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SBI promoted an AI banking panel but this text has no actual complaint against the bank

State Bank of IndiaPC-2026-03279Banking & LoansAnonymous ·
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It was a pleasure — and a real learning experience — to join the e-Panel discussion on "Banking in the Age of AI: From Cyber Threats and Consumer Privacy to Intelligent Defense" — a theme that could not be more timely for today's AI and Agentic world. Every financial institution now serves customers through AI chatbots, assistants ("May I help you?"), and a growing range of customer-facing tools. But the same tools that drive convenience can open doors to fraud, data leakage, scams, and real monetary loss — made more severe when sourced through 3rd- and 4th-party supply chains. A few notes from the discussion: 𝟭. 𝗠𝗮𝗸𝗲 𝗔𝗜 𝗮 𝗕𝗼𝗮𝗿𝗱𝗿𝗼𝗼𝗺 𝗮𝗴𝗲𝗻𝗱𝗮. Governance, monitoring, adoption, and awareness belong on the board's regular review with clear metrics — the risk is high and often unprecedented. This calls for a dedicated AI Governance Leader to ensure compliant, harmonised deployment while protecting customer trust. 𝟮. 𝗔𝗜 𝗶𝘀 𝗶𝗻𝗲𝘃𝗶𝘁𝗮𝗯𝗹𝗲; 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗔𝗜 𝗶𝘀 𝗻𝗼𝗻-𝗻𝗲𝗴𝗼𝘁𝗶𝗮𝗯𝗹𝗲. Protecting consumer data is the bank's utmost accountability. The foundations of AI — Data Risk, Model Risk, Agent Risk — are precisely where vulnerabilities emerge. 𝟯. 𝗕𝘂𝗶𝗹𝗱 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀. An AI Bill of Materials, due diligence, Explainable AI (the right to know), timely model retirement, and a Human-in-the-Loop are non-negotiable. 𝟰. 𝗠𝗶𝗻𝗶𝗺𝗶𝘇𝗲 𝗱𝗮𝘁𝗮; 𝗯𝗶𝗻𝗱 𝘁𝗵𝗲 𝗽𝘂𝗿𝗽𝗼𝘀𝗲. Data minimization and purpose limitation are key across the Data Life Cycle. Breaking AI agents into small, manageable units reduces risk and aligns with regulation. 𝟱. 𝗣𝗶𝗹𝗼𝘁 𝗯𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝘀𝗰𝗮𝗹𝗲. Test in sandbox environments with customers as pilot partners — with traceability, log management, Data Activity Management (DAM), and observability. A Test-Driven approach, resolving risks by Risk Tier (High→Low), beats doing everything at once. A disciplined lifecycle — Identify → Build → Test/Train → Log/Explain → Validate/Verify → Use → Refine → Retire — beats manual processes, handled with care. #RBI's 𝗙𝗥𝗘-𝗔𝗜 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 guides well, with its 𝟳 𝗦𝘂𝘁𝗿𝗮𝘀 (Trust, People First, Innovation over Restraint, Fairness & Equity, Accountability, Understandable by Design, Safety/Resilience/Sustainability) and 𝘀𝗶𝘅 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗣𝗶𝗹𝗹𝗮𝗿𝘀 (Infrastructure, Policy, Capacity, Governance, Protection, Assurance). The takeaway: 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗲 𝗯𝗼𝗹𝗱𝗹𝘆, 𝗯𝘂𝘁 𝗴𝗼𝘃𝗲𝗿𝗻 𝗱𝗲𝗹𝗶𝗯𝗲𝗿𝗮𝘁𝗲𝗹𝘆. Thank you to the State Bank of India team, co-panellist Sameer A., moderator S V N Murthy, under the leadership of RANJAN NAYAK (GM and Director - SBIT). Is #AI adoption and #DPDPA compliance moving in the same direction at your organization? #DPDPA #DataPrivacy #AISecurity #CyberSecurity #Banking #BFSI #AIGovernance #PrivacyEngineering #SBIT #Ardent Privacy - India (Bharat) #SBI Sameer A. • 3rd+ A veteran of the security industry (ex-Lockheed Martin, Symantec, Deloitte) Sameer’s work focuses on the intersection Data-Centric security and privacy. Helping organizations build ‘Privacy Compliance and Trustworthy AI’ 5d Follow Last week, I joined a special e-panel at @State Bank Institute of Technology (SBIT) on "Banking in the Age of AI: From Cyber Threats, Consumer Privacy to Intelligent Defense. Such as great panel ! A few themes that stood out: Cyber defense is realistically a #data #security problem even more now with AI . Attackers use AI to scale vulnerability exploitation and usual attack methods. The defense starts with knowing what data assets you hold, where it lives and who can touch it to protect. #DPDPA turns privacy into operations which starts with #personal #data #discovery. #Consent, #purpose #limitation, data minimization and #breach #management can't live in a policy itself. They have to be built into systems, workflows and vendor contracts. #AI adds a new attack surface. Training data, prompts, model outputs and third-party AI tools all carry personal data. If your AI governance isn't connected to your privacy program, you have blind spots. #Data #Minimization is a security control. The data you don't keep can't be breached, misused or fed into a model by mistake. Thank you to @Ranjan Kumar Nayak (GM & Director, SBIT) for the welcome, to my co-panelist Ramakant Mohapatra for sharing his experience, and to Mr. SVN Murty for moderating so well. And thanks to everyone from the State Bank of India community who joined and asked such sharp questions. Now I'd like to hear from you: what's the hardest part of getting #AI #adoption and #DPDPA compliance moving in the same direction at your organization? #DPDPA #DataPrivacy #AISecurity #CyberSecurity #Banking #BFSI #AIGovernance #PrivacyEngineering #SBIT Ardent Privacy - India (Bharat)

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  1. Case filed

    Filer · 3 Nov 2026, 10:28 am

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