the Indian insurance industry as well. The scheme
has brought the farm sector into the financial mainstream and consciousness in a way that no other
scheme before has been able to do.
Weather & Crop Yield Outlook
For the first time in India, RMSI attempts to provide crop yield forecasts before the start of the season which are updated monthly through the season as actual weather becomes known. These estimates are available crop-wise, at various levels of granularity – district, cluster, state or All-India.
Portfolio Analysis
Our portfolio analysis model is a great tool for evaluating the risk to insured crop and planning reinsurance protection accordingly.
Our portfolio analysis model is a great tool for evaluating the risk to insured crop and planning reinsurance protection accordingly.
The model is based on historical weather, localized hazard events and crop yield and also takes into account impact of CAT events like flood, cyclone, and drought.
The model helps to
- Determine market participation strategy by analyzing multiple target portfolios
- Evaluate the reinsurance strategy by assessing multiple treaty plans
- Balance the portfolio risk
- Generate EP curves at Portfolio/Crop/Cluster/State level, and return period losses
For reinsurance planning, a Target Portfolio Analyzer helps insurance companies to create portfolio scenarios and get return period losses for each combination. The analyzer gives the option to evaluate multiple treaty plans to determine the best reinsurance strategy.
Premium Pricing
PInCER™ helps insurance companies prepare for bids by estimating the premium rate of all major crops notified under
the PMFBY scheme across all districts in India.
PInCER™ helps insurance companies prepare for bids by estimating the premium rate of all major crops notified under
the PMFBY scheme across all districts in India. PInCER™ implements two highly efficient premium estimation approaches:
a) Historical Yield Based – which follows the process based on yield variations, as stipulated in the PMFBY Operational Guidelines.
b) Nat Cat Modeling Based – This approach implements an actuarial process based on a probabilistic modeling approach for the estimation
of various covers specified in PMFBY. For these additional covers, the ‘loads of calculation’ are based on Nat Cat modeling techniques
that utilize the most comprehensive database of peril coverage and time series.
The model output includes threshold yield, base premium rate and the additional loads rates.
In-season Tracker
PInCER™ provides an yield tracker which is an efficient, technology-based solution combined with on-ground intelligence to provide real-time update of crop progress, at IU level, using large sample sizes.
PInCER™ provides an yield tracker which is an efficient, technology-based solution combined with on-ground intelligence to provide real-time
update of crop progress, at IU level, using large sample sizes. These forecasts are based on satellite images, weather forecast, agronomic
information, and pests & diseases infestation potential.
Pincer’s yield tracker is aimed at estimating per hectare yield at IU level as the season progresses. These reports are generated basis
satellite images and in-field surveys conducted by teams managed by RMSI Cropalytics. Our experts combine various analytics
(such as NDVI/leaf area index/ green index/plant density) along with other information to extrapolate yield and acreage estimates.
Policy Verification
PInCER™ has a module on policy verification that helps insurance companies to verify hundreds of thousands of crop insurance policies in a short time to control the moral hazard risk associated with the portfolio.
PInCER™ has a module on policy verification that helps insurance companies to verify hundreds of thousands of crop insurance policies
in a short time to control the moral hazard risk associated with the portfolio. Through effective use of technology, individual policies
can be scrutinized on a large scale. Individual applications with deviations in ownership or farm size can be identified and the probability
of “moral hazard” can be estimated. For verified applications, claim settlement would be faster. This would also help the insurance company
in building a reputation for rapid response to farm distress.