Role of Gen AI in Accelerating Digital Transformation in Financial Services: By Shuvo G Roy

We are only at the dawn of the age of AI, and are still feeling our way as we try to fathom where it will deliver the greatest benefit and, in the process, transform key aspects of our business. We have some way to go before the mist clears, but that’s what makes this such a fascinating time to be in financial services. Until recently, for example, banks’ loan underwriting and fulfilment process was heavily dependent on human beings. Now you can reconstruct this value chain using a collection of AI agents responsible for data collection, risk assessment, recommendation and loan fulfilment.

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• AI is reshaping the future of banking, offering unprecedented opportunities for innovation, efficiency, and customer-centricity.
• In Kenya, M-Pesa has integrated over 50 million users into the financial system since its inception in 2007, facilitating payments and savings through simple SMS technology.
• Initiatives such as cross-border payments and remittance solutions are pivotal in this expansion, addressing the needs of migrant workers and others who rely on international money transfers.
• AI technologies such as robotic process automation (RPA) are automating routine tasks and streamlining back-office operations, reducing manual errors and operational costs.
• We worried less about the latter when our technology was restricted to the back office and did mostly what it was told.

These systems achieved 90% accuracy in anomaly detection and contributed to a 40% reduction in fraud losses. His work directly enabled a 25% increase in product cross-selling and a 20% surge in customer investment activity, redefining how banks personalize services at scale. While it offers numerous benefits, including increased efficiency, personalized customer experiences, and data-driven decision-making, it also raises concerns regarding data privacy and potential job displacements. As banks navigate the Gen AI landscape, balancing these benefits and challenges becomes crucial.

• Additionally, AI-powered chatbots and virtual assistants can help offer 24/7 support for customers, reducing friction and improving satisfaction.
• Adarsh naidu’s work is a testament to how generative AI, when implemented with insight and integrity, can transform not just banking infrastructure, but customer experience, risk management, and revenue growth.
• This content was researched, designed, and written entirely by human writers, editors, analysts, and illustrators.
• Most importantly, AI must also be positioned as a co-pilot, augmenting human decision-making rather than replacing it.
• Digital wallets like Paytm in India further simplify banking by offering secure, cashless financial management.

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As financial institutions compete in an increasingly digital, data-driven world, generative models like GANs and LLMs are emerging as critical tools to simulate financial behaviors, personalize services at scale, and unlock new revenue streams. What was once a traditional sector built on static rules and legacy systems is now embracing AI-driven agility, personalization, and intelligence. Appian’s inclusion underscores its unique approach to embedding AI within enterprise-wide financial workflows. With Appian, financial institutions can bring AI into processes to enhance operations from risk management to operational efficiency and customer service.

His ability to merge deep technical knowhow with strategic impact positions him as a key architect of AI-driven innovation in the financial world. Despite fintech and AI advancements, challenges like poor internet infrastructure, financial illiteracy, and cultural distrust continue to hinder universal financial inclusion. In rural areas, unreliable connectivity limits access to digital banking, prompting public-private partnerships to expand network coverage.

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Insights into its potential often come from consulting reports or academic opinion pieces, which tend to be speculative and lack real-world data. By striking a balance between innovation and oversight, the banking industry can harness the full potential of Gen AI and fintech to create a more equitable and accessible global financial landscape. By leveraging data-driven insights, fintech platforms reduce risks and expand outreach, integrating more individuals into the formal economy. As these innovations evolve, they continue to break barriers and promote financial accessibility for all, driving economic growth and empowerment. At a very high level, IBM’s transformation work within financial services primarily addresses migrating infrastructure to hybrid cloud, and decoupling monolithic systems at the application level.

To unlock this, AI must be more than a patchwork of business unit projects—it must be an enterprise-wide function, much like HR or finance. That requires a dedicated AI team, led by a senior executive reporting to the COO, ensuring AI is embedded across operations, not confined to fragmented initiatives. This team should combine AI specialists with experienced business leaders— people from the spectrum of Banking products – from Money Markets to Mortgages, Prime Brokerage to POS terminals – ensure AI solutions are built with real industry insight. The presence of sensitive information across finance creates natural limits on the types of use cases that banks pursue—at least for now. Because BNY mostly operates in the institutional space, meaning it doesn’t hold consumer data like credit card or mortgage information, it has more freedom than most competitors.

The regulated space for financial services providers, including their use of chatbots, places the responsibility on banks to meet legal and compliance obligations. This ensures they protect consumers, provide accurate and reliable information and remain within industry standards and regulations. Generative AI, including platforms like ChatGPT, is transforming industries by making processes simpler, more efficient and easier to interact with. However, in the heavily regulated financial services sector the benefits also come with some serious risks. So it’s vital that this emerging technology is employed responsibly in order to maintain stability and trust.

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Digital wallets like Paytm in India further simplify banking by offering secure, cashless financial management. Advanced AI algorithms also refine financial products, from robo-advisors managing real-time investments to AI-enhanced digital payments. Meanwhile, evolving regulatory frameworks, such as those from the Federal Reserve and European Central Bank, ensure ethical AI deployment in banking. A key impact of fintech is financial inclusion, as mobile and cloud-based platforms extend services to underserved populations, stimulating economic growth. Its adaptability to consumer demands and regulatory shifts keeps it at the forefront of financial innovation.

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The global outreach of banking services, particularly to marginalized communities in developing countries, is being significantly enhanced by innovative fintech solutions and blockchain technology. Initiatives such as cross-border payments and remittance solutions are pivotal in this expansion, addressing the needs of migrant workers and others who rely on international money transfers. Platforms like Wise have revolutionized this space by drastically reducing transaction fees, making it more affordable for workers to send money back home. Meanwhile, decentralized finance (DeFi) platforms built on blockchain technology offer an alternative financial system that operates without traditional intermediaries. This not only provides financial autonomy to unbanked populations but also ensures secure, transparent transactions that bypass conventional banking’s stringent documentation requirements. But these high-cost, high-touch interactions can be less than satisfying for customers when handled through a call center if, for example, technical systems are outdated or data sources are disconnected.