Firm rejects Rs 390-cr crop insurance claims in 2 dists
An insurance company, ICICI Lombard, has rejected crop insurance claims of Rs 390 crore of Sirsa and Bhiwani districts for the 2017 kharif season, leading to unrest among farmers.
The Agriculture and Farmers’ Welfare Department had assessed the claims through crop-cutting experiments (CCEs) carried out in the fields have been “rejected” by the ICICI Lombard.
The insurance company is contesting the methodology in CCEs and has quoted satellite evidence to prove its point, while the department alleges the matter was never raised when it settled the claims in five other districts where the amount of losses was lower. But it is disputing claims in Sirsa and Bhiwani as the amount of losses is higher.
In Sirsa district, claims worth Rs 170 crore of cotton crop are pending and, in Bhiwani district, claims worth Rs 220 crore of bajra crop are pending.
“The company has already received premium for the rabi crop and it will move to some other district now as a company is assigned a cluster of districts only for two years. Initially, company officials continued buying time. First, they sought time till June 1, then till July 20 and then till August 2. Now, they have refused to settle the claims,” alleged Vikal Pachar, president, Akhil Bharatiya Swaminathan Aayog Sangharsh Samiti, Sirsa.
Dusmanta Kumar Bahera, Director of the department, said: “The insurance company has wrongly disputed the claims. The department has taken up the matter with the Technical Advisory Committee (TAC) of the Centre constituted under the Pradhan Mantri Fasal Bima Yojana (PMFBY).”
He said the meeting of the TAC was to be held in New Delhi on Monday, but it was put off due to some reason.
A spokesperson for ICICI Lombard, however, claimed that the CCE schedules were not shared with the company for co-observance and even where company’s officials were involved, data mismatch have been found.
“The company resorted to Remote Sensing Technology (RST) analysis using normalised difference vegetation index (NDVI). The results showed that our stand was correct. We have placed the evidence before the TAC, which is to take the final call,” the company said.
On why the matter of the CCEs was not raised in other districts, ICICI Lombard said the anomalies were mainly observed in multiple-harvesting crops such as cotton. Courtesy: www.tribuneindia.com
The use of technology in agriculture has become the norm of modern agriculture. It is the new way to improve production while at the same time reducing the cost involved. Normally, the use of the right technology in agriculture will guarantee the best results, but of course depending on a variety of factors. One of the challenges that many farmers have is the ability to determine the best inputs needed in a given area, as well as monitoring the growth of crops. Technology, through remote sensing abilities has made it crop health monitoring easy. This article provides an in-depth overview of how you can use technology to monitor the health of your crops.
Various remote sensing techniques are commonly used nowadays in providing information about land cover, as well as the condition of the land in terms of resources. Additionally, other remote sensing techniques such as satellite imageries play a significant role considering the rapid changes in landscape following the adoption of large scale development in agriculture. With the application of the appropriate remote sensing techniques, you are able to capture information on changes in the growth of plants be it structural or chlorophyll changes. As such, some of the approaches you can adopt in this case include the use of airborne and satellite images for the purpose of classifying crops, examining their viability and health, as well as monitoring the farming practices.
There are significant benefits associated with the identification and mapping of crops. Usually, the primary objective of such a farming practice is to ensure the preparation of an effective inventory of what is growing in a specific area, as well as the time it is growing. As such, the main activities revolve around the identification of the types of crops, and demarcating their coverage in terms of acres. Traditionally, farmers used methods such as ground surveying and census to obtain such information. Remote sensing can be used in the provision of strategies to collect common data and extract the relevant information on crop health.
The use of remote sensing techniques of crop monitoring can help in getting reliable information on the condition of the seedlings, and the trend and status of the crop growth. Additionally, such an approach is necessary in the acquisition of information on crop production. It is advisable to acquire crop growth conditions and status during the early stages of the growing season as opposed to getting the production information after you are harvested your crops. The reason for such early consideration is the fact that you get the chance to make the right policies and decisions about price, distribution and storage of your yield.
Use of NDVI and satellite maps in crop monitoring
There are different models that you can use to monitor the condition of your crops. For example, direct monitoring models are used to analyze the condition of the crops based on provided direct remote sensing indices such as Normalized Difference Vegetation Index (NDVI). Usually, such models are easy to adopt since they require less data.
NDVI maps are use in the collection of information on the variability of the health of crops; identification of the possible areas where the crops are poor; establish the development status of pants; detect problem areas for the purpose of timely decisions. Such maps are useful in that they clearly indicate the differences in the growth of vegetation in a given area. Usually, NDVI values have a strong correlation with respect to the stages of crop growth and hence, it is an ideal way of determining the health of crops within the growing period.
NDVI has a number of applications including crop monitoring, variable rate applications, yield estimation, and scouting. Often, scouting maps are used to guide farmers on the variations in the field for making the appropriate decision on what preventive and corrective measures to adopt. Crop monitoring, on the other hand, uses NDVI maps to monitor crops’ growth with the aim of detecting any anomalies within the crop season.
Methodology for crop health monitoring
The quantity of yield that you get from a given farm is depended on the amount as well as the timing of rainfall. Other important factors that influence the yield to expect in a given farming season include the quantity of fertilizers, sources of seeds, speed of wind, sunshine, and temperatures. The right satellite images can be useful in the assessment of the crop vigor especially during the growth period of crops. Normally, different crops tend to have different cycle of growth which implies variation in crop vigor. NDVI values are used in the examination of the growth of plant. Any changes in the NDVI values for a given crop raise concerns regarding certain areas of the farmland. Nevertheless, such data becomes highly useful when analyzed with respect to the GIS’ administrative boundaries and used in the assessment of real ground conditions that prevail in a given area.
Evidently, NDVI and satellite techniques and other remote sensing approaches are great in the monitoring of the growth of crops. They offer a great option to identifying areas that need attention concerning in terms of poor health of the crops. If used for scouting normalized difference vegetation index can offer insights into areas that require attention as such maps shows sections of the field where vegetation is growing well in comparison to the others. Such information is necessary in making appropriate decisions that are aimed at improving the health of crops, as well as the productivity of a given field. Therefore, it is advisable to employ the right techniques of identification, mapping and monitoring crops. Such a practice will help you prepare an effective inventory of what is growing in a specific area, as well as the time it is growing; and help you make the right decisions based on the health of your crops.
Over the past few months, farmer protests
have erupted across India. The common thread across the protests was the demand
for the revision of the minimum support price (MSP) and farm loan waivers.
However, the focus on MSP addresses just one aspect of the various risks that
farmers in India face.
Another risk mitigating measure that has
received relatively less focus has been crop insurance. It is pertinent to
understand the roles MSP and insurance play in addressing the various risks
farmers face in India.
The risks can be broadly classified into
yield risks (risks that arise due variability in crop yield)and price risk
(risks that arise due variability in crop price). MSP addresses the latter
while crop insurance addresses the former. Yield risks arise due to
uncontrolled inputs attributable to weather or pests and disease. Yield risks,
specifically weather-related risks, are critical and account for nearly 60% of
the variation in crop yield. This is primarily induced by weather fluctuations
Weather shocks can create health and
nutrition problems that undermine long-term earning capacity. Thus, formal risk
mitigation mechanisms, such as crop insurance play a critical role in this
Globally, crop insurance schemes have not
succeeded as they have failed to address moral hazard and adverse selection
risks. Currently in India, we have two main crop insurance schemes namely the
Pradhan Mantri Fasal Bhim Yojana (PMFBY) and the Revised Weather-Based
Insurance Coverage Scheme (RWBICS).
PMFBY is yield-based insurance that uses
crop-cutting experiments (CCEs) to determine the yield lost by farmers due to
natural catastrophes and adverse weather conditions. The yield obtained through
the CCE’s determine the payout made by the insurance firm to the farmer. The
new scheme looks to improve on the existing schemes by removing caps on the
premiums and making use of modern technology. However, there are several problems that exist with the PMFBY such as
the delay in crop cutting experiments and its associated high costs,
delayed/non-payment of insurance claims to farmers and lack of
transparency. As a result, farmers lose interest in the crop insurance schemes.
Another problem that faces crop insurance
schemes in India is coverage. The new scheme reveals that overall area insured has decreased over the last 2 years (from
53.7 million hectare in 2015-16 and 57.2 million hectare in 2016-17 to 47.5
million hectare in 2017-18). This is less than 24% of the gross cropped area
(against a target of 40%) as compared to 89% in the US and 69% in China.
A promising insurance product that
mitigates the risks associated with yield based crop insurance is
weather-indexed insurance. It is a financial instrument consisting of
contingent claims contracts held by farmers. The payouts are determined by a
combination of objective weather parameters (rainfall, temperature etc.) that
are highly correlated to crop yields and are automatically triggered once the
weather parameters reach a pre-specified level. This results in timely payouts
farmers and low administrative costs as there is no need for field-level damage
assessment. As the weather index is publicly available & transparent, it
allows the insurance companies to transfer a part of their risk to
However, for weather-indexed insurance to
be viable, it is necessary to mitigate basis risk. Basis risk is the
possibility that the insurance may not pay out even though the customer has
experienced a loss or the insurance pays out even though no loss occurs. In order
to address basis risk, it is pertinent to increase the density of automatic
weather stations (AWS) and rainfall data loggers in India. At present, there are only 706 AWS installed by the government across the country.
to a working paper by the Indian Council for Research on International
Economic Relations(ICRIER) , the entire country could be covered by installing
an additional 33,000 AWS and 170,000 rainfall data loggers. This would cost the
government anywhere between Rs 300 crore and Rs 1,400 crore. As weather indices
are lead indicators, the government can ensure timely payments by linking land
records of farmers with their Aadhaar numbers and bank accounts. Also, the unit
area covered under the insurance scheme should be the village for effective
targeting and minimisation of basis risk. At present, the only state government to have defined the village as the unit
area under insurance is Odisha.
In order to increase coverage, it is
necessary for the government to effectively communicate to the farmers the
value of insurance products.
Research has shown that a farmer’s
willingness to buy insurance may be greater when it is tied to credit and the
farmer’s knowledge of how index insurance works along with their initial levels
of wealth. At present, insurance products are viewed as an additional cost that
the farmer has to endure and the farmer sees no benefit in purchasing insurance
unless mandated as a part of the loan that is extended to the farmer by rural
This year’s Union budget increased the
allocations to PMFBY (Rs 13,000 crore, a 22% increase over its revised estimate
in 2017-18) but that alone does not guarantee increased coverage if the
above-mentioned measures are not undertaken.
At the end of the day, insurance is a
financial instrument that serves to transfer risk not necessarily reduce it.
With the effects of climate change becoming more pronounced, risk across the
board increases and it is very likely that insurance may no longer be
financially viable for the firm and the government which subsidies the
insurance scheme. In order to avoid this, it is incumbent upon the central and
state governments in creating the necessary infrastructure that allows farmers
to adapt effectively to the effects of climate change and thereby reduce the
impact of climate change on them.
At present, 52% of India’s total land under
agriculture is still unirrigated and rain-fed. The Economic Survey 2017-18
states that climate change could reduce annual agricultural incomes by between
15% and 18% on average, and between 20% and 25% particularly for unirrigated
areas. The measures that governments need to take up on war footing include
extending irrigation via efficient drip and sprinkler technologies and
replacing untargeted subsidies in power and fertiliser with direct transfers.
The Narendra Modi government has made a
serious attempt at addressing agrarian distress in India by announcing the
revised crop insurance scheme a couple of years ago.
But alas, both the PMFBY & WBICS have
neither received the push it ought to have nor have they been accompanied by
the financial literacy programmes required for their widespread success.