RBI proposes tighter oversight of AI and algorithms in financial firms

The Reserve Bank of India (RBI) has released a draft framework to regulate the use of models, including Artificial Intelligence (AI) and Machine Learning (ML), by financial entities. The proposal was issued for public consultation on June 25, 2026, signalling a structured approach to AI governance.

The framework covers banks, NBFCs and other regulated entities relying on data-driven systems. It aims to address risks arising from increasing dependence on automated decision-making tools.

RBI AI Model Risk Framework Explained

The RBI has defined “models” broadly to include AI systems, algorithms, analytics tools, decision engines and even spreadsheet-based applications. This wide definition ensures that any system influencing financial or operational decisions falls within regulatory oversight.

The draft highlights that models are now central to lending, risk assessment and customer service processes. However, it also warns that improper model use can result in inaccurate outcomes and operational disruptions across institutions.

Applicability And Scope of RBI Model Guidelines

The proposed framework applies to all models used by regulated entities, irrespective of their origin. This means models developed internally as well as those sourced from third-party vendors are covered under the guidelines.

The RBI has made it clear that outsourcing does not reduce responsibility for outcomes. Entities must remain accountable for all model-driven decisions, regardless of external involvement in development or deployment.

Model Risk Classification and Approval Requirements

Under the draft, models must be categorised based on risk using factors such as complexity, business impact and consumer exposure. High-risk models will require approval from the Risk Management Committee of the Board (RMCB).

This ensures that critical systems are subject to higher levels of oversight before deployment. Risk-based classification also helps institutions allocate resources effectively for monitoring and governance.

Governance, Validation and Monitoring Standards

The framework mandates that all regulated entities establish a Board-approved Model Risk Management Framework (MRMF). This includes governance structures, validation processes, monitoring mechanisms and contingency planning.

A “three lines of defence” approach is required, involving model owners, independent validation teams and internal auditors. Additionally, all models must undergo independent validation, covering data quality, assumptions and alignment with intended use before implementation.

Model Inventory and Compliance Requirements

The RBI has proposed that no model should be deployed unless it is listed in a formal inventory maintained by the institution. This inventory will act as a central record for tracking all active and inactive models within the entity.

Decommissioned models must be retained for at least 10 years for audit and compliance purposes. These measures are aimed at improving transparency, traceability and regulatory supervision across financial institutions.

Read More: RBI Issues New TReDS Rules to Streamline MSME Participation.

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Conclusion

The RBI’s draft framework marks a structured step towards regulating AI and model usage in the financial sector. By introducing comprehensive governance, validation and accountability standards, the proposal seeks to mitigate model-related risks.

The emphasis on independent validation and risk-based classification reflects a systematic approach to oversight. Overall, the framework aims to strengthen operational resilience and ensure responsible adoption of advanced technologies in financial services.

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