The All India Bank Officers’ Confederation (AIBOC), representing over 3.25 lakh bank officers nationwide, has strongly cautioned the Reserve Bank of India (RBI) against pushing through its proposed “Framework for Responsible and Ethical Enablement of Artificial Intelligence” (FREE-AI) without wider consultation.
In a statement issued to Kashmir Age newspaper, AIBOC said the framework, though well-intentioned, risks undermining both banking officers and consumers if imposed in a “top-down, time-bound manner” without structured dialogue. The union warned that hasty adoption of artificial intelligence in banking could expose public sector banks to legal uncertainty, operational risks, consumer harm, and greater stress on already strained resources.
“Technology cannot be a substitute for public trust,” AIBOC said, noting that the RBI’s so-called Seven Sutras—Trust, People-First, Fairness, Accountability, Understandability, Safety, and Innovation—must be translated into enforceable rights and protections rather than remain aspirational principles.
Key Concerns Highlighted
AIBOC’s detailed analysis of the framework flagged eight critical issues that need urgent attention:
Legal and Compliance Risks: AI cannot dilute existing compliance obligations, yet responsibility between banks and technology vendors remains unclear. Explicit liability clauses, adverse action protocols, and audit-ready model documentation are necessary, AIBOC argued.
Employee Accountability: Since bank staff will still execute AI-driven decisions, the union insisted officers not be made scapegoats for system-led errors. It sought RACI-based accountability, incident registers, and HR protections.
Operational Risks: Issues like model drift, bias, hallucinations, adversarial attacks require advanced safeguards including red-teaming, AI threat playbooks, and strong business continuity mechanisms.
Unequal Playing Field: Early adopters—mostly private banks—may get ahead due to higher resources. AIBOC urged the government and RBI to build shared AI infrastructure and sandboxes accessible to public banks and rural institutions.
Inclusion Concerns: The union demanded a Right to Human Review, protection against algorithmic-only loan denials, bias testing across socio-economic attributes, and local-language, outcome-specific explanations for customers.
Job Security: Automation must not translate into job losses. AIBOC called for a no-forced-redundancy covenant, large-scale upskilling for staff, and joint committees to monitor impacts.
Financial Stability: Misclassified AI-driven credit risk ratings could worsen NPAs. The Confederation pushed for stress testing, override tracking, and post-outcome monitoring.
Impact on Inequality: AI must not privilege data-rich corporates while excluding small borrowers and rural customers. AIBOC wants explicit rural credit targets and public funding for safe AI experimentation.
Global Parallels
The Confederation highlighted that trade unions worldwide are demanding worker-first AI adoption. The Australian Council of Trade Unions has called for mandatory AI implementation agreements, while unions in the US like AFL-CIO and Teamsters are pushing for laws mandating human oversight in AI-driven decisions. Similar movements in Australia and Europe back large-scale retraining, transparent use of AI, and job protections.
Demands to RBI and Government
Summing up, AIBOC pressed for:
A National Council on AI in Banking with trade union, consumer, and civil society representation.
A phased adoption with moratorium on high-risk AI use until regulatory safeguards are in place.
Job security guarantees, funded upskilling, and HR safeguards.
Mandatory consumer rights: disclosures, human review, adverse action notices, fair compensation for harm.
Equal footing for PSBs and RRBs through shared infrastructure, multilingual models, and budgetary support.
Vendor accountability with AI-specific outsourcing clauses and regulatory attestations.
“Dialogue First, Deployment Next”
AIBOC General Secretary Rupam Roy summed up the Confederation’s stand, stating:
“Responsible AI can strengthen public trust only if it is built with the participation of workers and customers. Dialogue first, deployment next—that is the path to innovation with accountability.”
