Visiting a bank, insurance office, or any financial institution can feel overwhelming due to long queues, tedious paperwork, and repetitive procedures. And, as it does for most problems in life today, AI is poised to play the saviour in India’s banking, financial services, and insurance (BFSI) industry, given its capabilities.
At Microsoft’s AI Boardroom event, Nitin Chugh, head of digital banking and transformation at the State Bank of India, highlighted how the firm is leveraging AI for various operations. He revealed that SBI utilises more than 150 AI models across multiple sectors, including business, fraud, risk management, customer service, employee productivity, and others.
The Big Banks of India Have Embraced AI
The banking firm utilises several conversational agents for operational efficiency. For instance, the ‘Deceased Account Settlement Queries Chatbot’ handles customer queries related to deceased account settlement cases.
Another chatbot called askSBI provides solutions for ‘complex business scenarios’ experienced by the banking staff, which in turn leads to improved service quality. Additionally, Chugh revealed that SBI is also exploring agentic AI workflows for operations.
“All of us are looking at agentic workflows very seriously—from front to back, and vice versa,” said Chugh.
“At some point, we’d like to give an agent to each of our customers, which would be intelligent enough to connect to a workflow agent in the bank,” he added. Chugh also clarified that this will enable humans to perform more valuable tasks.
Additionally, just as the API or microservices layer, Chugh said he expects an agent orchestrator layer to support multi-agent workflows. This will indeed prove pivotal for customer experience.
Besides SBI, multiple other banks, such as ICICI Bank, HDFC Bank, Federal Bank, Axis Bank, and more, have implemented conversational AI solutions.
More importantly, the Reserve Bank of India, the country’s central bank, is also betting big on the technology. The RBI has developed a solution based on AI and machine learning frameworks to identify suspected mule accounts. These technologies can analyse transactions and the necessary data sets to predict mule accounts with higher accuracy.
Sanjay Malhotra, the governor of the RBI, in a speech at the Annual Conference of the RBI Ombudsmen last month, was quite vocal about the potential of AI in grievance resolution in the banking sector.
“Leveraging data analytics, sentiment analysis, and predictive models, AI can be used to analyse large volumes of data to detect spikes in issues, such as ATM failures or erroneous charges, and alert REs [regulated entities] pre-emptively,” he said.
Last December, the bank also launched a committee to establish a Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREE-AI) in the financial sector. The initiative aims to propose guidelines for the responsible integration of AI models in India’s financial infrastructure, particularly catering to the growing fintech ecosystem.
AI in Insurance, Trading, and Tax
In the broader context of the BFSI sector, AI is playing a crucial role in accelerating business outcomes. Microsoft also commissioned a study along with IDC, which revealed that this sector “enjoys the highest return on investment” with generative AI solutions, where companies earn $5 for every $1 invested.
Devang Mody, CEO of Bajaj Finserv Health, was also present at the Microsoft BFSI Boardroom event and shared insights on how the company uses AI. The company has developed an AI-enabled platform called Enigma, which helps minimise fraud, optimise resource utilisation, and streamline the insurance management process.
The platform was built to handle outpatient doctor visit claims, which are often small, typically INR 500–700.
“We were thinking hard about how to solve this [adjudicating claims] problem for a ₹500 claim. I don’t want to spend ₹1000 adjudicating it. So, in a way, necessity was the mother of all invention,” said Mody, indicating that an automated solution had to be built, as it was deemed expensive to adjudicate these claims manually.
Enigma is built on top of Microsoft Azure’s AI solutions. It was reported that Enigma reduced average claim handling time by 40%, and identified 5x more fraudulent claims in comparison to conventional methods. Mody also revealed that Engima was able to adjudicate 90% of OPD claims without any manual intervention.
He illustrated the technology’s capability with a simple example. He explained that the company handles around 10 million health transactions annually, each ranging from 3 to 140 pages.
To improve processing efficiency, the company uses AI to automatically analyse unstructured documents, such as detecting missing KYC documents in large PDF claims without requiring human intervention.
In another instance, ICICI Lombard is said to have used Microsoft Azure and OpenAI’s tools to improve claims adjudicator productivity.
A tool was built to generate a summary of health claims from documents and consolidate information related to diagnosis and treatment, comparing it to NHA (National Health Authority) guidelines. This solution reportedly reduced the time to process a single health claim by over 50%.
Besides the big names in the country, several startups have emerged in the fintech sector that leverage AI for financial operations.
For instance, MyFi is a startup that uses AI to democratise financial planning. Registered with SEBI and integrated with the RBI-approved Account Aggregator framework, it helps users access all their financial accounts securely and delivers personalised investment recommendations using real-time market insights.
Another startup called uTrade Solutions, based in Noida, offers a no-code algorithmic trading platform that enables users to automate trades using AI-powered strategy templates and dashboards. Its marketplace, uTrade Originals, also provides one-click access to expert-built trading algorithms.
Chennai-based Fhero Accounting Solutions provides an AI-enabled solution for tax and accounting. The platform automates data entry, categorises financial transactions, and offers analytics-driven insights, helping businesses reduce errors and make proactive decisions.
Having said that, we’re far from a world where AI is perfect. While being optimistic about AI, the RBI governor mentioned that institutions need to remain cognizant of the risks associated with AI.
“Every transaction represents not just a number in a ledger, but the hard-earned savings of a family, the dreams of a small entrepreneur, or the lifelong savings of a senior citizen,” said Malhotra, indicating that it is crucial not to lose sight of the human element, and regulated entities must continue to invest in human resources for grievance resolution.
“While technology in all its forms is a powerful enabler, I would like to emphasise that it is no substitute for integrity, empathy, and human judgment,” said Malhotra.
The post Smart Money: How AI is Disrupting India’s BFSI Game appeared first on Analytics India Magazine.
