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lighting or hidden damage. The entire process is automated, accurately captures their intent to purchase and identifies
completed in just 2-3 minutes and instant feedback gets their preferred communication channels, all through real-
delivered. This cuts down inspection time by over 70% and time conversations driven by generative AI.
improves customer satisfaction.
However, most InsurTechs deploy a human-in-the-loop ap-
Similarly, in health insurance, natural language processing proach, where AI is monitored by human advisors. This is
(NLP) engines can easily scan discharge summaries and hos- especially true for sensitive or high-stakes situations where
pital invoices, matching them with policy clauses to process AI reaches its edge. InsurTechs are now building sophisti-
claims faster and more accurately. Through computer vision- cated AI models that analyse speech-to-text transcripts from
driven algorithms, the processing of customer documents like customer calls, helping agents understand the context and
KYC forms, policy papers and bank statements has been intent behind interactions. This model ensures the customer
seamlessly automated. These AI models accurately extract gets the due support without feeling the heat of excessive
relevant data from each document, which cuts down manual automation.
effort and review time. This translates into a gain in produc-
tivity and a smoother, more efficient backend operation. Growing investment in AI enables cost-
efficiency
Generative AI at the frontline for better
What's also accelerating adoption is the growing cost-effi-
customer experience ciency of implementing AI. Cloud-native infrastructure,
Coming to another equally important piece of the puzzle, open-source large language models and the democratisation
which is customer experience, AI is making the entire ser- of AI tools have significantly lowered the barriers to entry.
vice journey faster and more efficient. AI-powered chatbots As AI's accessibility increases across the globe, it will become
and voicebots are now the first point of contact for many easier for InsurTechs to focus on the area with the highest
users. And they're getting better with every conversation. impact - claims. And the cost of servicing claims is drop-
They are capable of understanding multiple languages, even ping, allowing InsurTechs to reinvest in innovation. In fact,
the regional ones, and are also equipped to handle policy McKinsey estimates that AI can reduce insurance opera-
queries, claims initiation and grievance redressal with in- tional expenses by up to 40%, with claims processing time
creasing accuracy. In multilingual countries like India, this slashed by more than 60% in some cases.
makes claims handling far better.
According to industry estimates, investments in AI within
The rise of Generative AI and Large Language Models or InsurTech have grown nearly 40% year-on-year in the past.
LLMs has also made responding to complex policy queries The biggest advantage is that technology won't just optimise
and dealing with specific use cases much faster. What sets existing processes, it can open up newer avenues for the
these systems apart is their ability to customise advice in industry in terms of how insurance is designed, sold and
real time. AI systems can analyse user profiles, previous in- serviced.
teractions and browsing behaviour to offer recommenda-
tions and guidance. This allows even first-time users to ease At its best, insurance is a promise meant to cover life's most
into the conversation and make an informed decision after vulnerable moments, and the claim is called the moment of
they have verified all aspects of the policy. truth for this very reason. As digital adoption deepens and
customer expectations evolve, claims will remain the ulti-
Also, it significantly improves the fitment between a mate test of value for insurance. By using AI to transform
customer's needs and the product being offered. It also the claims experience, InsurTechs are strengthening that
enables a deeper understanding of customer sentiment, promise with intelligent systems.

Risk Culture

Risk Culture refers to the shared values, beliefs, knowledge, and attitudes within an organization that influence how
risks are understood, communicated, and managed. A strong risk culture promotes transparency, accountability, and
informed decision-making at all levels. It ensures that employees are aware of risks and take ownership in mitigating
them, rather than ignoring or concealing them. Leadership plays a critical role in setting the tone, reinforcing ethical
behavior, and aligning risk appetite with business objectives. Embedding risk culture into daily operations strengthens
resilience, supports long-term success, and reduces the likelihood of costly failures or regulatory breaches.

The Insurance Times May 2025 35