Authors : Utkarsh Sharma

Volume/Issue : Volume 10 - 2025, Issue 9 - September

Google Scholar : https://tinyurl.com/bdfyrhrb

Scribd : https://tinyurl.com/5bhsark3

DOI : https://doi.org/10.38124/ijisrt/25sep110

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Note : Google Scholar may take 30 to 40 days to display the article.

Abstract : The prime focus of the present study is to explore the socio-economic implications of AI integration in the context of the Indian financial sector. It will also aim to identify the various opportunities and threats associated with this integration and particularly focus on the sustainable development goals of the SDG 8: Decent Work and Economic Growth. The primary objective is, therefore, to employ a purposive sample of 52 financial executives with complementary roles and formal background for the analysis of the level of acceptance of AI integration, what it means in terms of employment possibilities (positive and negative), the deliberate slow process of embracing AI, and the interventions that would have to be implemented to realize SDG 8 thanks to AI. It is observed that many of the respondents hold the view that, while there are some aspects of AI that can lead AI to a democratization, breaking up and streamlining the structure of financial markets and preventing the behavior of a few players, it is also true that modernization in capitalism is rather a power-based exercise. Respondent were fairly optimistic about the potential od AI to bring about inclusion and efficiencies. Costs have been associated with such optimism with respondents observing that various factors such as ‘algorithmic bias’, aspects related to ‘transparency’ as well as, ‘data security’ raises concern, not leaving the specter of jobs being eradicated due to automation either. Even though many of the participants stand in positive light of the possibilities of AI towards the achievement of SDG8, a number of participants envision there will be reduced incorporation of this sector in the society’s overall economic activities within the next few years. Clearly, this development calls for a purposeful and efficient policy formulation involving the government, banks, and education sectors in order to mitigate the disadvantages of AI technology and enhance the benefits of it, so that there is a secure and fair AI-led financial sector development, which will promote the development of the poor and high-growth and encourage grievance- free economic growth in India.

Keywords : Artificial Intelligence, Financial Sector, India, Sustainable Development Goal 8, Employment, Ethical Considerations.

References :

1. Agarwal, S., & Ghosh, D. (2024). Artificial Intelligence and Financial Inclusion: Evidence from Emerging Economies. Journal of Development Economics, 168, 103245.
2. Banerjee, S., & Chatterjee, P. (2022). Algorithmic Bias in Credit Scoring: Evidence from Fintech Lending Platforms in India. Economic & Political Weekly.
3. Das, S., & Sen, G. (2023). Financial Literacy and Digital Inclusion: The Role of AI-Powered Education Tools in Rural India. Journal of Financial Education.
4. Iyer, L., & Menon, K. (2023). AI for Regulatory Compliance in Indian Banks: A Framework for Anti-Money Laundering. Journal of Regulatory Economics.
5. Lee, J., & Gupta, V. (2024). Fintech Regulation and Innovation: A Comparative Analysis of Sandbox Approaches in India and Singapore. Journal of Financial Regulation and Compliance.
6. Patel, D., & Joshi, K. (2022). AI-Powered Chatbots in Indian Banking: Factors Influencing User Adoption and Satisfaction. International Journal of Bank Marketing.
7. Rao, P., & Bhat, S. (2022). The Future of Skills in the Indian Financial Sector: A Scenario Planning Exercise. Technological Forecasting and Social Change.
8. Sharma, A., & Kumar, R. (2023). The Impact of AI on Employment in the Indian Banking Sector: A Mixed-Methods Analysis. IIMB Management Review.
9. Singh, R., & Reddy, M. (2023). Cybersecurity in Indian Financial Institutions: A Risk Assessment Framework. Information & Computer Security.
10. Verma, N., & Kapoor, A. (2024). Predictive Analytics and Algorithmic Trading in the Indian Stock Market: A Performance Evaluation. Journal of Emerging Market Finance.
11. Chakraborty, R., & De, R. (2023). AI-Driven Credit Risk Assessment for Microfinance Institutions in India: A Case Study. Journal of Business Analytics, 6(2), 145-162.
12. Dhar, S., & Sarkar, S. (2024). Explainable AI (XAI) for Fraud Detection in Indian Banks: A Comparative Analysis of Techniques. International Journal of Intelligent Systems, 39(3), 1201-1225.
13. Jha, P. K., & Kumar, A. (2022). The Ethical Implications of AI in Algorithmic Trading: A Review of Literature and Case Studies. Journal of Business Ethics, 180(4), 1101-1120.
14. Mishra, V., & Sharma, P. (2023). Regulatory Challenges of AI in the Indian Financial Sector: Balancing Innovation and Consumer Protection. National Law School of India Review, 35(1), 78-95.
15. Rajan, S., & Nair, A. S. (2024). Impact of AI-Powered Chatbots on Customer Service Efficiency and Satisfaction in Indian Private Sector Banks. The IUP Journal of Marketing Management, 23(1), 56-73.