 "Challenges and opportunities of adopting AI for financial security in India’s growing digital economy")
The promise of artificial intelligence (AI) to revolutionize finance is particularly compelling in India, a nation striving for greater financial inclusion and security. AI offers powerful tools to extend financial services to underserved populations and combat increasingly sophisticated fraud.
However, realizing this potential requires careful consideration of significant challenges, including regulatory frameworks, infrastructure limitations, and the need for a skilled workforce. To fully harness AI’s potential, India must address these complexities while building on its growing trust in digital platforms. This journey will define the future of financial security in the world’s fastest-growing economy.
A growing trust in technology
India’s digital payment landscape has experienced unprecedented growth, driven by the widespread adoption of platforms like UPI. The success of UPI highlights Indians’ strong trust and preference for digital financial services, despite safety and security concerns.
In November 2024 alone, UPI processed 15.48 billion transactions worth Rs 21,55,187 crore. This immense transaction volume and user confidence present a prime opportunity to integrate AI for further innovation and system enhancement.
Opportunities presented by AI
Financial inclusion: According to India’s Economic Survey 2024, adult bank account ownership has increased to 77 per cent, reflecting significant progress in recent years. Building on this momentum, AI can bridge this gap even further by enhancing the accessibility of financial services. For instance, AI-driven natural language processing can enable UPI interfaces to support regional dialects, breaking down language barriers and empowering rural users. Additionally, AI can analyze alternative data sources—such as mobile usage patterns, utility payments, and social behaviours—to generate credit scores for individuals and small businesses without formal credit histories. This approach has shown promise in countries like Kenya, where platforms like Tala use AI to assess creditworthiness based on alternative data.
Enhancing financial security and fraud prevention: The rise in digital payments has been accompanied by an increase in fraud, including phishing, identity theft, and deepfake scams. AI can strengthen financial security by analyzing real-time transaction data to identify anomalies and flag suspicious activities. For example, Mastercard leverages GenAI-powered systems to accurately detect and prevent fraud, enabling faster blocking of compromised cards. By scanning transaction data across billions of cards and millions of merchants, the technology operates at unprecedented speeds. In India, integrating AI at a platform level can enhance security through multi-modal authentication, combining device recognition, typing patterns, and voice analysis to ensure robust protection without compromising user experience.
Cost efficiency: Automating routine processes such as loan approvals, risk assessments, and document verification can significantly reduce operational costs for financial institutions. For instance, HDFC Bank has implemented AI-driven chatbots like EVA (Electronic Virtual Assistant) to handle customer queries, reducing the need for human intervention and lowering costs. These savings can be passed on to consumers, making financial services more affordable and accessible.
Impact Shorts
More ShortsChallenges to AI adoption
The adoption of AI in financial systems presents immense opportunities, but it also comes with a few significant hurdles:
Capital constraints: A major challenge is securing the capital needed to integrate AI into such large-scale infrastructure. The government plays a pivotal role as a key facilitator of capital inflow. While it has launched initiatives like the National AI Strategy and the Digital India program, more targeted funding is needed to support AI-driven projects in the financial sector. Public-private partnerships can play a crucial role in mobilizing resources and sharing risks.
Regulatory uncertainty: India’s data privacy laws, such as the Digital Personal Data Protection Act (2023), are still evolving. The lack of clear regulations around AI usage in finance poses risks, including unauthorized data access and algorithmic biases. To address this, India can draw lessons from the European Union’s AI Act, which emphasizes transparency, accountability, and user protection. Establishing a robust regulatory framework is essential to prevent misuse and build consumer trust.
Skill gaps: While India produces over 1.5 million engineers annually, there is a shortage of professionals with specialized AI skills. Bridging this gap requires targeted education and up-skilling initiatives. Programs like the National Program on AI, launched by NITI Aayog, are steps in the right direction. Collaboration between academia and industry can further enhance AI talent development.
Infrastructure limitations: Expanding connectivity and upgrading cloud infrastructure are essential for democratizing access to AI-driven financial services. Initiatives like BharatNet and PM-WANI have made significant strides in bridging the digital divide, particularly in rural areas, but much more remains to be done. Currently, only 57.2 per cent of schools in India have functional computers and 53.9 per cent have internet access, and 52.3 per cent are equipped with ramps, highlighting critical gaps in both accessibility and technological readiness that need to be addressed for widespread adoption.
The path forward
Unlocking AI’s transformative potential demands a cohesive and multi-faceted approach. A key starting point is collaborative regulation, where policymakers partner with industry leaders to design frameworks that balance innovation with ethical and security concerns. Establishing a dedicated AI regulatory body can ensure consistent oversight and accountability.
This effort must be complemented by public-private partnerships, exemplified by the collaboration between NPCI and Google Pay, which significantly expanded UPI’s reach and demonstrated the power of collective action. Equally important is strengthening the talent pipeline through AI-focused education and upskilling initiatives, with institutions like IITs and IIMs taking the lead in preparing a future-ready workforce. Lastly, to make AI-driven solutions reach every corner of the country, India must invest heavily in infrastructure, especially by expanding internet connectivity and upgrading cloud systems in rural areas.
To conclude, the future of finance in India rests on our ability to leverage AI effectively. This requires a dynamic approach that fosters innovation while ensuring inclusivity and accessibility. By building a robust ecosystem that empowers both individuals and businesses and by prioritizing the development of a skilled AI workforce, India can build a future where finance works for everyone.
The author is the Managing Director, AI and Data Science at Nagarro. Views expressed are the author’s own.
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