For this, the Centre and the Insurance Regulatory and Development Authority of India (IRDAI) are in discussions to adopt artificial intelligence and big data to identify manipulation of processes, and reduce delays in settlement of claims.
Initially, technological upgradation will be voluntary, and this would soon be made mandatory for all insurers, creating a new benchmark, said an official.
The use of technology for claim assessment is being pushed to diagnose processes that are being manipulated, leading to fraudulent claims in agricultural as well as industrial insurance.
For agriculture insurance, where claims are dependent on crop and crop-cutting patterns, the plan is to initially make the use of satellite imagery and drones for detailed evaluation of crop produce on a voluntary basis.
This would be replicated for industrial insurance as well due to difficulty in identifying the cause of the problem, and subsequent delay in settlement of claims, the official said.
This leads to inordinate delays in settlement of claims, he added.
Insurance frauds are reportedly committed at the time of application or claim and cost Rs 45,000 crore per year to insurance companies.
The changes for insurance claims settlement will be introduced by IRDAI. The changes have been initiated by the government, after conducting pilot studies.
The Department of Agriculture, Cooperation and Farmers Welfare, in 2018, had carried out pilot studies for optimisation of crop-cutting experiments (CCEs) using remote sensing and satellite data during the Kharif and Rabi 2018-19 season under the Pradhan Mantri Fasal Bima Yojana (PMFBY).
Based on the results from use of technology, the government, in 2019, had rolled out a smart sampling technique using satellite data in 96 districts of 9 states, for rice crop during the Kharif season.
Pilot studies have been undertaken for estimation of yield at the gram panchayat level by using unmanned aerial vehicles (UAVs) or drones, artificial intelligence and machine learning, among others.
The government is yet to adopt any methodology for yield estimation, through technology.
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