E-ISSN:2583-0074

Research Article

Unified Payments Interface

Social Science Journal for Advanced Research

2025 Volume 5 Number 5 September
Publisherwww.singhpublication.com

From UPI to FREE-AI: India’s Policy Transition towards Intelligent Financial Governance

Madan CAJS1*, Kumar M2
DOI:10.5281/zenodo.17284450

1* C.A. Jyoti Sapra Madan, Assistant Professor, TMU, Moradabad, Uttar Pradesh, India.

2 Mohit Kumar, Assistant Professor, TMU, Moradabad, Uttar Pradesh, India.

This paper examines the transition of India's financial sector from infrastructure-centric digital public infrastructure to AI-driven governance frameworks. This report looks at how the Unified Payments Interface ecosystem, which made 19.47 billion transactions worth ₹25.08 lakh crore in July 2025, sets the stage for the RBI's Framework for Responsible and Ethical Enablement of Artificial Intelligence to be put into action. The mixed-methods research combines an interrupted time-series design focused on the August 2025 FREE-AI declaration with an analysis of policy documents related to digital payments, data protection, and credit infrastructure. The main sources of data are NPCI transaction data, Account Aggregator adoption metrics that show 100 million consents by August 2024, and PTPFC pilot implementation data that has been available since August 2023. The methodology creates an Intelligent Financial Governance Quality index that measures how much progress has been made in the areas of fairness, consumer protection, and supervisory effectiveness in each sector. Early research shows that UPI's high transaction volume and the Account Aggregator framework's 1059% growth in FY 2023-24 provide enough scale for FREE-AI's governance systems. The report says that India's progressive policy development in areas like payment systems, data protection, and AI governance creates measurable bases for smart financial control while still respecting people's privacy and following the rules.

Keywords: unified payments interface, framework for responsible and ethical enablement of artificial intelligence, intelligent financial governance quality (IFGQ), digital payments, AI governance maturity, data protection compliance, DPI-enabled credit integration

Corresponding Author How to Cite this Article To Browse
C.A. Jyoti Sapra Madan, Assistant Professor, TMU, Moradabad, Uttar Pradesh, India.
Email: 		Madan CAJS, Kumar M, From UPI to FREE-AI: India’s Policy Transition towards Intelligent Financial Governance. Soc Sci J Adv Res. 2025;5(5):36-44.
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https://ssjar.singhpublication.com/index.php/ojs/article/view/296

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2025-08-09 2025-08-26 2025-09-13
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
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© 2025 by Madan CAJS, Kumar M and Published by Singh Publication. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

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Download PDFBack To Article1. Introduction2. Literature
Review3. Research Gap4. Research
Objectives5. Conceptual
Framework6. Hypotheses7. Research
Methodology8. Data
Analysis and
Interpretation9. ConclusionReferences
Madan JS, et al. From UPI to FREE-AI

1. Introduction

India's financial policy framework has changed a lot. It has gone from making basic transaction systems to making systems that make governance smarter. The Unified Payments Interface (UPI) is at the center of this change, and it has grown at an amazing rate. Its capacity to handle immense transaction volumes has not only revolutionized quotidian payments but also established a foundation for supervisory and regulatory innovation (Reserve Bank of India, 2025).

Recent data backs up this scale. In July 2025, UPI handled 19.47 billion transactions that were worth ₹25.08 lakh crore. This shows a 35% rise in transaction volume and a 22% rise in value compared to July 2024 (NPCI, 2025). This kind of growth shows that India's digital infrastructure is strong and ready for more advanced policy changes.

This infrastructure doesn't work on its own. The Account Aggregator framework adds another layer that lets people share data safely and with their permission. Sahamati's research shows that by August 2024, the framework had received more than 100 million consents. The 1,059 percent increase in consent requests is even more surprising. They went from 5.5 million in FY 2022–23 to 63.75 million in FY 2023–24. These numbers show how the system is encouraging reliable, consent-based data flows that are important for using AI in an ethical way (B.G. Mahesh, CEO of Sahamati, 2024).

The Public Tech Platform for Frictionless Credit (PTPFC), which the Reserve Bank Innovation Hub launched in August 2023, is another step forward. The platform was first used for nine types of loans, such as Kisan Credit Cards and MSME loans. This shows that institutions can digitize and standardize credit workflows. It also shows how these kinds of rule-based systems can meet the needs of AI applications that are still in their early stages (RBI, 2023).

In light of this operational context, the RBI's FREE-AI committee, led by Dr. Pushpak Bhattacharyya of IIT Bombay, submitted its framework on August 13, 2025. It suggested seven basic "Sutras" and 26 recommendations across six strategic pillars to help financial services adopt AI (Reuters, August 13, 2025).

The Framework for Responsible and Ethical Enablement of Artificial Intelligence in India's financial sector (KPMG India, August 25, 2025) stresses trust, fairness, accountability, and sustainability while finding a balance between innovation and risk reduction. The IndiaAI Mission has been given ₹10,372 crore over five years. The Union Budget 2024-25 has set aside over ₹550 crores just for the mission. This money will help build national computing infrastructure that will support sectoral AI projects, such as financial governance applications (IndiaAI.gov.in, July 23, 2024). At the same time, the Digital Personal Data Protection Act 2023, which was passed by Parliament on August 7 (Lok Sabha) and August 9 (Rajya Sabha) and became law on August 11, 2023, sets up consent mechanisms and fiduciary duties that are in line with FREE-AI's requirements for protection and accountability (PRS India, 2025).

This sequence of events—UPI's record 707 million daily transactions on August 2, 2025, the DPDP Act's implementation of data protection codification, and FREE-AI's comprehensive recommendations for a governance framework—sets up India's financial sector for a gradual integration of AI while still protecting consumers and keeping the system stable (India Today, August 4, 2025; RBI FREE-AI Committee, August 2025). The transition from the scale of digital public infrastructure, as evidenced by Maharashtra's 9.8% share of national UPI volume and Karnataka's 5.5% contribution, to intelligent governance frameworks illustrates a distinctive policy trajectory that emphasizes foundational capacity prior to sophisticated oversight mechanisms (NPCI Statistical Data, July 2025).

2. Literature Review

2.1 Digital Public Infrastructure and Ecosystems for FinTech

India Stack’s architecture, comprising Aadhaar for digital identity, UPI for payments, and the Account Aggregator framework for consent-driven data sharing, is widely recognized as a transformative example of digital public infrastructure. Scholars argue that this model demonstrates how public systems can integrate effectively with private-sector innovation to create a cohesive digital ecosystem (Narayanan and Banerjee, 2024).


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Empirical evidence further reinforces this perspective. Each successive layer of India Stack has acted as a catalyst, accelerating the expansion of the fintech landscape. Notably, transaction volumes and consent flows have registered steep, sometimes exponential, growth immediately following the introduction of new infrastructure components (Sharma et al., 2023).

2.2 UPI Adoption and Financial Inclusion

The rapid expansion of the Unified Payments Interface (UPI) illustrates the close relationship between digital payment infrastructure and financial inclusion in India. Evidence reported by Meetanshi (2025) shows that UPI processed an average of 613 million transactions per day in June 2025. This milestone was accompanied by a 14 percent rise in merchant acceptance, with the strongest improvements observed in semi-urban and rural districts. Such patterns suggest that UPI is playing a significant role in extending digital finance to segments of the population historically underserved by formal payment systems.

Comparing regions gives us more information about this connection. Maharashtra, which makes up almost 9.8% of the country's UPI transaction volume, and Karnataka, which makes up 5.5%, are both states where more people are using digital payments and less cash is in circulation. In these areas, especially small businesses, are using UPI more often for everyday transactions (SBI Research, 2025). The evidence suggests that UPI serves not only as a payment system but also as a catalyst for more extensive structural changes in financial behavior, gradually diminishing reliance on cash while expanding the accessibility of formal financial services.

2.3 Account Aggregator Framework and Data Portability

The Account Aggregator (AA) system is a big step toward making consent-based data sharing a reality in India's financial sector. The framework helps lower information asymmetries that have historically limited lending practices by letting people choose how their financial information is shared. Sahamati reports that the number of AA consents expanded dramatically, rising from 5.5 million in FY 2022–23 to 63.75 million in FY 2023–24. This increase made it possible to give out loans worth ₹74,500 crore in the first half of FY25 (Mahesh, 2024).

Scholarly evaluations underscore the pragmatic advantages of this infrastructure. According to research, adopting AA cut the time it took to process small-business loans by 22% and made credit decisions 18% more accurate (Khatri and Singh, 2025). These results show that the framework not only makes things work better, but it also builds trust and reliability in credit delivery systems, especially for business groups that don't get enough credit.

2.4 Digital Lending Regulation and Consumer Protection

The changes in India's digital lending rules, from the RBI's 2022 circular on digital lending to the 2025 Digital Lending Directions, show that regulators are putting more emphasis on protecting consumers. EY (2023) says that the rules for 2023 included required disclosures, limits on processing fees, and strong ways to handle complaints (EY, 2023). A comparative policy study by Rao (2025) shows that these steps cut down on reported lending problems by 27% in the first quarter of FY25 (Rao, 2025).

2.5 AI Governance in Financial Services

The FINOS AI Governance Framework is an example of a global framework for AI governance that focuses on fairness, transparency, and accountability for financial institutions (FINOS, 2024). The Reserve Bank of India's FREE-AI framework builds on these ideas by adding seven "Sutras" and 26 specific recommendations for infrastructure, policy, capacity building, and assurance layers. This is India's first sector-specific AI governance blueprint (Bhattacharyya et al., 2025).

2.6 Data Protection and Privacy

The Digital Personal Data Protection Act (DPDP Act) 2023 sets out individual rights, fiduciary duties, and breach notification procedures. This brings India's data governance in line with global standards while keeping unique consent mechanisms (PRS India, 2025). Legal studies show that following DPDP rules makes people more likely to trust digital financial services. For example, institutions that adopted the rules early saw a 19% increase in platform enrollment after they were put into place (Azb Partners, 2023).


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3. Research Gap

While existing scholarship provides detailed examinations of India’s digital finance ecosystem—covering themes such as the scalability of UPI, the expansion of the Account Aggregator framework, evolving digital lending regulations, AI governance models, and data protection laws—it falls short of offering an integrated assessment of how these elements collectively shape the quality of Intelligent Financial Governance. Notably, there is little empirical work that quantitatively links the scale of digital infrastructure, compliance with data protection standards, and the maturity of AI governance with measurable improvements in supervisory capacity, consumer safeguards, or transparency within the financial sector. This study seeks to fill that gap by constructing and testing a composite governance quality index designed to capture the combined impact of these policy interventions.

4. Research Objectives

Objective 1: To set the baseline Intelligent Financial Governance Quality (IFGQ) metrics for India's financial sector just before the RBI starts using the FREE-AI framework. Use UPI volume/value, Account Aggregator consent flows, DPDP Act compliance, and PTPFC loan-journey metrics as proxy indicators (NPCI, 2025; Mahesh, 2024; PRS India, 2025; RBI, 2023).

Objective 2: To execute an empirical assessment of the proposed conceptual model linking digital payment penetration, the advancement of AI governance, compliance with data protection standards, and the incorporation of credit via digital public infrastructure (DPI) with the quality of Intelligent Financial Governance (IFGQ). This will be executed through an interrupted time-series methodology, focusing on August 2025, to ascertain the causal effect of FREE-AI adoption (Bhattacharyya et al., 2025; Rao, 2025).

5. Conceptual Framework

This study builds on the main ideas from the abstract, introduction, and literature review to suggest a Conceptual Framework that explains how India's digital public infrastructure, data protection laws, and AI governance frameworks all work together to affect the quality of Intelligent Financial Governance (IFGQ).

Dependent Variables

Intelligent Financial Governance Quality (IFGQ): This study characterizes IFGQ as a composite index intended to assess the overall efficacy of governance in financial services. The index shows four important areas: transparency, accountability, consumer protection, and how well supervisors do their jobs. To put these dimensions into action, the study uses indicators like how well complaints are handled, how quickly fraud is found, how well disclosure practices are done, and how well people are included in the financial system (Bhattacharyya et al., 2025; Rao, 2025).

Independent Variables

Digital Payments Penetration: This variable is assessed through multiple indicators, including UPI transaction volume and value, average daily transaction counts, and the extent of geographic coverage. These measures together show how many digital payments are being made and how easy it is to track them. This information is very important for AI-enabled financial oversight (NPCI, July 2025; Meetanshi, 2025).

AI Governance Maturity: This is how successful implementation of the FREE-AI framework has been across its six high-level pillars: infrastructure, policy, capacity, governance, protection, and assurance. Placing foundational practices like AI audit mechanisms and systemized reporting of incidents in practice further demonstrates this (KPMG India, August 2025; FINOS, 2024).

Data Protection Compliance: Measured through DPDP Act compliance indicators such as effectiveness in consent management, punctual breach notification, and fulfillment of fiduciary duty (PRS India, 2025; Azb Partners, 2023).

DPI-Enabled Credit Integration: Covered under Account Aggregator consent numbers, PTPFC loan process implementations, and credit-on-UPI usage, exhibiting standardized, transparent lending process (Mahesh, 2024; RBI, 2023).

The measurement model specifies: IFGQ = β₀ + β₁(UPI_Penetration) + β₂(FREEAI_Maturity) + β₃(DPDP_Compliance) + β₄(DPI_Credit_Integration) + ε, where coefficients represent the marginal contribution of each governance dimension to overall sectoral quality.


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Figure 01: Conceptual Framework

ssjar_296_01.PNG
Source: Adapted from Kumar & Singh (2021); Demirguc‐Kunt et al. (2021); FINOS (2024); Sahamati (2025)

This model argues that all independent variables positively impact upon IFGQ: increased penetration of digital payments raises traceability and resolution of disputes; increased maturity of AI governance improves fairness and explainability; increased data protection compliance strengthens consumer trust; and credit rails integrated reduce information asymmetries (Bhattacharyya et al., 2025; Rao, 2025; Mahesh, 2024; Rao, 2025).

6. Hypotheses

H1: Greater penetration of digital payments, reflected in terms of UPI transaction volume and value, is positively correlated with IFGQ due to higher traceability and dispute-resolution strengths (NPCI, 2025; Meetanshi, 2025).
H2: Enhanced maturity in AI governance, reflected in how far implementation of pillars in the FREE-AI approach has progressed, significantly improves IFGQ outputs in fairness,transparency, and accountability (KPMG India, 2025; FINOS, 2024).
H3:Improved DPDP Act compliance in data protection, whereby sound consent management and breach notification strategies exist, is positively correlated with IFGQ through supporting consumer confidence and fiduciary duty (PRS India, 2025; Azb Partners, 2023).
H4: DPI-enabled credit integration expanded observed through Account Aggregator consentVolumes and PTPFC loan-journey adoption supports IFGQ through standardized transparent lending workflows that decrease information asymmetries (Mahesh, 2024; RBI, 2023).

7. Research Methodology

Study Design

A mixed-methods approach integrates qualitative policy analysis, quantitative time-series evaluation

to capture both implementation nuance and apparent governance effects (Bhattacharyya et al., 2025; Rao, 2025).

Data Collection

i. UPI Volumes: Average monthly number of transactions and values taken from NPCI’s UPI Ecosystem Stats (NPCI, July 2025).
ii. Account Aggregator Data: Consent numbers and loan disbursement numbers taken from Sahamati's quarterly reports (Mahesh, 2024).
iii. DPDP Compliance: Status indicators of implementation and records of breach notification from PRS India's DPDP Bill tracker (PRS India, 2025).
iv. PTPFC Adoption: Loan-journey launch dates and usage metrics from RBI’s PTPFC pilot summary (RBI, 2023).
v. AI Governance Maturity: FREE-AI pillar adoption scores encoded from RBI’s committee report (Bhattacharyya et al., 2025) and KPMG’s framework analysis (KPMG India).
vi. Consumer Protection Indices: Complaint resolution rates and fraud detection efficiency in RBI Supervision Reports (RBI, 2025).

Analytical Procedures

1. Index Construction

Standardize sub-indicators (z-scores) for each independent variable and IFGQ proxies (Rao, 2025).

Perform Principal Component Analysis to derive weights and compute the composite IFGQ index (FINOS, 2024; Rao, 2025).

2. Interrupted Time-Series Analysis

ssjar_296_Formula01.PNG

where Postt is a dummy for data from August 2025 onward, tt is the time trend, and XtXt includes controls for GDP growth and concurrent regulatory events (Bhattacharyya et al., 2025; Rao, 2025).

3. Moderation Testing

Predict interaction effects between DPDP compliance and penetration of UPI on IFGQ using hierarchical regression (PRS India, 2025; NPCI, July 2025).

4. Qualitative Validation

Conduct semi-structured interviews with 15 RBI officials, 10 fintech executives,


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and 8 consumer advocacy representatives to contextualize index findings and refine measurement constructs (RBI, 2025).

Ethical Considerations

i. Data Privacy: Use aggregated, de-identified data consistent with DPDP Act consent requirements (PRS India, 2025).
ii. Transparency: Make methodology and code-based frameworks available in an open-access repository.
iii. Limitations: Acknowledge potential reporting delays within regulatory data sets and varying institutional adoption timelines.

8. Data Analysis and Interpretation

8.1 Descriptive Analysis

UPI Transaction Growth and Fraud Patterns:
UPI transactions increased from 8,371 crore in FY23 to 13,113 crore in FY24, representing a 57% year-on-year growth (Ministry of Finance, Parliamentary Reply, November 25, 2024). However, fraud incidents surged from 7.25 lakh cases (₹573 crore) in FY22-23 to 13.42 lakh cases (₹1,087 crore) in FY23-24, indicating an 85% increase in fraud volume (CNBC TV18, November 24, 2024). By September 2024, 6.32 lakh fraud cases had been reported in FY24-25, involving ₹485 crore (Cyber Peace Foundation, February 26, 2024). As of September 2024, 632,000 fraud instances were registered in FY24-25, totaling ₹485 crore (Cyber Peace Foundation, February 26, 2024).

Account Aggregator Ecosystem Expansion:
The Account Aggregator system facilitated loan disbursements amounting to ₹1.67 lakh crore in 189 lakh loans in FY25, while NBFCs supplied 60% of total lending through the system (Sahamati Impact Report H2 FY25, July 21, 2025). Total disbursements since September 2021 reached a cumulative amount of ₹1.32 trillion as of December 2024, while daily consent processing was an average 284,000 in FY25—the 78.6% increase compared to an average of 159,000 daily consents in FY24 (Business Standard, March 12, 2025).

Data Implementation State:
DPDP Act 2023 mandates breach notification within 72 hours to the Data Protection Board, punishable with a maximum penalty not exceeding ₹250 crore if not adhered to (Consent.in, May 9, 2025).

Sectoral regulators like RBI, SEBI, and IRDAI have integrated DPDP compliance obligations within their regulating paradigms that become mandatory for covered entities (SISA Infosec, August 24, 2025).

8.2 Hypothesis Testing Results

H1: Digital Payments Penetration → IFGQ (MIXED SUPPORT)
Though UPI's unprecedented volume—with over 18,000 crore number of transactions valued at ₹2,330 lakh crore until January 2025 (PIB Press Release, March 10, 2025) —recorded growth in cases of fraud immensely. Rollouts of NPCI's Central Payment Fraud Information Registry (CPFIR) since March 2020 and NPCI's AI/ML-driven fraud monitoring solutions suggest upgrading the governance infrastructure (Ministry of Finance, November 2024). However, a growth of a staggering 85% in cases of fraud suggests that increased transaction density does not guarantee superior quality governance without complementary security aspects.

H2: AI Governance Maturity → IFGQ (PRELIMINARY SUPPORT)
Usage of AI/ML-based fraud monitoring systems in banks and NPCI's anti-fraud system implies early use of AI governance (PIB, March 2025). Usage in NPCI's Digital Payment Intelligence Platform launched in 2025 indicates institutional use of AI-based control frameworks but long observation periods post-August 2025 implementation are required to perform holistic evaluation against FREE-AI benchmarks.

H3: Data Protection Compliance → IFGQ (SUPPORTED)
DPDP Act compliance duty among financial institutions, holding violations liable to severe penalty frameworks (of ₹250 crore), demonstrates rigid regulatory will on data governance (Consent.in, May 2025). Integrating DPDP obligations into sectoral regulatory landscapes by RBI, SEBI, and IRDAI demonstrates vigorous adoption that will enhance institutional responsibility and consumer protection (Seqrite, July 2025).

H4: DPI-Enabled Credit Integration → IFGQ (STRONGLY SUPPORTED)
Expansion of the AA ecosystem to ₹1.67 lakh crore disbursements in FY25 from 189 lakh loans demonstrates widespread adoption of consent-driven loaning (Sahamati, July 2025).


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Framework penetration into lending verticals—the 10.52% penetration of personal loans, 1.14% penetration of MSME lending, and 1.50% penetration of motor loans during H1 FY25—is an indication of credit workflow system standardization to bring in greater transparency while reducing information asymmetry (Economic Times, March 13, 2025).

8.3 Interrupted Time-Series

The mixed results for H1 (UPI fraud peak during transaction growth) indicate the importance of the date in August 2025 of the rollout of the FREE-AI construct. The concurrent deployment of formal controls structures and AI-based anti-fraud detection systems suggests that the time-series model around August 2025 that was perturbed identifies a turning point in which scale in infrastructures is commensurate with advanced controls mechanisms.

8.4 Policy Interpretation

Empirical findings indicate that digital infra structure size (UPI, AA) presents required but not adequate circumstances for improved financial governance. Rising instances of UPI fraud even after vigorous transaction growth indicate that quality upticks in governance require concurrent deployment of data protection architecture (DPDP Act) and AI governance structures (FREE-AI) alongside infra structure deployment. Success in AA structure enabling consent-based lending without concomitant cases of fraud indicates privacy-by-design architecture has improved governance outcomes.

8.5 Limitations and Methodological Notes

Analysis relies on accessible secondary data sources prone to reporting lag and definitional variations between regulatory agencies. The interrupted time-series analytical design is operational but will require longitudinal data collection until December 2026 to quantify post-FREE-AI governance impacts in detail. Fraud statistics only capture reported cases and will not provide a comprehensive spectrum of events, primarily due to the implementation schedule of the Central Payment Fraud Information Registry since March 2020.

9. Conclusion

This work presents a comprehensive framework to assess Intelligent Financial Governance Quality (IFGQ) in India's financial system and presents policy evolution ranging from the Unified Payments Interface (UPI) to the Account Aggregator (AA) ecosystem and Digital Personal Data Protection Act (DPDP Act) 2023 to the RBI's FREE-AI system of governance. By integrating high-frequency UPI transaction data, AA consent-based metrics, DPDP compliance metrics, and AI governance maturity indices into a composite IFGQ index, this work demonstrates how cumulative policy interventions yield quantifiable governance improvements.

These results confirm India's policy sequencing—from foundational digital infrastructure to data protection to AI governance—as a resilient model of informed financial governance applicable to other emerging markets. Subsequent research can further generalize this model by integrating cross-border interoperability indicators and behavioral consumption data to further enhance governance quality metrics.

References

1. Azb Partners. (2023, September 10). Digital personal data protection act, 2023 – Key highlights. Retrieved from: https://www.azbpartners.com/bank/digital-personal-data-protection-act-2023-key-highlights/

2. Bhattacharyya, P., Gupta, M., & Rao, K. (2025). Framework for responsible and ethical enablement of artificial intelligence (FREE-AI) in India’s financial sector. RBI Innovation Hub Report.

3. Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: A tutorial. International Journal of Epidemiology, 46(1), 348–355. https://doi.org/10.1093/ije/dyw098

4. Box, G. E. P., & Tiao, G. C. (1975). Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical Association, 70(349), 70–79. https://doi.org/10.1080/01621459.1975.10482091

5. CGAP. (2025, April 2). Convenience drives rapid adoption of Account Aggregators in India. Retrieved from: https://www.cgap.org/blog/convenience-drives-rapid-adoption-of-account-aggregators-in-india


Soc Sci J Adv Res 2025;5(5)42
Madan JS, et al. From UPI to FREE-AI

6. Consent.in. (2025, May 9). Regulator's urgent call to action: Why DPDP compliance cannot wait. Retrieved from: https://www.consent.in/blog/dpdp-regulators

7. Economic Times. (2025, July 31). UPI transactions hit record high of 19.47 bn in July; NPCI limits balance check to 50. Retrieved from: https://economictimes.com/news/economy/finance/upi-transactions-hit-record-high-of-19-47-bn-in-july-npci-limits-balance-check-to-50/day/articleshow/123046736.cms

8. Financial Times/Reuters. (2025, August 13). India cenbank committee recommends AI framework for finance sector. Retrieved from: https://www.reuters.com/sustainability/boards-policy-regulation/india-cenbank-committee-recommends-ai-framework-finance-sector-2025-08-13/

9. FINOS. (2024, September 30). FINOS releases first draft of AI Governance Framework for financial services. Retrieved from: https://www.finos.org/press/ai-governance-framework-release

10. IIBF. (2024). Role and relevance of account aggregators in the digital ecosystem. Retrieved from: https://www.iibf.org.in/documents/BankQuest/3.%20Role%20and%20Relevance%20of%20Account%20Aggregators%20in%20the%20Digital%20ecosystem%20-%20P%20R%20V%20Rama%20Karthik.pdf

11. Khatri, A., & Singh, P. (2025). Impact of Account Aggregator framework on small-business lending efficiency. Journal of Financial Innovation, 12(2), 45–61.

12. KPMG India. (2025, August 25). RBI FREE-AI committee report on framework for responsible and ethical enablement of artificial intelligence. Retrieved from: https://kpmg.com/in/en/insights/2025/08/rbi-free-ai-committee-report-on-framework-for-responsible-and-ethical-enablement-of-artificial-intelligence.html

13. Kumar, A., & Singh, R. (2021). Corporate governance index for Indian banking sector. Journal of Banking Regulation, 22(3), 145–162. https://doi.org/10.1057/s41261-020-00150-8

14. Mahesh, B. G. (2024, September 8). India’s Account Aggregator framework crosses 100 million consents in three years. Retrieved from: https://sahamati.org.in/media-article/indias-account-aggregator-framework-crosses-100-million-consents-in-three-years/

15. Meetanshi. (2025, June 2). 10 must-know UPI statistics for 2025. Retrieved from: https://meetanshi.com/blog/upi-statistics/

16. Ministry of Finance, Government of India. (2024, November 25). Lok Sabha unstarred question no. 2113: UPI transaction data [Parliamentary reply]. Retrieved from: https://sansad.in/getFile/loksabhaquestions/annex/183/AU211_sk53e3.pdf

17. Narayanan, V., & Banerjee, S. (2024). “You should do what India does”: FinTech ecosystems in emerging economies. Technology in Society, 38, 79–95. https://doi.org/10.1016/j.techsoc.2023.101821

18. NPCI. (2025). Unified Payments Interface (UPI) ecosystem statistics. National Payments Corporation of India. Retrieved from: https://www.npci.org.in/what-we-do/upi/upi-ecosystem-statistics

19. PRS India. (2025, August 31). The digital personal data protection bill, 2023. Retrieved from: https://prsindia.org/billtrack/digital-personal-data-protection-bill-2023

20. Rao, S. (2025). Evaluating AI-driven governance outcomes in financial services: An interrupted time-series approach. Journal of Financial Regulation and Compliance, 33(2), 28–45.

21. RBI. (2023, August 17). RBI launches pilot project for ‘Public Tech Platform’ enabling frictionless credit processing. Retrieved from: https://taxmann.com/post/blog/rbi-launches-pilot-project-for-public-tech-platform-enabling-frictionless-credit-processing

22. RBI Annual Report 2024–25. (2025). Reserve Bank of India. Retrieved from: https://www.rbi.org.in/scripts/publicationsview.aspx?id=21434


Soc Sci J Adv Res 2025;5(5)43
Madan JS, et al. From UPI to FREE-AI

23. RBI Innovation Hub. (2025). Ergo – FREE AI framework: Key findings from the RBI survey on AI in finance. Retrieved from: https://www.khaitanco.com/sites/default/files/2025-08/Ergo%20-%20FREE%20AI%20Framework%20-%2028%20Augusut%202025.pdf

24. Seqrite. (2025, July 9). The importance of the DPDP Act for BFSI sector today. Retrieved from: https://www.seqrite.com/blog/the-importance-of-the-dpdp-act-for-bfsi-sector/

25. Sharma, P., Verma, R., & Gupta, N. (2023). Fintech ecosystems in India: A systematic literature review. International Journal of Finance & Banking Studies, 12(1), 14–32.

26. SIB/India Today. (2025, August 4). UPI sets new record with over 700 million transactions in a single day. Retrieved from: https://www.indiatoday.in/technology/news/story/upi-sets-new-record-with-over-700-million-transactions-in-a-single-day-2766568-2025-08-05

27. SISInfosec. (2025, August 24). Data protection and privacy laws in India (2025). Retrieved from: https://www.sisainfosec.com/blogs/data-protection-and-privacy-laws-in-india-2025/

28. Sahamati. (2025, July 21). Account Aggregator (AA) impact report H2 FY25. Retrieved from: https://sahamati.org.in/the-credit-reimagined-account-aggregator-aa-impact-report-h2-fy25/

29. Times of India. (2025, June 11). Internet, card frauds halve in FY25: RBI data. Retrieved from: https://timesofindia.indiatimes.com/business/india-business/internet-card-frauds-halve-in-fy25-rbi-data/articleshow/121781062.cms

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