India AI Impact Summit 2026

ai-for-fraud-prevention-and-financial-inclusion-in-bfsi

4 min read

TRACK:Safe and Trusted AI
SPEAKERS
  • Mr Bhuvan Lodha, Mahindra & Mahindra Limited
  • Mr Manish Agarwal, Kotak811, Kotak Mahindra Bank
  • Mr Neeraj Aggarwal, BCG
  • Mr Saurabh Mittal, DBS India
  • Mr Srijay Ghosh, Temasek
  • Mr Suresh Sethi, Protean eGov Technologies
  • Shri Abhishek Singh, Ministry of Electronics & IT, GoI
SESSION OVERVIEW

This panel explores how, as BFSI systems expand through digital onboarding, payments, and credit, trust can no longer rely on manual oversight or fragmented rule-based controls. It examines AI as a core trust infrastructure—enabling real-time fraud prevention, advanced risk intelligence, and resilient cross-border controls—while ensuring explainability, privacy, auditability, and fairness. The discussion also highlights how AI-driven trust rails reduce friction and unlock financial inclusion at scale for underserved citizens and MSMEs.

VIDEO RECORDING

AI for Fraud Prevention and Financial Inclusion in BFSI

Abstract

The panel examined how AI can become the backbone of trust in the rapidly expanding BFSI (Banking, Financial Services, and Insurance) ecosystem—supporting real‑time fraud prevention, risk intelligence, and cross‑border control while also advancing financial inclusion for underserved citizens and MSMEs. The discussion moved from practical AI applications to broader themes of governance, international cooperation, and capacity‑building, culminating in a policy‑focused address that highlighted human‑centric, inclusive, and adaptive AI governance as essential to unlock the technology’s full societal benefit.

Detailed Summary

Shri Abhishek Singh opened by locating AI within the wider agenda of inclusive development:

  • Equity Impact: He argued that when AI is applied to underserved communities—optimising agriculture for smallholder farmers, delivering transparent public services, and expanding financial access—it can act as a force multiplier for equity.
  • Governance Dependency: The direction AI takes, he noted, will be shaped by the governance frameworks erected today.

2. Lessons from India’s Digital Journey

  • Scale & Accountability: India’s large‑scale digital rollout provides “useful lessons” on balancing rapid expansion with democratic accountability.
  • Key Enablers:
    • Open standards and interoperable platforms that allow diverse actors to plug into the same ecosystem.
    • Public‑private collaborations that fuel innovation while protecting citizen rights.

3. Embedding Trust through Safeguards

Shri Singh emphasized that AI must be coupled with concrete trust‑building mechanisms:

  • Grievance & Redressal: Structured pathways for citizens to raise concerns and obtain remedies.
  • Responsible Data Governance: Policies that secure privacy, ensure auditability, and prevent misuse.

4. Geopolitics, Standards, and Strategic Diplomacy

  • Intersection of Competition & Tech: He warned that geopolitical rivalry now intersects closely with technological advancement, making AI governance a strategic diplomatic issue.
  • Co‑operative Pathways:
    • Joint development of AI standards and ethical frameworks.
    • Cross‑border research partnerships to build “bridges of trust” among nations.

5. Risks of Fragmented Regulation

  • Digital Silos: Disparate regulatory regimes risk creating isolated digital ecosystems.
  • Technological Divides: Such silos could widen the gap between advanced and lagging economies, undermining inclusion goals.

6. Capacity Building Across Stakeholders

Shri Singh highlighted that regulation alone is insufficient; a broad uplift in AI literacy is required:

StakeholderNeeded Capability
Policy‑makersTechnological literacy to draft informed policies
RegulatorsAnalytical tools for monitoring AI systems
JudgesTechnical understanding to adjudicate AI‑related disputes
CitizensDigital awareness to engage safely with AI services

He stressed that democratizing AI resources must go hand‑in‑hand with democratizing knowledge and institutional capacity.

7. Three Guiding Ideas for Future Governance

  1. Human‑Centricity – Technology must serve people, not the reverse.
  2. Inclusivity – Governance structures should reflect the diversity of societies (notably referenced by “honorable members of parliament”).
  3. Adaptivity – Rules must evolve as technology evolves, preventing lagging legislation.

8. The Rule of Law as an Enabler, Not a Barrier

  • Foundation of Trust: The rule of law provides predictability, encouraging investment and fostering legitimacy.
  • Balance with Innovation: Contrary to the belief that law stifles innovation, Shri Singh framed it as a foundational element that sustains responsible innovation.

9. Trust, Transparency, and Public Acceptance

  • Fair, Transparent, Contestable AI: When citizens perceive AI systems as just and explainable, they are more willing to adopt digital financial services.
  • Trust‑Enabled Adoption: Trust is positioned as the conduit that translates technical capability into real‑world uptake, especially for the underserved.

10. Closing Call to Action

  • Beyond Labs & Boardrooms: The future of AI governance will be shaped in legislatures, courtrooms, and democratic forums such as this panel.
  • Strategic Choices: Decisions made now will decide whether AI becomes an instrument of concentration or a catalyst for empowerment.
  • Alignment with Democratic Values: He urged alignment of innovation with democratic ideals to ensure that technological progress advances human dignity.

11. Transition & Closing Ceremony

  • Following the speech, the moderator thanked the speaker and invited Kazim (presumably a senior official) to hand over commemorative mementos.
  • Participants were asked to take their places on the dais and pose for photographs before the ceremony concluded.

Key Takeaways

  • AI can accelerate equity in finance, agriculture, and public services when paired with robust governance.
  • Open standards and interoperable platforms are critical for scaling AI while safeguarding citizen rights.
  • International cooperation on AI standards and ethical frameworks is essential to prevent geopolitical fragmentation.
  • Fragmented regulations risk creating digital silos that exacerbate technological divides.
  • Capacity building—from policymakers to citizens—is a prerequisite for effective AI governance.
  • Three pillars for AI governance: human‑centric design, inclusivity, and adaptivity.
  • The rule of law should be viewed as an enabler of innovation, providing predictability and legitimacy.
  • Trust, transparency, and contestability are decisive factors for public acceptance of AI‑driven financial services.
  • Future AI governance will be decided in democratic institutions, not just in corporate labs.
  • Aligning AI innovation with democratic values will ensure the technology acts as a catalyst for empowerment rather than a tool of concentration.

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