मैगज़्टर गोल्ड के साथ असीमित हो जाओ

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AI road map for financial services

Financial Express Lucknow

|

July 11, 2025

When it comes to artificial intelligence (AI) adoption in the financial services (banking, financial services, and insurance) sector, India ranks as a global leader.

- ASHVIN PAREKH

According to some recent surveys by recognized firms, more than 30% of Indian companies have been trying to or plan to maximize value from AI. Fintechs, banking, and software sectors in India are at the forefront of this, leveraging AI for tasks such as customer interface and servicing, credit risk assessments, process and control efficiencies, and automation and fraud detection.

The adoption of digital is exceptionally high, and India can boast of the highest fintech adoption. According to a survey, the adoption is 87% compared to a global average of 64%. About 46% of the world's banking digital transactions occur in India, reflecting the country's strong digital foundation.

There has been strong government backing as well as regulatory encouragement. The Reserve Bank of India (RBI) has played a significant role in both digital as well as AI adoption in banking. With the support of policymakers and regulators, the nation has built innovation and skilling hubs across several centers of excellence. Initiatives like India AI Mission and Digital India Bhashini are supporting indigenous AI models and language technologies, further strengthening the ecosystem for AI innovation and accessibility in financial services. There are guidelines and regulations framed by the regulators in areas like algorithmic trading, robo-advisory, and digital lending. The Digital Personal Data Protection (DPDP) Act establishes comprehensive data protection requirements for AI deployment in BFSI.

This article, in the backdrop of such excitement around AI, examines the ways to make AI adoption in any BFSI constituents deeper and wider. It examines the essentials and parameters to build a robust framework of governance, and critical ingredients essential for a linear and structured growth of AI application in a company. Some of the pitfalls and risk management of undesired consequences are also discussed.

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