The Indian Economic Survey 2025 indicated the growing adoption and impact of generative AI within India’s banking sector. It pointed out that several financial institutions and banks in India are increasingly leveraging AI to enhance their operations, improve customer experiences, and streamline services.
However, alongside these advancements, challenges related to security and scaling remain. This is what AWS is trying to solve, offering solutions designed to address these concerns.
In an exclusive interview with AIM, Kiran Jagannath, head of financial services and conglomerates at Amazon Web Services (AWS) India and South Asia, revealed that banks are now open to using generative AI services.
According to him, AWS is helping BFSI companies integrate generative AI securely and efficiently. Many fintechs and FSI firms have already begun their generative AI journey using AWS with key adopters, including Dhan, HDFC Securities, Fibe, and Axis Bank.
He shared that for the stockbroking fintech startup Dhan, KYC timelines were long, and the company wanted to address this issue. The company used generative AI to shorten these timelines, automating 25% of the KYC process and reducing wait times by 50%. “They achieved this with a 30% reduction in operational costs,” Jagannath added.
The startup developed a chatbot solution based on LLM and retrieval-augmented generation (RAG) technology, utilising Amazon Lex, Amazon Bedrock knowledge base, and Amazon Bedrock agents. The GenAI chatbot integration automated KYC queries, with multilingual voice and text support, enabling 24/7 customer support with the flexibility to route conversations to live agents, accompanied by a summary of the chat history, based on the user’s preference.
Regarding another customer, Razorpay, Jagannath said the company used generative AI to reduce payment failures. “Payment failures are still quite common today, and they have a significant impact. Whether in e-commerce or other sectors, a failed payment means a potential loss of sales for the customer.”
The company recently launched Ray Concierge, an AI onboarding system that simplifies the often complex process of setting up payment gateways.
Moreover, he added that generative AI has several applications in the BFSI sector, including fraud detection, customer experience, document summarisation, and process automation. Jagannath further explained that the financial sector handles vast amounts of data and documentation, and AI helps speed up processes such as underwriting, insurance claims processing, and customer support.
How is AWS Making UPI Possible?
Jagannath said that many payment providers today operate on AWS, and even on the enterprise side, AWS collaborates with several customers. “Every UPI payment, whether it is ₹5 or ₹5,000, impacts core banking systems. These platforms were not originally designed to handle such high transaction volumes. So, we are working with these customers to improve resiliency.” He said, citing RBI data, that over 47% of the world’s real-time payments happen in India.
Speaking of resilience, he said that the AWS ensures resiliency and scalability through its availability zone (AZ) architecture. “Cloud computing provides automatic scaling, allowing AWS to handle failures seamlessly without customer intervention,” he said.
He revealed that each AWS region, such as Mumbai and Hyderabad, consists of multiple AZs. These AZs contain one or more physical data centres, which are isolated from each other by using different power grids, water sources, and other infrastructure. They are also interconnected with high-bandwidth, low-latency networks, ensuring minimal delay in communication.
The redundancy across AZs makes it extremely difficult for an entire AWS region to go offline unless a major disaster occurs. AWS automates failovers between AZs, meaning customers experience no visible downtime.
Moreover, he added that AWS is one of the most secure clouds and follows the security-by-design approach. “We have various concepts, like landing zone, where we help our customers, especially banks, develop these security guardrails and policies,” Jagannath said.
A landing zone is a pre-configured environment where security policies and guardrails are automatically applied. He explained that developers can write code within these security boundaries, ensuring compliance with policies from the start.
AWS Efforts to Bring AI to Everyone
Jagannath believes that more enterprises and customers will adopt generative AI services if they receive proper training. He said that AWS has trained about 5.9 million individuals in India.
“We do a lot of outreach to our developers across whether they’re working for large banks or working for large system integrators, it doesn’t matter for us, because they are the ones who are the pillars of foundations on how to adopt technology.”
Moreover, in 2025, AWS announced plans to invest $8.3 billion into cloud infrastructure in the AWS Asia-Pacific (Mumbai) Region in Maharashtra to further expand cloud computing capacity in India. This investment is estimated to contribute $15.3 billion to India’s gross domestic product (GDP) and support more than 81,300 full-time jobs annually in the local data centre supply chain by 2030.
“Our investments and operations in India are enabling customers of all segments to experiment and build technology applications and platforms, re-invent industries and their business models, and power their growth,” Jagannath concluded.
