Another insights piece to fit our January theme, Stormy Weather & How to Handle Claims Spikes. This time US company Neutrinos offers some thoughts on coping and triage;
It’s authored by Dr. Hari Prasad of Neutrinos
Every December claims teams brace for another surge, and every January, they’re overwhelmed again.
In late November 2025, Tropical Cyclone Senyar struck Sumatra, triggering flash floods and landslides that killed over 600 people, displaced more than 570,000 residents, and generated thousands of simultaneous property and motor claims across Indonesian insurers. In the Philippines, Super Typhoon Fung-Wong displaced 1.4 million people and triggered waves of claims across every insurer within days.
The same pattern plays out every year in the United States, just without the typhoon headlines. In Florida, hurricane season drives sharp, short-duration claim spikes that can multiply daily volumes by orders of magnitude, particularly for property and auto. In California, wildfire season creates compressed surges of homeowners, renters, and commercial property claims that arrive faster than adjuster capacity can scale. Even outside catastrophe events, winter storms across the Midwest and Northeast reliably flood carriers with auto collision, property damage, and liability claims within days of the first major freeze.
And it’s not just extreme weather. The holiday season in the U.S. sends 110 million Americans onto the roads, while home insurers face their busiest claim period of the year. More cooking fires occur on Thanksgiving Day than any other day, according to the National Fire Protection Association, and one-third of annual fire deaths happen in winter. Retail workers’ comp claims spike 25% in January as seasonal workers handle post-holiday cleanup and navigate icy conditions.
These aren’t surprises. They’re calendar events.Yet traditional claims operations, built for steady volumes, collapse when claims surge 50x overnight.
For policyholders, this breakdown is not abstract. It means uploading the same documents multiple times. It means calling a contact center that has no new information because the claim has not yet been touched. It means waiting days for resolution while paying out-of-pocket expenses or taking on short-term debt to cover repairs, temporary housing, or medical costs as they wait in claims limbo. In these scenarios, delays compound stress at the exact moment insurers are meant to deliver certainty.
For insurers, these delays carry consequences beyond customer dissatisfaction. Extended cycle times drive higher loss adjustment expenses, increase inbound call volume, and elevate complaint risk following catastrophe events. In property and auto lines especially, slow claims resolution can escalate into litigation exposure, public adjuster involvement, and reputational damage that persists long after the event itself.
The reason these spikes remain so disruptive is not a lack of planning or experience. It is that most claims organizations are still designed around static capacity and sequential workflows. Staffing models assume predictable inflow. Systems assume claims arrive one at a time, move step by step, and require human intervention at every gate. Governance models assume decisions are reviewed after the fact, not in real time.
That model works on an average Tuesday. It breaks the moment volume compresses into hours instead of weeks. Digital channels have collapsed submission timelines from days to hours. Photos, videos, and documents arrive instantly and in parallel. Claims that once trickled in now arrive all at once, overwhelming intake, triage, and decision layers simultaneously.
Many insurers have already experimented with AI in claims. Document automation, basic triage models, and chat-based intake are no longer novel. But most of these efforts are layered onto workflows that were never designed for autonomy or scale.
Optical character recognition may extract data, but claims still queue for manual review. Triage models may score severity, but decisions still wait for handoffs. Automation exists, but execution remains sequential. During surge events, these systems improve efficiency at the margins while the underlying bottleneck remains unchanged. The difference is not whether AI is present, but whether it is embedded into how decisions are made and executed in real time.
AI-powered systems solve this through elastic capacity. Intelligent Document Processing (IDP) ingests thousands of first notices of loss via mobile upload, eliminating weeks of postal delays. Natural Language Processing (NLP) extracts and interprets policy and medical data instantly, while computer vision auto-triages damage from photos and flags total losses before adjusters deploy. Modern composable AI platforms automate adjudication rules with high-confidence and surface only truly complex cases for human review.
This can result in as high as 80% of routine claims cleared straight-through in under 24 hours, freeing adjusters for the 20% that require judgment.
The spikes are predictable. The technology exists. The question is whether we will deploy AI infrastructure now or keep explaining to policyholders why they must wait weeks or months after the next predictable surge.
About the Author: Dr Hari Prasad, Head, Insurance Propositions at Neutrinos, is a distinguished leader with over 20 years of expertise in healthcare, insurance and technology transformation. Known for driving innovation in global markets, he has led impactful projects in automation, underwriting, and claims processing. From spearheading AI-driven solutions at Neutrinos to founding successful ventures, his leadership has enhanced business efficiency and customer outcomes across Asia, Africa and the USA. Dr. Hariprasad’s unique blend of medical and technological expertise positions him as a thought leader in the insurance transformation space.
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