing Inclusion and Efficiency. Journal of Financial Innovation, 10(2), 45–58. [2] Brynjolfsson, E., & McAfee, A. (2021). The Business of Artificial Intelligence. MIT Sloan Management Review. [3] Chaudhary, R., Mishra, S., & Gupta, N. (2023). AI Ethics in Digital Banking: Balancing Innovation and Inclusion. International Journal of Banking Technology, 14(3), 123–138. [4] Demirgüç-Kunt, A., Klapper, L., Singer, D., & Ansar, S. (2020). The Global Findex Database 2020: Measuring Financial Inclusion and Fintech Revolution. World Bank. [5] Jagtiani, J., & Lemieux, C. (2019). The Roles of Alternative Data and Machine Learning in Fintech Lending: Evidence from the US Market. Financial Management, 48(4), 1009–1027. [6] Kaur, G., & Aggarwal, P. (2021). AI-Driven Chatbots and Customer Experience in Digital Banking. International Journal of Digital Finance, 8(1), 67–79. [7] Ozili, P. K. (2022). Digital Finance, Financial Inclusion, and AI: A Systematic Review. Journal of Economic Studies, 49(2), 354–371. [8] Sarma, M., & Prasad, S. (2020). Artificial Intelligence and the Future of Financial Inclusion in Emerging Economies. Global Economic Review, 49(1), 22–39. [9] Sharma, N., & Kaur, M. (2020). Machine Learning-Based Credit Scoring for Inclusive Banking. Journal of Banking Research, 12(4), 213–230. [10] Trivedi, P., & Singh, V. (2021). AI Applications in Indian Banking: Towards Inclusive Growth. Indian Journal of Finance and Digital Economy, 6(2), 87–101.

Copyright

Copyright © 2025 Asst. Prof. Renuka Gaikwad. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.