Author(s):
Lokeshwari DV, Shruthi M P, T. Manjunatha
Email(s):
dvlhokeshwarie@gmail.com , mpshurthigvt@gmail.com , tmmanju87@gmail.com
DOI:
10.52711/2321-5763.2025.00021 
Address:
Lokeshwari DV1, Shruthi M P2, T. Manjunatha3
1Assistant Professor, PG Department of Commerce, Surana College – Autonomous, Bangalore, Karnataka.
2Assistant Professor, School of Commerce and Management, Dayananda Sagar University, Bangalore, Karnataka.
3Professor, Department of MBA, Visvesvaraya Technological University, BDT College of Engineering, Davanagere -577004, Karnataka.
*Corresponding Author
Published In:
Volume - 16,
Issue - 2,
Year - 2025
ABSTRACT:
This study investigates AI's impact in increasing financial inclusion and strengthening government-led initiatives such as PMJDY and DBTs. AI tools like machine learning-based credit scoring and automated transactions help to combat instability, fraud, and financial exclusion. The study, which is based on TAM, Financial Inclusion Theory, RBV, and Fraud Triangle Theory, analyses primary data from 468 stakeholders as well as secondary data from the RBI and NITI Aayog. While AI enhances transparency and efficiency, its influence on fraud prevention and financial literacy is questionable. SEM confirms a beneficial link between artificial intelligence and financial inclusivity. Future research should focus on improving AI infrastructure, literacy initiatives, and internet accessibility to promote long-term economic growth.
Cite this article:
Lokeshwari DV, Shruthi M P, T. Manjunatha. Artificial Intelligence in Financial Inclusion: An Impact on Financial Accessibility and Efficiency in India. Asian Journal of Management. 2025;16(2):134-8. doi: 10.52711/2321-5763.2025.00021
Cite(Electronic):
Lokeshwari DV, Shruthi M P, T. Manjunatha. Artificial Intelligence in Financial Inclusion: An Impact on Financial Accessibility and Efficiency in India. Asian Journal of Management. 2025;16(2):134-8. doi: 10.52711/2321-5763.2025.00021 Available on: https://ajmjournal.com/AbstractView.aspx?PID=2025-16-2-10
REFERENCES:
1. Verma, S., and Khanna, P. Reaching the unbanked: AI in financial inclusion initiatives. Journal of Emerging Financial Markets. 2023; 10(1): 12–29.
2. NITI Aayog. Enhancing financial accessibility through AI‐based credit scoring. New Delhi, India: NITI Aayog. 2023
3. Reserve Bank of India. Annual report on digital banking and AI adoption. Mumbai, India: RBI. 2023
4. McKinsey and Company. Efficiency gains in banking through AI: A global perspective. McKinsey Report. 2023
5. NASSCOM. AI automation in government-led banking: A comprehensive report. NASSCOM Research. 2023
6. Chatterjee, S. Scaling public financial services through AI automation. Journal of Financial Services Technology. 2023; 5(1): 12–28.
7. PwC. Machine learning algorithms in fraud detection: Innovations in government programs. PwC Insights. 2023
8. World Bank. AI‐based biometric authentication in public financial programs. World Bank Report. 2023
9. Rao, R., and Nair, M. Enhancing DBT security: The role of real-time AI monitoring. Journal of Public Security. 2023; 7(2): 56–70.
10. United Nations Development Programme. Digital financial literacy: The role of AI in enhancing financial awareness. UNDP Report. 2023
11. Chatterjee, S., and Roy, P. Enhancing financial literacy in rural areas through AI-enabled educational platforms. Journal of Rural Finance. 2023; 4(1): 12–27.
12. Rao, S. User engagement with AI-based financial literacy programs: An empirical study. Journal of Financial Behavior. 2023; 5(1): 33–48.
13. Chakrabarty, A. AI‐driven financial services: Reducing barriers in banking. International Journal of Financial Technology. 2022; 9(2): 101–120.
14. Sharma, R., Kumar, V., and Singh, P. AI‐powered chatbots and voice-based banking: A case study of UPI123Pay. Journal of Digital Banking. 2022; 7(1): 55–70.
15. Gupta, R., Sharma, A., and Verma, S. Integration of AI in digital payment platforms: Implications for financial inclusion. International Journal of Payment Systems. 2022; 8(2): 34–50.
16. Sharma, R. The impact of AI‐driven KYC on banking efficiency. Journal of Digital Verification. 2022; 6(1): 20–35.
17. Desai, P., and Mehta, R. Minimizing manual processing in public banking with AI automation. International Journal of Automation. 2022; 8(1): 88–102.
18. Singh, R., and Roy, S. AI‐driven fraud detection in government financial schemes. Journal of Fraud Prevention. 2022;10(3): 55–72.
19. KPMG. Enhancing security in DBTs through AI-powered anomaly detection. KPMG Research. 2022
20. Verma, A., Kapoor, S., and Joshi, D. Detecting ghost beneficiaries using AI: Evidence from government subsidies. Journal of Financial Security. 2022; 11(2): 30–45.
21. KPMG. AI‐driven predictive analytics for future fraud prevention in government programs. KPMG Research. 2022; 2(1): 15–29.
22. Deshmukh, A. The role of AI in promoting savings behavior among low-income individuals. Journal of Consumer Finance. 2022; 7(2): 40–55.
23. Singh, R. Digital financial education initiatives: The transformative power of AI. Journal of Financial Transformation. 2022; 3(2): 28–44.
24. NITI Aayog. AI interventions and financial literacy improvements among underserved populations. NITI Aayog Research. 2022
25. Mehta, K. AI adoption in microfinance institutions: Opportunities and challenges. Microfinance Journal. 2021; 5(3): 123–140.
26. Kumar, A., and Gupta, S. AI‐enabled automation in Direct Benefit Transfers: Enhancing public banking efficiency. Journal of Public Banking. 2021; 11(2): 45–60.
27. Patel, R. Reducing operational costs in public banking with AI. Journal of Banking Innovation. 2021; 7(2): 67–81.
28. Singh, D., Kumar, R., and Mehta, A. AI and customer satisfaction in government banking services. Journal of Customer Service in Banking. 2021; 9(2): 33–47.
29. Das, A., and Sharma, R. Predictive analytics and fraud prevention in government schemes. Journal of Predictive Analytics. 2021; 4(2): 44–60.
30. Gupta, R. Integrating AI for tracking fraudulent activities in public financial schemes. International Journal of Fraud Management. 2021; 6(3): 78–94.
31. Patel, R., and Sharma, A. Impact of AI-powered financial chatbots on financial literacy. Journal of Financial Education. 2021; 8(2): 50–65.
32. Jain, P., and Kumar, S. Multilingual AI advisory platforms: Enhancing financial literacy in diverse populations. Journal of Global Banking. 2021; 9(1): 22–38.
33. Jain, P., and Patel, R. Overcoming lending biases through AI: New paradigms in credit scoring. Journal of Banking and Finance. 2020; 14(4): 78–90.
34. Rao, R., and Verma, A. Fund disbursement efficiency and AI: An empirical study in public finance. Journal of Public Finance. 2020; 12(3): 90–105.
35. Chandra, S., and Singh, P. Reducing fraud opportunities with real-time AI monitoring. Journal of Fraud Analytics. 2020; 3(1): 12–25.
36. Banerjee, S. Gamification and financial literacy: AI tools in banking education. Journal of Digital Learning. 2020; 5(3): 34–49.
37. Kumar, V. Simplifying banking: The impact of AI advisors on financial literacy. International Journal of Financial Services. 2020; 6(1): 15–30.
38. Banerjee, S., and Singh, R. Policy frameworks for AI in financial inclusion. Policy Insights. 2019; 4(2): 32–48.
39. Banerjee, S. Enhancing process reliability through AI in public sector banks. Banking Technology Review. 2019; 3(4): 40–55.
40. Sarma, M. Measuring financial inclusion: The development of a Financial Inclusion Index. Journal of Financial Services Research. 2008; 12(3): 45–62.