New Delhi: 

This shift signals the RBI’s intention to modernise key functions using AI and big data, while simultaneously developing ethical guidelines to ensure responsible use of these technologies.

The Reserve Bank of India (RBI) is steadily advancing its integration of artificial intelligence and machine learning across critical financial and regulatory functions, according to its latest financial report. The central bank’s AI ambitions now span everything from fraud detection and economic forecasting to supervising banks and handling public complaints.

Framework for Responsible AI in Finance

Recognising the risks that come with rapid AI deployment, the RBI has appointed an external committee to develop a framework for the ethical and responsible use of AI in financial services. The proposed framework, titled FREE-AI (Framework for Responsible and Ethical Enablement of AI), is expected to be finalised as part of the 2025-26 agenda.

RBI Sets Up Supervisory Analytics Group, EmTech Repository

In the supervision space, the RBI has tasked its Department of Supervision (DoS) with adopting advanced technologies. To that end, a dedicated Advanced Supervisory Analytics Group (ASAG) has been established to build AI/ML-based models that support more efficient monitoring of banks and non-banking financial companies (NBFCs).

On May 28, 2024, the central bank also launched the EmTech Repository, a digital platform tracking how regulated entities are adopting emerging technologies, including AI. This repository, developed in coordination with the Reserve Bank Innovation Hub (RBIH), aims to give policymakers a clearer picture of AI deployment across the financial sector.

AI-Powered Complaint Systems and ChiRAG Platform

Efforts are also underway to enhance customer grievance handling. In collaboration with Reserve Bank Information Technology Pvt. Ltd. (ReBIT), the RBI is working on deploying a conversational AI chatbot to support the complaint management system. This is part of a phased rollout, with future updates expected to automate backend processes.

Alongside this, the RBI has developed an in-house generative AI tool named ChiRAG (Chat Interface with Retrieval Augmented Generation). Initially used for internal information retrieval, ChiRAG has the potential to become a centralised interface for accessing the RBI’s vast datasets.

Fighting Financial Fraud with MuleHunter.ai

The RBI Innovation Hub has also developed a machine learning model named MuleHunter.ai, aimed at identifying mule accounts used in fraud schemes. Described as a supervised ML model that operates in near real-time, the tool is currently being piloted in major public sector banks. The FinTech Department has listed its expansion as a key priority for 2025-26.

Forecasting Inflation, GDP, and Sentiment with AI

The Department of Statistics and Information Management (DSIM) is actively using AI/ML for economic modelling and forecasting. The RBI report highlights the use of large language models (LLMs) to forecast short-term macroeconomic indicators like GDP and Gross Value Added (GVA). LLMs are also being tested for cleaning datasets and extracting insights to improve accuracy in inflation prediction models.

Additionally, AI/ML-based sentiment analysis tools are tracking narratives from media coverage to supplement traditional business surveys and economic indicators.

Machine learning is already being used to build inflation forecasting models for both headline and core CPI, including specific models for wheat and onion prices. These models combine structured and unstructured data, and the RBI plans to incorporate climate data into these tools in the near future.

More Departments Exploring AI Adoption

AI pilots are also being considered in other departments. The Inspection Department is evaluating its potential use in internal audits, while the Legal Department plans to publish a research paper on the role of AI in enhancing legal functions within the financial sector.

As per the report, the RBI’s push into artificial intelligence is becoming a cornerstone of its long-term digital strategy.

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