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Home » Challenges and opportunities in adopting AI for financial security in India’s growing digital economy – Firstpost
AI in Finance

Challenges and opportunities in adopting AI for financial security in India’s growing digital economy – Firstpost

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The promise of artificial intelligence (AI) to revolutionize finance is particularly compelling in India, a country striving to improve financial inclusion and security. AI offers powerful tools to expand 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 the potential of AI, India must resolve these complexities while building on its growing confidence in digital platforms. This journey will define the future of financial security in the world’s fastest growing economy.

Growing confidence in technology

The digital payments landscape in India has witnessed 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 trust presents a great opportunity to integrate AI for further innovation and system improvement.

Opportunities presented by AI

Financial inclusion: According to the Economic Survey of India 2024, bank account ownership among adults has increased to 77%, reflecting significant progress in recent years. Building on this dynamic, AI can further bridge this gap by improving the accessibility of financial services. For example, AI-driven natural language processing can enable UPI interfaces to support regional dialects, thereby eliminating language barriers and empowering rural users. Additionally, AI can analyze alternative data sources, such as mobile usage patterns, utility payments, and social behaviors, to generate credit scores for individuals and small businesses without credit history. formal credit. This approach has shown promise in countries like Kenya, where platforms like Tala use AI to assess creditworthiness based on alternative data.

Improving financial security and fraud prevention: The increase in digital payments has been accompanied by an increase in fraud, including phishing, identity theft and deepfake scams. AI can enhance financial security by analyzing transaction data in real-time to identify anomalies and flag suspicious activity. For example, Mastercard leverages GenAI-based systems to accurately detect and prevent fraud, enabling faster blocking of compromised cards. By analyzing transaction data across billions of cards and millions of merchants, the technology operates at unprecedented speeds. In India, integrating AI at the platform level can improve security through multi-modal authentication, combining device recognition, keystroke patterns and voice analytics to ensure robust protection without compromising security. user experience.

Profitability: Automating routine processes such as loan approval, risk assessment, and document verification can significantly reduce operational costs for financial institutions. For example, HDFC Bank has implemented AI-based chatbots like EVA (Electronic Virtual Assistant) to handle customer queries, thereby reducing the need for human intervention and reducing costs. These savings can be passed on to consumers, making financial services more affordable and accessible.

Challenges of AI adoption

The adoption of AI in financial systems presents immense opportunities, but it also has some significant obstacles:

Capital constraints: A major challenge is obtaining the capital needed to integrate AI into such large-scale infrastructure. The government plays a central role as a key facilitator of capital inflow. Although it has launched initiatives such as the National AI Strategy and the Digital India programme, more targeted funding is needed to support AI-focused projects in the financial sector. Public-private partnerships can play a crucial role in resource mobilization and risk sharing.

Regulatory uncertainty: Indian data privacy laws, such as the Digital Personal Data Protection Act (2023), are still evolving. The lack of clear regulation around the use of AI in finance poses risks, including unauthorized access to data and algorithmic bias. To solve this problem, India can learn from the European Union’s AI law, which emphasizes transparency, accountability and user protection. Establishing a robust regulatory framework is essential to prevent abuse and build consumer confidence.

Skills gaps: While India produces over 1.5 million engineers annually, there is a shortage of professionals with specialized AI skills. Closing this gap requires targeted education and skills development initiatives. Programs like the National AI Program, 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 key to democratizing access to AI-enabled financial services. Initiatives such as BharatNet and PM-WANI have made significant progress in bridging the digital divide, particularly in rural areas, but more remains to be done. Currently, only 57.2 percent of schools in India have working computers and 53.9 percent have internet access, and 52.3 percent are equipped with ramps, highlighting critical gaps in education. accessibility and technological readiness that must be met for widespread adoption.

The way forward

Unlocking the transformative potential of AI requires a cohesive and multifaceted approach. A key starting point is collaborative regulation, in which policymakers partner with industry leaders to design frameworks that balance innovation with ethical and safety concerns. Creating a dedicated AI regulator 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 have significantly expanded the reach of the UPI and demonstrated the power of collective action. It is equally important to strengthen the talent pipeline through AI-driven training and upskilling initiatives, with institutions like IITs and IIMs taking the lead in preparing a workforce ready for the future. Finally, for AI-based solutions to reach every corner of the country, India needs to invest heavily in infrastructure, including expanding internet connectivity and modernizing cloud systems in rural areas.

In conclusion, the future of finance in India lies in our ability to effectively leverage AI. This requires a dynamic approach that promotes innovation while ensuring inclusion and accessibility. By building a robust ecosystem that empowers both individuals and businesses and prioritizing the development of a skilled AI workforce, India can build a future where finance works for everyone.

The author is Managing Director, AI and Data Science at Nagarro. The opinions expressed are those of the author.

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