Nagaland has become the first state in India to insure its entire geography against heavy rainfall through a pioneering parametric insurance scheme, signalling a new approach to climate resilience and disaster finance, reported Mongabay India.
The scheme, known as the Disaster Risk Transfer Parametric Insurance Solution (DRTPS), was revised and relaunched in 2024 to address previous design failures. So far, the scheme has triggered payouts worth Rs 1.06 crore to residents affected by extreme weather.
In August 2024, when intense rainfall lashed Kohima, 70-year-old Vejopra Dozo’s house was damaged by a landslide. “It was an especially bad bout of rain, and we even lost 40 to 50 bags of rice worth Rs 60,000, which were all washed away,” Dozo told Mongabay India. In May 2025, he received Rs 25,000 in compensation — not from traditional government funds but through the new insurance mechanism.
The scheme, developed by the Nagaland State Disaster Management Authority (NSDMA) in collaboration with SBI General Insurance and reinsurer Munich Re, uses gridded rainfall data from the India Meteorological Department and 34 all-weather stations across the state. Insurance payouts are automatically triggered when monsoon rainfall crosses pre-set thresholds.
“Although the eastern districts were hit hardest by rainfall-induced risks, other regions including Mokokchung, Dimapur, Phek, Kohima, and Wokha also experienced the effects of heavy rainfall, in addition to facing other concurrent challenges such as fires, pest outbreaks, drought, and human-wildlife conflicts,” said Noyingbeni Kikon, Project Coordinator at NSDMA, in an email to Mongabay.
Under the revised scheme:
· Rainfall above 1,500 mm triggers a payout of 10% of the sum insured for that tehsil.
· Every additional 80 mm of rainfall increases the payout by another 10%.
· A 100% payout is triggered if rainfall crosses 2,200 mm.
“All Tehsils covered under the scheme have been classified into high, medium, or low flood risk zones, with each zone assigned a pre-defined sum insured,” said Priya Sampath Kumar, Business Head – Emerging Business Lines, SBI General Insurance.
The state is reportedly paying an annual premium of Rs 4.5 crore for a coverage of Rs 50 crore, and Rs 150 crore over a three-year period. While expensive premiums and the risk of no payout make states hesitant to adopt similar schemes, Nagaland’s model includes a refund clause if no claim is made, and provisions for unseasonal rainfall, said Johnny Reungmei, Joint CEO of NSDMA.
Experts caution that the viability of such schemes depends on how frequently weather thresholds are breached. “When the frequency of extreme weather events goes up, insurance coverage may cause premiums to go up,” said Neha Khanna, Associate Director at the Climate Policy Initiative.
“The model can certainly be replicated, and it’ll be interesting to see how it pans out over the long-term in Nagaland.”
To ensure transparency and timely disbursal, NSDMA has set up a decentralized payments system with digital verification. “After an applicant is verified and approved, the system integrates their verified bank details after which the sanctioned insurance or relief amount is automatically disbursed into the beneficiary’s account,” said Kikon. A locker facility for cash payments is also available for beneficiaries without bank accounts.
Though the Rs 25,000 Dozo received helped build a makeshift structure with tarpaulin, he told Mongabay, “rebuilding the wall will be more expensive.”
At the national level, the Ministry of Home Affairs informed the Rajya Sabha in March that it is studying ways to extend parametric insurance cover to all citizens. Meanwhile, several northeastern and coastal states have reportedly shown interest in Nagaland’s model.
“By including high-frequency, low-severity risks in their portfolio, insurers can better manage risk, leading to more stable profitability,” noted Kumar of SBI. “However, it takes time to structure the contours. Various parameters along with data need to be evaluated before proposing a suitable product.”
(With inputs from Mongabay India)
