AI helps insurers cut onboarding costs, speed up claims processing: McKinsey
New Delhi, July 31
Artificial intelligence is helping insurance companies improve sales, reduce customer onboarding costs and process claims more accurately, according to a report by McKinsey.
The report said insurers adopting a domain-based AI strategy have recorded a 10-20 per cent improvement in new-agent success rates and sales conversion rates, along with a 10-15 per cent increase in premium growth. Customer onboarding costs have declined by 20-40 per cent, while claims processing accuracy has improved by 3-5 per cent.
McKinsey said insurers are focusing on applying AI across core business functions such as sales and distribution, underwriting, claims and policy servicing. Rather than deploying AI across the entire organisation at once, leading insurers are revamping specific business functions to generate measurable outcomes.
"Leading insurers don't see AI as just another efficiency tool--they recognize it as a fundamental driver of transformation and an opportunity to improve growth, relationships with customers, and productivity," the report said.
It added, "The transformation must be rooted in business value and the results have to be measurable."
According to the report, insurers need to prioritise a few high-impact business areas and link AI adoption to measurable operational improvements such as reducing customer churn.
McKinsey also said building in-house digital capabilities remains critical, with leading insurers aiming for 70-80 per cent of their digital talent to be employed internally while strengthening expertise to work alongside AI agents.
The report highlighted that strong data infrastructure and reusable AI systems are essential for scaling AI across insurance operations.
"Insurers excelling in AI rely on a flexible AI capabilities stack powered by reusable multiagent systems. The modern AI tech stack for an insurer is highly modular and flexible to cope with fast-changing technology," McKinsey said.
It further noted, "Reuse of underlying AI components and capabilities is critical, as is an agentic AI mesh architecture. This composable, distributed, and vendor-agnostic architectural paradigm enables multiple agents to reason, collaborate, and act autonomously across an array of systems, tools, and language models securely and at scale."
The report also stressed that successful AI adoption requires as much investment in organisational change as in technology.
"Adoption is just as important as development. As a rule, for every dollar spent on developing digital and AI solutions, plan to spend at least another dollar to ensure full user adoption and scaling across the enterprise. Change management is the key differentiator between AI sitting idle and AI transforming operations," McKinsey said.
— ANI
Reader Comments
The McKinsey report makes sense, but in India, the real challenge is data quality and infrastructure. Our insurance sector still deals with a lot of manual paperwork, especially in rural areas. AI is great, but we need to ensure it doesn't exclude people who aren't tech-savvy. Just saying! 🇮🇳
Interesting global trend, but the Indian insurance market has its own unique dynamics. The focus on agentic AI and multi-agent systems sounds futuristic, but I wonder how many Indian insurers are actually ready for this level of technological transformation. The 70-80% in-house digital talent target seems ambitious for our market.
My father works in an insurance company in Mumbai, and he says the onboarding process is still so tedious. If AI can genuinely speed up claims processing without compromising on fraud detection, that's a big win for customers like us. But change management is key - you can't just throw technology at people and expect them to adapt overnight.
The report highlights something crucial - the "adoption costs" being equal to development costs. Many companies underestimate this. In India, where the insurance penetration is still low, focusing on measurable outcomes and customer churn reduction makes perfect sense. More than AI, it's about intelligent implementation.
As a software engineer in Bangalore, I can see how AI is transforming every sector. But for insurance, the "agentic AI mesh architecture" mentioned in the report - while technically impressive - needs strong data privacy frameworks. In India, we have the DPDP Act now, so insurers must be careful about how they use customer data for AI models. Privacy first, profit later!
We welcome thoughtful discussions from our readers. Please keep comments respectful and on-topic.