For decades, India’s vast rural heartland remained out of reach of formal insurance. Low awareness, high distribution costs, and complex processes alienated rural consumers. However, a new wave of AI-powered insurtech companies is now working to bridge that gap, transforming not just how insurance is bought and sold, but also who it reaches.
Debashish Banerjee, partner and insurance sector leader at Deloitte India, said the intent to address the rural and underinsured population is strong, but progress is mixed. “The intent is strong, and while foundational steps have been taken, there’s still ground to cover before we can call it a strong transformation,” he told AIM.
As Banerjee puts it, “The product has to be reasonably made for them.” For rural India, it means combining smart technology with simplified experiences, culturally aware communication, and accessible physical healthcare. AI is the enabler, but only if the surrounding ecosystem is designed to support it.
Banerjee believes that insurtech alone cannot drive the change. “The entire ecosystem has to be nudged together,” he said, noting that rural penetration has significantly improved in sectors like e-commerce.
Banerjee highlighted the potential for insurtech to leverage ecosystem partnerships, including postal departments, crop insurance programmes, state insurance schemes, and embedded offerings within rural-facing apps. However, for these models to scale, they must be underpinned by robust AI and data infrastructure.
How AI and Big Data are Driving Transformation
“AI and big data help…create better targeted insurance products for specific customer cohorts,” Nikhil Kurhe, co-founder & CEO of Finarkein Analytics, said in conversation with AIM.
Banerjee called AI “quintessential” to personalised insurance. “It’s absolutely going hand-in-hand. Most advancements today are increasingly built on a foundation of data and AI.” He cited examples where AI models suggest real-time insurance products based on contextual cues, like reminding a user about travel insurance before they board an international flight.
Building Models for Rural Needs
The challenge in rural India isn’t just delivery; it’s also relevance.
Rural customers require policies that are affordable, comprehensible, and tailored to their specific needs and lifestyles. AI plays a key role here. Platforms like Finarkein are utilising Account Aggregator frameworks and Health Claims Exchanges to enable insurers to conduct more precise need-gap analysis and prevent misselling. “The insurance advisors are now able to touch base with customers more frequently with contextual and personalised insights,” Kurhe added.
One major public initiative transforming rural health insurance is the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), a publicly funded health insurance scheme. It provides ₹5 lakh per family per year for secondary and tertiary care hospitalisation, covering over 500 million Indians—a large portion of them from rural and low-income households.
AI and data analytics are used to automate claims adjudication, detect fraud patterns such as inflated billing, and support geospatial analysis for infrastructure planning. As a result, claims processing becomes faster, human error is reduced, and the National Health Authority can effectively monitor service quality across numerous hospitals.
The implementation of AI in rural healthcare faces several challenges. Outdated Socio-Economic and Caste Census (SECC) 2011 data leads to misclassification, causing many rural families to be overlooked. Moreover, limited internet access and low digital literacy hinder the effectiveness of AI tools in remote areas. Privacy concerns also arise, as beneficiaries are often unaware of how their data is used. While AI can accelerate approvals, the shortage of hospitals and doctors results in delays in care.
Furthermore, the focus on treatment rather than prevention within programs like PM-JAY prevents the effective use of AI for preventive care, which is vital for improving rural health outcomes.
Despite these challenges, PM-JAY’s use of AI and digital tools has created a blueprint for large-scale, tech-enabled health insurance that private insurtech players can adapt and build upon.
Banerjee highlighted another frontier: lifestyle-based analytics. “We’re seeing a shift from relying only on medical tests to using lifestyle data, what you eat, how you travel, even what you read, as predictors for long-term health. AI helps insurers track thousands of such parameters and segment customers with greater precision,” he explained.
Agentic AI: The Next Leap
One of the most exciting innovations Deloitte is championing is Agentic AI, a new paradigm in which AI agents not only process information but also take action in workflows such as underwriting and claims.
“We’re working closely with insurance CTOs to embed agentic AI in underwriting and claims. For instance, AI can now approve motor claims just by analysing photos, removing the need for surveyors in minor cases,” Banerjee said.
This reduces turnaround time, cuts costs, and offers instant claims approval, which could be a game-changer for rural areas where physical surveys are impractical.
However, cutting-edge AI is only valid if people use it. Many rural consumers remain unfamiliar and uncomfortable with digital tools.
Acknowledging this gap, Banerjee said, “Insurance customers in India are gradually adapting to digital platforms.”
Kurhe pointed out another key factor: trust. AI can help reduce fraud and create transparency, which builds credibility in underserved markets.
Embedded Insurance and Micro Products
A practical way to reach rural customers is by integrating insurance into everyday transactions, such as mobile recharges, agri-input purchases, ride-hailing apps, and more.
While this model is still maturing, Kurhe revealed early signs of adoption. “Large platforms like Swiggy and Zomato have tied up with insurers to offer insurance to delivery teams. Similar models can evolve for farmers and gig workers.” As these digital footprints grow, AI models can begin tailoring micro-insurance to the nuances of rural life.
Deloitte, which collaborates with both large insurers and startups, is helping build AI-first, future-ready operations. “We are working closely with insurers to rethink everything—from how their core systems operate to how products are sold digitally,” Banerjee said.
Over the next three to five years, he anticipates three key themes: leveraging agentic AI for intelligent automation, transforming insurance distribution through platformisation and creating hyper-personalised go-to-market strategies for specific segments, such as rural populations, youth, and affluent buyers.
Moreover, the buy-vs-build debate is alive. “Some insurers want to build their tech, and even sell it. Others partner with startups. Deloitte supports both, we evaluate, advise, and co-build as needed,” he concluded.
Insurtech’s success in India will ultimately hinge on how well AI can be applied at the edges, where insurance is still a foreign concept, and technology is often absent.
By combining agentic workflows, personalised AI models, and ecosystem partnerships, the industry has a real chance to democratise access and rewrite India’s insurance story from its smallest villages to its fastest-growing towns.
[Update: The articled has been edited for clarity.]
