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Paper ID:IJSREM68614

AI-Enabled Sustainable Banking: An Empirical Examination of the State Bank of India’s Green Practices

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM68614

Volume:

10 |

10 |

Oct 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM68614

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

YP

Yogita Patil

Accounting and Finance

Ramsheth Thakur College of Commerce and Science

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NB

Namit Bhatnagar

Accounting and Finance

Doon Business School

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Abstract

Environmental concerns are pushing banks toward green banking practices that minimize ecological footprints while maintaining efficiency. The State Bank of India (SBI), the country’s largest public sector bank, has introduced initiatives in sustainable finance, energy conservation, and paperless transactions, and Artificial Intelligence (AI) can make these practices more efficient, scalable, and engaging for customers. This empirical study aims to (i) examine SBI’s current green banking initiatives, (ii) identify AI applications that can amplify them, and (iii) assess the benefits and challenges of AI integration. A mixed-methods design combined surveys and interviews with 50 SBI employees and 150 customers with secondary data from sustainability reports and RBI guidelines, using descriptive and inferential statistics, thematic analysis, and AI application mapping. Awareness was highest for online/digital banking (92%), lowest for green loans (38%), and significantly higher among urban than semi-urban customers. Carbon footprint tracking was the most appealing AI-enabled feature (68% interest), although 28–32% of respondents reported privacy concerns. SBI has progressed in digital and green initiatives, but AI integration remains at an early stage. Promising applications include AI-driven credit risk assessment, machine learning for branch energy optimization, natural language processing for customer sustainability education, and predictive analytics for environmental impact monitoring. Barriers include high implementation costs, limited staff AI literacy, data privacy concerns, and regulatory uncertainty, calling for training, digital infrastructure, and phased adoption aligned with the UN Sustainable Development Goals. The study offers an integrated framework for AI-enabled sustainable banking in India, positioning SBI as a benchmark for other banks.

KEYWORDS

Artificial Intelligence Green Banking Sustainable Finance State Bank of India AI Integration Sustainable Development Goals.

Cite This Article

Yogita Patil, Namit Bhatnagar, "AI-Enabled Sustainable Banking: An Empirical Examination of the State Bank of India’s Green Practices," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 10, pp. 1-7, Oct 2026. https://doi.org/10.55041/IJSREM68614

Full Article/Conclusion

In sum, the data analysis demonstrates that SBI has a solid digital foundation and a customer base moderately receptive to AI-enabled sustainability features, while also facing nontrivial implementation and governance challenges. The combined quantitative and qualitative evidence supports a phased, governance-centric AI adoption roadmap that prioritizes privacy, staff capacity-building, and demonstrable operational wins to accelerate SBI’s transition to AI-enabled sustainable banking. This research underscores that while SBI is on a positive trajectory in promoting green banking, there is considerable room for improvement, particularly in awareness-building for specialized products and expanding outreach in semi-urban regions. AI integration holds transformative potential for advancing the bank’s sustainability agenda, but its success will depend on a balanced approach that combines technological innovation with trust-building and inclusivity.

References

Akter, A., Majumder, M. T. H., & Rahman, M. M. (2012). Green banking—A new dimension. Journal of Management and Science, 2(4), 343–347. https://doi.org/10.26524/jms.2012.43[ME1]  Bahl, S. (2012). The role of green banking in sustainable growth. International Journal of Marketing, Financial Services & Management Research, 2(1), 27–35.[ME2]  Cao, L. (2021). AI in finance: Challenges, techniques and opportunities [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2107.09051[ME3]  Elshamly, A., Rehman, S. U., Rahman, M. M., Hameed, R., & Jameel, Z. (2023). AI-based green banking technologies and bank stability: Moderating role of climate change. Journal of Namibian Studies: History Politics Culture, 35, 217–228. https://doi.org/10.59670/jns.v35i.3406[ME4]  Faruq, A. T. M. O., & Chowdhury, M. A. R. (2025). Financial markets and ESG: How big data is transforming sustainable investing in developing countries [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2503.06696 Islam, M. S., & Das, P. C. (2013). Green banking practices in Bangladesh. IOSR Journal of Business and Management, 8(3), 39–44. https://iosrjournals.org/iosr-jbm/papers/Vol8-issue3/G0833944.pdf[ME5]  Jha, B., & Bakhshi, P. (2019). Green finance: Fostering sustainable development in India. International Journal of Recent Technology and Engineering, 8(4), 3798–3801. https://doi.org/10.35940/ijrte.D8172.118419[ME6]  Narayanan, M. (2025). Trends and artificial intelligence development of banking sector: Social implication of green banking initiatives. Asian Journal of Management, 16(1), 29–33. https://doi.org/10.52711/2321-5763.2025.00005 Park, H., & Kim, J. D. (2020). Transition towards green banking: Role of financial regulators and financial institutions. Asian Journal of Sustainability and Social Responsibility, 5(1), Article 5. https://doi.org/10.1186/s41180-020-00034-3[ME7]  Xu, J. (2024). AI in ESG for financial institutions: An industrial survey [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2403.05541  [ME1]CORRECTED (verified on the journal's Vol 2, No 4 issue page): author order is Akter, Majumder, Rahman (not Majumder first) and pages are 343–347 (not 62–66). DOI unchanged. Entry moved alphabetically under 'A'.  [ME2]PARTLY VERIFIED. Not confirmed from the journal itself. Several citing papers give volume 1(2), pp. 27–35; one gives 2(1). Kept as you wrote it (2(1)); please confirm volume/issue from your copy. Note: article title de-italicized per APA 7.  [ME3]VERIFIED as an arXiv preprint. A peer-reviewed version exists: Cao, L. (2022). AI in finance: Challenges, techniques, and opportunities. ACM Computing Surveys, 55(3), Article 64. https://doi.org/10.1145/3502289. Citing the published version is recommended.  [ME4]CORRECTED (verified on the journal's article page): surname 'Elshamly' (no hyphen) and five authors, not three. No issue number exists. CAUTION: this journal is reported as discontinued from Scopus (2023); reviewers may question the citation. Consider replacing it.  [ME5]CORRECTED (verified from the article PDF): first author is Md. Shafiqul Islam (M. S.); journal is IOSR Journal of Business and Management, 8(3), 39–44 (Mar.–Apr. 2013). No DOI exists. 'Retrieved from' and '(no DOI available)' removed per APA 7.  [ME6]VERIFIED (Crossref). CAUTION: IJRTE appears on a Scopus 'discontinued titles' list (publication concerns). Reviewers may question it.  [ME7]CORRECTED (verified on the SpringerOpen article page): 'Springer Open' is the platform, not the author. The authors are Park, H., & Kim, J. D.; the journal is Asian Journal of Sustainability and Social Responsibility, vol. 5, Article 5 (2020). Issue 1 is from Crossref/RePEc.

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Publication Date

10/31/2026

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