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CERT-In empanelled · AI governance

AI governance for RBI-regulated entities

As banks, NBFCs and payment firms deploy AI and machine-learning models — for credit, fraud, collections and customer service — RBI’s emphasis on model risk management, data governance, explainability and accountability makes AI governance a board-level obligation. CyberSigma helps RBI-regulated entities build a defensible AI-governance programme: a model inventory and risk classification, data-governance and bias controls, human-oversight and explainability, third-party/GenAI vendor risk, and audit-ready evidence aligned to RBI expectations and the DPDP Act.

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Who needs it

Who this is for

RBI-regulated entities — banks, NBFCs, payment aggregators and lenders — deploying AI/ML for credit decisioning, fraud, collections, KYC or customer service, and their model-risk, compliance and technology functions.

Scope

What an AI-governance programme covers

Model inventory & risk classification
A living register of every AI/ML model, its purpose, data and risk tier.
Data governance & bias
Training-data lineage, quality, fairness and bias controls.
Oversight & explainability
Human-in-the-loop, challenge, monitoring and model explainability.
Third-party & GenAI risk
Vendor and GenAI/API risk, data-leakage controls and contractual safeguards.
Regulation

What it aligns to

RBI’s model risk management and data-governance expectations for regulated entities, the DPDP Act 2023 for personal data used in models, and emerging AI-governance good practice — mapped to how you actually build and buy models.

Deliverables

What you receive

AI-governance framework
Policy, roles, model-lifecycle controls and a risk-classified model inventory.
Assessment & roadmap
Gap assessment of current models with a prioritised remediation plan.
Common gaps

Common gaps we find

  • No model inventory — nobody can list the models in production
  • Training-data lineage and bias controls undocumented
  • No human-oversight or challenge process for high-impact decisions
  • GenAI/third-party model data-leakage risk unaddressed
Proof

See how we’ve done it before

Relevant case study
How a lender built a risk-classified model inventory and oversight controls. Read case studies →
Redacted sample deliverable
Inspect a redacted AI-governance assessment first. Request a redacted sample →

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AI governance for RBI entities — FAQs

Does RBI require AI governance?

RBI emphasises model risk management, data governance, explainability and accountability for regulated entities using models. AI governance operationalises those expectations, alongside the DPDP Act for personal data used in AI.

Where do we start?

With a model inventory and risk classification — you cannot govern models you have not listed. From there we prioritise controls for the highest-impact models.

Talk to an AI-governance specialist

We inventory and risk-classify your models and build a defensible governance programme aligned to RBI and DPDP. Reply within four business hours.

Book a 20-minute call →

Ready to discuss your AI governance for RBI-regulated entities requirement?

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