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Enhancing
technology use
in agriculture
insurance
REPORT OF THE TASK FORCE ON
National Institute for Transforming India (Niti) Aayog
Government of India
December, 2016 02Enhancing technology use in agriculture insurance
Citation:
Aggarwal, P.K., Chand, R., Bhutani, A., Kumar, Vijay, Goel, S.K., Rao, K.N., Poddar, M.K., Sud, U.C., Krishna
Murthy, Y.V.N., Ray, S.S., Murthy, C.S., Sikka, A., Shirsath, P.B., Mishra, J.P., Choudhury, M., Chaudhury, O.P.,
Joshi, A.K., Sen, G., Tarpara, C.N., Kumar, D., Sahoo, R.N., Kumar, N.S., Yadav, A.K., Singh, T.P., Kannan, H.,
Satish Raju, G., Sudhakar, M., Singh, K.K., Agarwal, N., Reddy, P.K., Shukla, A., Shanbaug, A., Srivastava,
A.K., Mehta, S., Gupta, P.K., Gopalakrishnan, A., Chandel, B.S., Duggal, R.K., Deshmukh, V., Kotwaliwale,
N., Vora, P., Kumar, S. and Lochan, R. 2016. Report of the Task Force on ‘Enhancing Technology Use in
Agriculture Insurance’. NITI (National Institute for Transforming India) Aayog, Government of India. i
List of Abbreviationsiii
Prefacev
Executive Summaryvii
1. Introduction1
2. Enrolment in Crop Insurance4
2.1. Key challenges4
2.2. Technology solutions4
2.3. Recommendations6
3. Crop Loss Assessment7
3.1. Key challenges7
3.2. Technology solutions8
3.3. Recommendations9
4. Claim Settlement11
4.1. Key challenges11
4.2. Technology solutions11
4.3. Recommendations12
5. Product Design and Development13
5.1. Key challenges13
5.2. Technology solutions14
5.3. Recommendations14
6. In-season Crop Yield Loss Assessment (on Account Payment)16
6.1. Key challenges16
6.2. Technology solutions16
6.3. Recommendations17
7. Livestock and Aquaculture Insurance18
7.1. Key challenges18
7.2. Technology solutions18
7.3. Recommendations19
8. Institutional Mechanisms for Technology Use in Crop Insurance20
8.1. Key challenges20
8.2. Recommendations21
Constitution of the Task Force22
Sub Groups23
Contents iiEnhancing technology use in agriculture insurance iii
List of
Abbreviations
AFMU Agriculture Field Monitoring Units
AIC/ AICI Agriculture Insurance Company of India Limited
AMIS Alliance Marketing and Insurance Services
App Mobile-Based Application
CBS Core Banking Solution
CCE Crop Cutting Experiments
CCIS Comprehensive Crop Insurance Scheme
CCAFS CGIAR Research Program on Climate Change, Agriculture and Food Security
CIMMYT International Maize and Wheat Improvement Center
DAC&FW Department of Agriculture, Cooperation and Farmers Welfare
DAH,D&F Department of Animal Husbandry, Dairying & Fisheries
DCCB District Central Cooperative Bank
EEZ Exclusive Economic Zone
FASAL Forecasting Agricultural output using Space, Agro meteorology and Land based
observations
FEWS NET Famine Early Warning Systems Network
GEOGLAM Group on Earth Observations Global Agricultural Monitoring Initiative
GIC General Insurance Corporation of India
GIS Geographic Information Systems
GPS Global Positioning System
IARI Indian Agricultural Research Institute
ICAR Indian Council of Agricultural Research ivEnhancing technology use in agriculture insurance
ICAR-CIFE ICAR-Central Institute of Fisheries Education
ICAR-IASRI ICAR-Indian Agricultural Statistics Research Institute
IMD India Meteorological Department
IRCTC Indian Railway Catering & Tourism Corporation Ltd
ISRO Indian Space Research Organisation
IT/ICT Information Technology and Information and Communications Technology
IVRS Interactive Voice Response System
KISAN Crop Insurance using Space Technology and Geo informatics
KVK Krishi Vigyan Kendra
MARS Monitoring Agricultural Resources
MNAIS Modified NAIS
MNCFC Mahalanobis National Crop Forecast Centre
NABARD National Bank for Agriculture and Rural Development
NAIS National Agricultural Insurance Scheme
NCAER National Council of Applied Economic Research
NCIP National Crop Insurance Programme
NDDB National Dairy Development Board
NDVI Normalized Difference Vegetation Index
NRSC National Remote Sensing Centre
PMFBY Pradhan Mantri Fasal Bima Yojana
RFID Radio-Frequency Identification
RS Remote Sensing
SAC Space Applications Centre
SAU State Agricultural University
SMS Short Message Service
UAV Unmanned Aerial Vehicles
VMS Vessel Monitoring Systems
WBCIS Weather Based Crop Insurance Scheme v
Preface
Pradhan Mantri Fasal Bima Yojana (PMFBY) is a flagship scheme of the Government of India to
provide insurance coverage and financial support to farmers in the event of failure of any of the
notified crops, unsown area and damage to harvest produce as a result of natural calamities, pests
and diseases to stabilise the income of farmers, and to encourage them to adopt modern agricultural
practices. The scheme is a considerable improvement over all previous insurance schemes in India
and is heavily subsidised by the state and central governments. The scheme aims to cover 50 percent
of the farming households within next 3 years.
During its implementation in the last one season, several challenges relating to enrolment, yield
estimation, loss assessment, and claim settlement were reported by farmers, insurance companies
as well as the state governments. It was also noted that several technological opportunities existed
for possibly leveraging support to the Indian crop insurance program for enhanced efficiency and
effectiveness. NITI Aayog of the Government of India, therefore, constituted a Task Force to deliberate
on this subject and identify such potential opportunities. This report summarises the recommendations
of the Task Force.
The Task Force constituted to address the issue of technology support to crop insurance comprised
the following 5 sub-groups: (1) Remote Sensing & Drones; (2) Decision Support Systems, Crop
Modelling & Integrated Approaches; (3) IT/ICT in Insurance; (4) Crop Cutting Experiments (CCEs); and
(5) Technologies for Livestock and Aquaculture Insurance. Each sub-group had several discussions
with experts in the respective areas, and submitted draft reports. More than 100 experts related to
professional research agencies, insurance industry, banks, and the government contributed to these
discussions. Technological options available in the country and abroad were considered by all groups.
The Task Force together with the sub-groups then deliberated on key issues and formulated its
recommendations as presented in this report. During the discussions it was realised that there were
many administrative and institutional issues that needed to be addressed in PMFBY. However, the
focus of the Task Force was on its main mandate, technology use in crop insurance. We hope these
recommendations would help the Indian crop insurance sector take full advantage of the technological
options suggested so as to increase its efficacy and effectiveness leading to reduced agrarian distress
in the country. viEnhancing technology use in agriculture insurance
The Task Force is grateful to Dr. Arvind Panagariya, Vice Chairman, Dr. Ramesh Chand, Member and
Shri Amitabh Kant, CEO of NITI Aayog for constituting this Task Force, and to Dr. Ashish Bhutani of the
Ministry of Agriculture & Farmers’ Welfare for providing the government’s point of view. The Task Force
is also grateful to Dr. Sudhir Goel, former Additional Chief Secretary, Government of Maharashtra, Mr.
Vijay Kumar, former Additional Chief Secretary, Government of Andhra Pradesh, Dr. Alok Sikka, South
Asia Director of the International Water Management Institute, Dr. YVN Krishna Murthy, Director of the
National Remote Sensing Centre, and Dr. Dilip Kumar, former Director/Vice Chancellor of ICAR-CIFE
for chairing the sub-groups and advising the Task Force. vii
Executive
Summary
The Pradhan Mantri Fasal Bima Yojana (PMFBY) is a transformative scheme of the Government of
India to provide insurance coverage and financial support to farmers in the event of failure of any of
the notified crops, unsown area and loss of harvested produce as a result of natural calamities, pests
and diseases to stabilise the income of farmers, and to encourage them to adopt modern agricultural
practices. The scheme recognises the need for technological interventions in crop insurance to
make the insurance mechanism more efficient, transparent and farmer-friendly. Considering the
complexities associated with Indian agriculture such as small and scattered land holdings, very high
eco-geographical variability, yield variability and weather aberrations, it is imperative that technologies
are effectively used to increase the efficacy and effectiveness of the insurance sector.
For effective implementation of the PMFBY several technological options have been proposed such as
remote sensing technologies (satellite and Unmanned Aerial Vehicles − UAVs), smart-phones, digital
photography, new statistical techniques and modelling approaches, and IT/ICTs. Currently, there is a
modest use of IT/ICT in the insurance sector for enrolment and other operational issues. There have
been only some piecemeal studies on the use of technologies in other arenas like yield estimation, loss
assessment and product design despite the country having a large agriculture and space research
program, which has many potential technologies suitable for the insurance sector. However, the
evidence base of these technologies, under diverse agro-ecological regions of the country, is limited
to support their nationwide implementation in crop insurance program. A
comparative evaluation of different technologies has not been done so far
and often the states, researchers and insurance players have diverse views
on their use. The key technology providers for remote sensing are research
and academic organisations and private companies whereas IT/ICT and UAV
technology suppliers are largely private players. Other technologies such
as integrated assessment modelling, and statistics are still in the domain of
national and international research institutes.
The Task Force on “Use of Technology for Agriculture Insurance” constituted
by the NITI Aayog deliberated on this subject with almost 100 leading experts viiiEnhancing technology use in agriculture insurance
from research organisations, universities, insurance industry, the government, banks and other
stakeholders to recommend the key technologies for effective implementation of the PMFBY. The Task
Force noted several administrative and institutional challenges beyond its mandate that needed to
be addressed for effective implementation of the PMFBY apart from the use of technology. The Task
Force constituted five sub-groups to do a detailed assessment of technological options and to obtain
stakeholders’ feedback on various issues. The sub-groups were on: (1) Remote Sensing & Drones;
(2) Decision Support Systems, Crop Modelling & Integrated Approaches; (3) IT/ICT in Insurance;
(4) Crop Cutting Experiments (CCEs); and (5) Technologies for Livestock & Aquaculture Insurance.
After deliberating the reports from the five thematic sub-groups, the following recommendations on
enhancing technology use in agricultural insurance were made by the Task Force largely targeted
to the concerned ministries of state and central governments for action besides the crop insurance
industry, which needs to act on some of the recommendations and share the costs of implementation:
1. To increase insurance literacy, the state governments should urgently commission the
development of a comprehensive mobile-based application (App) that has 24x7 links with the
payment gateways/e-wallets to facilitate ease of registration, online payment of premium and
issue of instant e-receipts. This should have links with the National Crop Insurance Portal available
at www.agri-insurance.gov.in. This data should be simultaneously accessible to insurance
companies, bankers and the state government departments.
2. The states should commission major campaigns during the enrolment period in every crop
season using participatory videos, and other ICT tools such as voice blasts, IVRS and SMS, to
increase awareness and insurance literacy. Together with related banks and insurance industry
they should simultaneously arrange for on-the-spot enrolment in crop insurance using the
customised mobile App.
3. To reduce farmers’ discomfort with the enrolment process, PMFBY guidelines should be relaxed
to accept geo-tagged and time-stamped digital photographs of land to establish the insurable
interest instead of manual certificates. Such photographs submitted by the farmers should be
accepted as sowing certificates if the declared crop is changed after the payment of premium.
4. Digitising geo-referenced records of land holding is critical for reducing moral hazards in crop
insurance. This work is currently being done in the states at a varied pace. Development of a
strong geo-referenced and regularly updated cadastral map base and its linkage with different
land records should be accelerated and completed in a time-bound manner. Bhumi project
of Karnataka government has shown considerable progress in this aspect and could provide
lessons for other states.
5. The Task Force is of the view that although CCEs are central to the insurance scheme, they are
not serving much purpose in their present form because of the financial, scientific, institutional
and operational challenges associated with them. Moreover, they do not necessarily provide good ix
estimates of yield loss over insurance units in a timely manner. It was noted that a combination
of these options - remote sensing, digital photography, statistical methods, and integrated crop
modelling- can provide an objective and unbiased assessment of crop yield losses well in-time
at a fraction of the current CCE costs. There is an urgent need to identify the most suitable
technology option and associated operational guidelines for every state. Capacity to undertake
such work in India is available with institutes/centres of ISRO, ICAR, and IMD, MNCFC, IT/ICT
agencies, state agricultural universities, state remote sensing centres, CGIAR research centres,
and private companies.
The Task Force, therefore, recommends that CCEs in their present form
must be replaced in a phased manner with technological solutions for crop loss assessment. The
following approach is proposed for developing protocols for loss assessment:
a. All state governments with a large stake in crop insurance should immediately commission
a 12-month project for a comparative evaluation and deciding on the suitability of
technological options for agro-ecological diversity in the state. The project should propose
the most suitable approach to provide robust estimates of crop yields at individual village/
village panchayat level along with cost-benefit analysis of the operations, and assessment
of technical capacity to implement this in an operational manner. For this work, the state
governments and insurance industry should allocate 0.20 percent premium.
b. The project should also propose a scientifically designed sampling strategy for a few very
high quality CCEs at block/tehsil/district/agro-ecological zones level in the state which can be
independently used to supplement/calibrate/validate/verify the technology proposed for loss
assessment.
c. Conducting these few and high quality CCEs should be the responsibility of the state
government and should be guided and monitored by independent experts from state
agricultural universities (SAUs) and their associated Krishi Vigyan Kendras (KVKs)/reputed
agricultural NGOs. The entire CCE must be digitally recorded so that it can be witnessed by
anyone, and be publicly available.
d. The above approach should be tested in at least 10 percent districts in Rabi 2017-18 and
Kharif 2018. Subsequently, the whole experience should be reviewed, calibrated, and applied
in the entire state from Rabi 2018-19.
e. For the time being, all CCEs should be witnessed, monitored and reported using mobile
Apps involving the staff of SAUs/KVKs, farmers, agriculture departments and insurance
companies.
6. Although there are several satellites today that can support crop insurance sector, it is
recommended that a dedicated constellation of 3-4 satellites of high to moderate resolution
(10-30 m) with 10-days frequency and with multispectral optical sensors, two microwave
satellites, and one hyper-spectral satellite may be deployed to increase the precision of crop yield
estimates/loss assessment at the village scale. xEnhancing technology use in agriculture insurance
7. Crop losses due to localised climatic events such as hailstorms, landslides, small floods and
post-harvest losses, where CCE data do not play a role, need to be supported by a mobile based
App. A separate mechanism for such data collection, visualisation and customisation needs to
be developed. The experience of the Karnataka Government for mango and grape could provide
lessons for such an App.
8. The Ministry of Agriculture and Farmers’ Welfare should expand their mobile App - CCE Agri - to
process CCEs’ data and weather data to calculate the loss and claim estimation in real-time. On
completion of the risk phase, the trigger and claim calculation should be done on the portal itself;
an SMS notification should be sent to the insured farmer and the claim due credited to his bank
account directly.
9. Historical yields at the desired insurable yields are needed for calculating the risk profile and
premiums. This data is generally not available at the desired scale. Depending upon the need
and urgency, the state governments in collaboration with AICI should commission projects to
develop such estimates of threshold yields of major crops at the desired insurable unit scale for
the past 10 years. Both agencies should make data of CCEs and block/tehsil yields available
for this purpose. The approach used should be the same as finalised for CCEs (see earlier
recommendation #5) in order to have consistency in the process for generating threshold yields
and premium rates.
10. Wherever WBCIS is to be implemented, agro-ecological region-specific weather triggers should
be redeveloped using integrated approach of statistics, historical weather data, crop models and
remote sensing data that can maximise the farmer’s satisfaction, and optimise the loss ratio while
keeping premiums within limit.
11. The state governments in collaboration with AICI and research institutes having understanding
of crop-weather relations should scientifically delineate clusters of districts/blocks with equitable
business opportunities for the insurance industry based on climatic risk profiles of the regions
together with the number of potential farmers to be insured, crops to be insured and infrastructure
available in the region. Basic premium rates for various clusters should also be identified to
eliminate the issues of over and under-pricing. An application/module for automated premium
calculation framework (yield index schemes) should be developed and tested for a few districts
and crops on a pilot mode.
12. An independent tool that uses seasonal and short-term weather forecasts, historical databases,
satellite images, and current weather data should be developed to provide a double trigger
product for mid-season claim calculation and ‘on-account’ payment to the insured as well as
a yield index for final loss assessment and claim settlement. The Ministry of Agriculture and
Farmers’ Welfare should explore expanding the scope of its FASAL program for this purpose. xi
13. The importance of livestock and aquaculture in Indian economy is growing and hence we
need to have effective insurance policies for them. There are several technologies that have
become available in recent times that can be used to increase livestock insurance. The use of
RFID technology, for example, can replace retagging of animals at policy renewal. Portability of
tag number across insurers can be operationalized for continuation of insurance. Index based
insurance schemes and ICT technologies can be piloted in livestock as well as fishery sectors.
There are, however, several institutional and policy issues related to livestock and fisheries
insurance sector which need to be addressed simultaneously. The Task Force recommends that
two independent groups be established on (a) livestock and (b) fisheries and aquaculture, to
develop comprehensive insurance plans for the respective sectors.
14. The central government should consider urgently establishing a dedicated mechanism either
within the existing institutions or by creating a new autonomous agency to coordinate among
various stakeholders including farmer groups, industry, different government ministries and
departments, banks and technology providers related to insurance in agriculture and allied
sectors. The same agency should also be mandated to support, monitor and improve insurance
services at the national scale. This could also include efficient data collection, storage, and
transfer between the stakeholders of different agencies. Similarly, the state governments should
consider establishing formal or informal units for crop insurance purpose where experts from
agriculture, remote sensing, ICT and insurance industry can come together to deliberate on
issues related to crop insurance in the state and advise the government and other stakeholders
on all related issues.
15. Developing innovative insurance products as well as greater use of technology in implementing
and monitoring crop insurance would need budget. It is recommended that a sum of 0.25 percent
of the premium collected every year should be made available for such purpose and should be
contributed by the central government, state government and insurance industry. xiiEnhancing technology use in agriculture insurance 1
1.1 Despite impressive development of agricultural infrastructure and irrigation
potential, a large part of Indian agriculture still remains exposed to climatic risks.
Crop insurance provides a safety-net for farmers to mitigate losses arising from
climatic shocks and also encourages them to continue to invest in inputs and
technology to increase yields and household income.
1.2 Although the need for crop insurance in India was debated since India became
independent, no serious efforts were made to implement it. Between 1947 and
1985, there were isolated schemes of crop insurance. These pilot schemes
were generally crop or location specific. In 1979, a scheme based on area
approach as suggested by V.M. Dandekar, linking crop insurance with credit,
was implemented by the General Insurance Corporation of India (GIC). Under this
scheme, the farmer was to be compensated in case of a shortfall in yield in the
area. The central government decided to introduce a country-wide crop insurance
scheme commencing from Kharif season of 1985 called Comprehensive Crop
Insurance Scheme (CCIS). The CCIS was also based on the approach described
by Dandekar (1979). This approach was ‘Area’ based and the farmer was liable
for compensation if there was a short-fall in the actual average yield per hectare
in the area as compared to the threshold yield as obtained on the basis of normal
yield. A few modifications and improvements were made to this Scheme and
subsequently the National Agricultural Insurance Scheme (NAIS) was launched
from Rabi 1999. This was further improved and the
Modified NAIS (MNAIS) was launched on a pilot basis
from Rabi 2010-11. It remained a pilot scheme till Kharif
2014. Subsequently it became a full-fledged scheme
under the National Crop Insurance Programme (NCIP).
Full details of these schemes, their operational details
and challenges can be found in the 2014 PK Mishra
Committee Report of the Government of India (www.
http://agricoop.nic.in/Admin_Agricoop/Uploaded_File/
Rpt_pkm2.pdf).
1. Introduction 2Enhancing technology use in agriculture insurance
1.3 A revamped, comprehensive and transformative insurance scheme called Pradhan Mantri Fasal
Bima Yojana (PMFBY) has been launched by the Government of India from Kharif 2016. The
PMFBY aims at supporting sustainable production in agriculture sector through (a) financial
support to farmers suffering crop loss/damage arising out of unforeseen events, (b) stabilization
of farmers’ income to ensure continuity in farming, (c) encouragement to farmers to adopt
innovative and modern agricultural practices, and (d) ensuring flow of credit to the agriculture
sector, which will contribute to food security, crop diversification, growth enhancement and
competitiveness of agriculture sector besides protecting farmers from production risks. It has
been conceptualised to address the operational and implementation problems of previous
schemes and incorporate various recommendations of Mishra Committee. The new scheme
will cover both yield losses and farm harvest losses, and also provide farm level assessment
for calamities. It is designed to operate across an insurable unit (village/Gram Panchayat) and
aims to double the coverage of farmers across the country from the current 23 percent of total
farming households to 50 percent in the next few years.
1.4 Use of technology has been proposed as a major input in the operations considering
the large diversity in climate, crops, cropping practices, agriculture infrastructure across
the country, and the limited capacity across government departments and implementing
insurance companies to effectively manage and monitor the scheme. However, guidelines
on what technologies to use for various insurance processes are not clearly specified in the
PMFBY and as a result not well-understood by relevant stakeholders. Several states had
requested for clarifications and guidance from the NITI Aayog to improve this understanding
and facilitate the development and implementation of relevant tools and instruments under
the PMFBY program. A Task Force was, therefore, constituted by the NITI Aayog under the
Chairmanship of Prof. Pramod K. Aggarwal of the CGIAR Research Program on Climate
Change, Agriculture and Food Security, Borlaug Institute for South Asia, CIMMYT, and under
the overall guidance of Prof. Ramesh Chand, Member, NITI Aayog to address the issues
related to the use of technology for agriculture insurance. The composition of the Task Force
is attached as Appendix A. To address the issue of technology support in crop insurance,
the Task Force constituted 5 sub-groups: 1. Remote Sensing & Drones; 2. Decision Support
Systems, Crop Modelling & Integrated Approaches; 3. IT/ICT in Insurance; 4. Crop Cutting
Experiments; and 5. Technologies for Livestock and Aquaculture Insurance. Each sub-group
had several discussions together with experts in the fields and submitted draft reports. More
than 100 experts related to professional research agencies, insurance industry, banks, and the
government contributed to these discussions. Technological options available in the country
and abroad were considered by all groups.
1.5 The Task Force concluded that several opportunities exist for applying technologies to increase
the efficacy and efficiency of the crop insurance program particularly in the process of 3
farmers’ enrolment, objective and convenient way of establishing insurable interest, developing
scientific weather triggers for WBCIS product development, data sharing among farmers and
insurers, banks and insurers and insurers and banks/farmers, and objective as well as real-
time assessment of crop yields and loss assessment due to various perils. These technologies
besides bringing objectivity to the insurance process would also increase its efficiency and cost
effectiveness. In the following sections of the document, solutions have been identified for key
challenges of the insurance sector and appropriate recommendations have been made keeping
in mind a clear focus on operational implementation. Some recommendations simplify or facilitate
the operational processes that can be implemented directly while other recommendations
propose mechanisms for establishing a stronger evidence base for technology use through rapid
but rigorous analyses. 4Enhancing technology use in agriculture insurance
2. Enrolment in
Crop Insurance
2.1 Key challenges
2.1.1 Almost 30 million farmers (25 percent of households) are covered today by the
Indian crop insurance program. The PMFBY aims to expand the coverage of
farmers across the country to 50 percent of farming households in the span of next
2 to 3 years. However, even today, the insurance cover is largely availed by the
loanee-farmers for whom this is compulsory. There is a need to increase awareness
among farmers, especially in climatic risk prone regions, and also among non-
loanee farmers, about crop insurance, risks covered, government schemes and
subsidies available and their benefits. To ensure retention of farmers in crop
insurance program on a sustained basis, satisfaction of the farmers with scheme
implementation is critical. Farmers’ satisfaction is linked to the information available
to them during enrolment about the availability of scientifically designed products,
quick enrolment process and more importantly about the claim settlement process
that is simple, quick and linked to the actual damage. A large number of co-
operative banks, which are often in the fore-front of the enrolment process, are not
yet computerised. The hard copy data flow to the banking and insurance industry
is sluggish and therefore limits enrolment as well as claim settlement.
2.2 Technology solutions
2.2.1 There are several technological opportunities today,
especially in ICT/IT sector, that can be used to
accelerate the process of enrolment in the crop
insurance program. Besides conventional extension
mechanisms such as radio, television and newspapers,
IT and ICT technologies such as mobile applications,
Kisan Call Centres, voice blasts, IVRS and SMS 5
can be used to raise the awareness of farmers about the insurance products. Further, IT
infrastructure of Gram Panchayat, Common Service Centres and internet café, etc., can be
used as insurance information centres. Participatory videos/films, where farmers record their
own experiences, and showing them to a large number of other farmer groups is becoming
a very powerful and effective tool in agricultural extension. This simple participatory process,
if linked with enrolment process, could significantly raise participation in the insurance
programs. In the near future, an insurance service on the lines of 139 by IRCTC may be
started for crop insurance.
2.2.2 Several portals have already been developed for the implementation of crop insurance;
however, none of them include holistic approaches covering all processes from customer
enrolment to claim settlement. The portals also lack connectivity with CBS, and the payment
gateway is still to be integrated. ICT can help to reach the farmers at the grass roots and
assist them in overcoming the challenges currently posed in the manual registration process.
Mobile/tablet based applications can ensure ease of registration, payment of premium and
issuance of e-receipts. A mobile App for dissemination of crop insurance has already been
developed. The mobile App facilities should be extended to enrol non-loanee farmers with
payment gateways. Further, the enrolment process with banks and national portal should be
available 24×7 till the cut-off date.
2.2.3 In respect of loanee-farmers, the insurance portal’s bulk uploading facilities should be
improved. The National Crop Insurance Portal available at www.agri-insurance.gov.in has
been designed as an integrated platform for all stakeholders – states, insurance companies,
banks and farmers. Different states have different hierarchies and they need to be integrated
with the portal so that all missing links like the Revenue Circle in Maharashtra, Firka in Tamil
Nadu, and Nyaya Panchayat in Uttar Pradesh, etc., can be covered. The codes and fields
of CBS and the National Portal also need to be matched so as to facilitate seamless flow
of data. Banks with CBS capability already have the details of loanee-farmers opting for
agricultural credit and that information can be directly transferred to the National Portal for
their enrolment. Online web-form or excel sheets uploaded with correct codes could be used
till the time CBS is connected.
2.2.4 The absence of digitized land records and cadastral maps creates big hurdles in the
enrolment process. A strong geo-referenced cadastral map base and its linkage with details
of the land records will help in controlling the menace of over reporting of the insured area
and easing the enrolment process. The responsibility of providing land records should
be given to the concerned government department instead of the farmers. Lessons from
the Bhumi project of the Karnataka could be very educative. Database protocols of using 6Enhancing technology use in agriculture insurance
standard coding patterns for the land records should be followed by every state for seamless
integration into the National portal.
2.2.5 As per the present guidelines of the PMFBY, a sowing certificate is required if declared crop
is changed after the enrolment, sometimes necessitated by various exigencies. This causes
confusion, increases administrative load and discourages farmers from enrolment in the
insurance program.
2.3 Recommendations
2.3.1 To increase insurance literacy, the state governments should urgently commission the
development of a comprehensive mobile-based application (App) that has 24x7 links with the
payment gateways/e-wallets to facilitate ease of registration, online payment of premium and
issuance of instant e-receipts. This should have links with the National Crop Insurance Portal
available at www.agri-insurance.gov.in. This data should be simultaneously accessible to
insurance companies, bankers and state government departments.
2.3.2 The states should commission major campaigns during the enrolment period in every crop
season by using participatory videos, and other ICT tools such as voice blasts, IVRS and
SMS, to increase awareness and insurance literacy. Together with related banks and insurance
industry they should simultaneously arrange for on-the-spot enrolment in crop insurance with
the use of customised mobile App.
2.3.3. To reduce farmers’ discomfort with the enrolment process, PMFBY guidelines should be
relaxed to accept geo-tagged and time-stamped digital photographs of land to establish the
insurable interest instead of manual certificates. Such photographs submitted by the farmers
should be accepted as sowing certificates if the declared crop is changed after the payment of
premium.
2.3.4. Digitising geo-referenced records of land holding is critical for reducing moral hazards in crop
insurance. This work is currently being done in the states at a varied pace. Development of a
strong geo-referenced and regularly updated cadastral map base and its linkage with different
land records should be accelerated and completed in a time-bound manner. Bhumi project
of Karnataka government has shown considerable progress in this aspect and could provide
lessons for other states. 7
3. Crop Loss
Assessment
3.1 Key challenges
3.1.1 Accurate loss or damage assessment is the most important component of an
insurance scheme for all stakeholders. This assessment is currently done using
either a weather index (for WBCIS) or a stratified CCE when yield is used as an
index. Weather indices have not worked well in the past due to limited density of
weather stations, their maintenance, and large spatial and temporal variability in
weather.
3.1.2 Currently in the country around 9 lakh CCEs are being conducted for General
Crop Estimation Survey. With the requirement of carrying out at least 4 CCEs per
insurable unit of village/village panchayat for each crop, this number may become
very large considering there are around 2.3 lakh village panchayats in the country.
Assuming that 40 lakh CCEs would need to be done and each CCE costs a
minimum of 1000 rupees, it would cost more than Rs. 400 crore every year to
conduct CCEs. Since CCEs need to be generally conducted within a time frame
of 15-20 days in a season, there will be a massive need of trained manpower to
manage, monitor and report them in time. Carrying out so many CCEs rigorously
is extremely difficult and time consuming. Over the
years CCEs have lost their credibility owing to such
complexities, human bias, measuring errors, high labour,
time and cost intensive design, and their limitation in
covering spatial and temporal basis risks, objective
monitoring, reporting and verification process. It is
also noted that the states often have two sets of yield
estimates - one for production statistics and the other
for payment of crop insurance claims. This brings further
confusion and subjectivity in the estimates of crop yield
and losses. 8Enhancing technology use in agriculture insurance
3.1.3 Localised calamities such as hailstorms, flash floods, and post-harvest rains have
increasingly become a source of concern. In the last few years, we have witnessed
widespread hailstorms in some villages of Maharashtra, localised floods in some parts of
Rajasthan and unseasonal rainfalls after harvest of crops in many states. Loss assessment
due to these remains a challenge because of verification methods.
3.2 Technology solutions
3.2.1 Fortunately, there are a number of technological solutions available today that can support
objective assessment of crop losses at the desired scale. These include satellite based
remote sensing (RS), Unmanned Aerial Vehicles (UAVs), digital geo-referenced photographs,
integrated crop yield assessment models, and statistical sampling techniques. Remote
sensing technique is rapid and the technology is used routinely for acreage estimation and
in combination with regression/crop models to estimate yields in many parts of the world,
especially in non-cloudy (such as Rabi) seasons. UAVs appear to be promising, especially
under cloud (Kharif) conditions, but there are many key challenges with linking their signals
with crop performance, possible interference with national security guidelines, and their
costs-benefits, which are not yet fully understood. There are as yet no clear success stories
with UAVs for crop loss assessment in India although they can play a critical role for the
assessment of localised perils such as hailstorms and flood related damages. More research
is needed to fully understand their scope and limitations before they can be employed for
crop loss assessment. Similar are the limitations of the picture based technologies where loss
libraries are yet to be developed based on systematic and rigorous scientific experiments.
An integrated approach linking RS signals and crowd-sourced agronomic inputs with crop
models can provide a very suitable tool for loss assessment. Initial experiments done by
the Maharashtra Government, KISAN project of the Ministry of Agriculture and many other
independent agencies in this respect appear to be promising. Small area statistical sampling
design approach is another promising approach to reduce the number of CCEs if suitable
and easily measurable yield proxies could be identified.
3.2.2 However, all these tools have been tested in research mode or in small pilots in a few states.
There is an urgent need to examine their suitability for operational purpose on a large-scale,
which should include understanding the scope, limitations in loss assessment, costs-
benefits, technical capacity in different regions to implement, monitor, report and verify in a
given time frame and developing protocols to be followed. This has to be complemented by
a scientifically designed CCE sampling strategy where a small number of high quality CCEs
are conducted, monitored and reported by experts from SAUs, KVKs or other competent
agencies. These institutions have large scientific and technical capacity and routinely do 9
such sampling for their own purposes. Such CCEs can be used to calibrate/validate/verify/
supplement various technological solutions.
3.3 Recommendations
3.3.1 The Task Force is of the view that although CCEs are central to the insurance scheme, they are
not serving much purpose in their present form because of the financial, scientific, institutional
and operational challenges associated with them. Moreover, they do not necessarily provide
good estimates of yield loss over insurance units in a timely manner. It was noted that remote
sensing, digital photography, statistical methods, integrated crop modelling, and a combination
of these options can provide an objective and unbiased assessment of crop yield losses well
in-time and at a fraction of the current CCE costs. There is an urgent need to identify the most
suitable technology option for every state and associated operational guidelines. Capacity
to undertake such work in India is available with institutes/centres of ISRO, ICAR, and IMD,
MNCFC, IT/ICT agencies, state agricultural universities, state remote sensing centres, CGIAR
research centres, and private companies.
The Task Force, therefore, recommends that CCEs
in their present form must be replaced in a phased manner with technological solutions for
crop loss assessment. The following approach is proposed for developing protocols for loss
assessment:
a. All state governments with a large stake in crop insurance should immediately commission
a 12-month project for a comparative evaluation and deciding on the suitability of
technological options for agro-ecological diversity in the state. The project should propose
the most suitable approach to provide robust estimates of crop yields at individual village/
village panchayat level along with cost-benefit analysis of the operations, and assessment
of technical capacity to implement this in an operational manner. For this work, the state
governments and insurance industry should allocate 0.20 percent premium.
b. The project should also propose a scientifically designed sampling strategy for a few very
high quality CCEs at block/tehsil/district/agro-ecological zones level in the state which can
be independently used to supplement/calibrate/validate/verify the technology proposed for
loss assessment.
c. Conducting these few and high quality CCEs should be the responsibility of the state
government and should be guided and monitored by independent experts from state
agricultural universities and their associated Krishi Vigyan Kendras/reputed agricultural
NGOs. The entire CCE must be digitally recorded so that it can be witnessed by anyone,
and be publicly available. 10Enhancing technology use in agriculture insurance
d. The above approach should be tested in at least 10 percent districts in Rabi 2017-18 and
Kharif 2018. Subsequently, the whole experience should be reviewed, calibrated, and
applied in the entire state from Rabi 2018-19.
e. For the time being, all CCEs should be witnessed, monitored and reported using mobile
Apps involving the staff of SAUs/KVKs, farmers, agriculture departments and insurance
companies.
3.3.2 Although there are several satellites today that can support crop insurance sector, it is
recommended that a dedicated constellation of 3-4 satellites of high to moderate resolution
(10-30 m) with 10-days frequency and with multispectral optical sensors and two microwave
satellites and one hyper-spectral satellite may be deployed to increase the precision of crop
yield estimates/loss assessment at the village scale.
3.3.3 Crop losses due to localised climatic events such as hailstorms, landslides, small floods and
post-harvest losses, where CCE data do not play a role, need to be supported by a mobile
based App. A separate mechanism for such data collection, visualisation and customisation
needs to be developed. The experience of the Karnataka Government for mango and grape
could provide lessons for such an App 11
4. Claim
Settlement
4.1 Key challenges
4.1.1 Accurate loss assessment and its timely reporting are prerequisites for faster
and accurate claim settlement. Satisfaction of farmers with insurance is mainly
associated with quick claim settlements. Owing to the complex nature of loss
assessment associated with CCEs, large delays running into 6-12 months have
been observed in the process of claim settlement and transfer of money to the
farmers. Normally, the cut-off date for data (yield/weather) submission of CCEs
is fixed at one/two months from harvesting time but this is not always followed.
Sometimes, the submission of yield data by the various agencies involved in the
process is done in a piece-meal manner. There are quality issues as well with the
submitted data. Submitted data may not be acceptable to the industry since it is
based on less than the requisite number of CCEs. Occasionally the submitted CCE
data is also revised.
4.1.2 Although the process of submission of weather data in WBCIS is much easier, but
certification, data quality checks and replacement of missing datasets take time
and cause delayed submission.
4.1.3 Claims are also partially delayed by the lack of automation in claim calculation and
direct transfer of the payments to the insured farmer.
4.2 Technology solutions
4.2.1 The efficiency of the claim settlement process can be
considerably enhanced by automation. A mobile App
(CCE-Agri) has already been developed by the Ministry
of Agriculture and Farmers’ Welfare to digitize and
witness the CCEs. The CCEs data through this App is
directly uploaded to the web portal. Protocols further 12Enhancing technology use in agriculture insurance
need to be developed to process CCEs data and calculate loss and claim estimation. For
weather index insurance scheme, the weather data flow should be assured to the portal on a
real-time basis. On completion of the risk phase, the trigger and claim calculation should be
done on the portal itself and accordingly a notification should be sent to the farmer about the
claim. Once the claim is assessed based on the crop loss or weather index, it should instantly
be directly credited to the bank account of the insured farmer. The entire process of claim
settlement and transfer of money has to be shared with the insured farmer through the SMS
alert at each stage.
4.3 Recommendations
4.3.1 The Ministry of Agriculture and Farmers’ Welfare should expand their mobile App - CCE-Agri -
to process CCEs data and weather data to calculate the loss and claim estimation in real-time.
On completion of the risk phase, the trigger and claim calculation should be done on the portal
itself and an SMS notification be sent to the insured farmer and the claim due credited directly
to his bank account. 13
5. Product
Design and
Development
5.1 Key challenges
5.1.1 Designing an appropriate insurance product and suitably pricing it require a good
analysis of available crop yield data, threshold yields (based on the last 7 years)
and various other factors at the village/panchayat level in PMFBY. Such data is
normally available only at district level and at block level in some states. For some
minor crops, such yield series do not exist. This causes problems in designing
a suitable product. Even for WBCIS, triggers are often used without a scientific
basis resulting in payments when risks and consequent yield losses are minimal or
vice-versa.
5.1.2 PMFBY is implemented in the states by insurance companies who compete for
business by quoting their premium rates. These companies quote premium rates
based on their business strategy. It was informed to the Task Force that the rates
quoted in the last season for the same crop in the same state/district sometimes
varied by 8 times. In the absence of any mechanism with the governments to
calculate the burning cost or loss cost for addressing the issues of over and
under- pricing by the insurance providers and its
relation with the climatic risks in the region, the decision
making by the state government becomes difficult.
5.1.3 The states are currently using a cluster approach where
several districts are pooled and given to one insurance
company for business over a period of time. This is
perhaps done based on administrative convenience for
providing sufficient long-term business to companies.
However, since this does not have a link to climatic
risks and volume of business, such clusters become 14Enhancing technology use in agriculture insurance
unequal leading to unfair competition. Small companies may often find it difficult to participate
in large clusters with large insurable risks.
5.2 Technology solutions
5.2.1 Several statistical, remote sensing and modelling approaches have the potential to generate
yield series at the insurable units by using proxies of historical weather, crop management
details, NDVIs, and district/block level crop yields. However, they have not yet been applied
for this purpose in our country. If data on block level yields of high quality CCEs done in past is
made available, it should be possible for practitioners familiar with the above tools to construct
such historical yield series with some confidence.
5.2.2 Integrated approach of using statistics, dynamic weather and satellite data and crop growth
models has been shown to result in scientifically designed agro-ecological region- specific
weather triggers that can maximise farmers’ satisfaction and optimise loss ratio while keeping
premiums within limit. Such methodologies need to be encouraged. For some crops, if the
yield and weather relationship is not clearly established, pilot projects can be undertaken on the
lines of the All India Coordinated Research Projects for identification of WBCIS triggers.
5.2.3 Various tools and products are available that characterise climatic risks of India even by
cropping season. Gridded weather data has also been made available by the IMD and
various other global agencies that can support such characterisation. Such data on climatic
risks together with the number of potential farmers to be insured, crops to be insured and
infrastructure available in the region should be used to scientifically delineate clusters with
equitable business opportunities for the insurance industry.
5.3 Recommendations
5.3.1 Historical yields at the desired insurable yields are needed for calculating risk profile and
premiums. This data is generally not available at the desired scale. Depending upon the need
and urgency, the state governments in collaboration with AICI should commission projects to
develop such estimates of threshold yields of major crops at the desired insurable unit scale
for the past 10 years. Both agencies should make the data of CCEs and block/tehsil yields
available for this purpose. The approach used should be the same as finalised for CCEs
(see earlier recommendation #5) in order to have consistency in the process for generating
threshold yields and premium rates. 15
5.3.2 Wherever WBCIS is to be implemented, agro-ecological region-specific weather triggers should
be redeveloped using integrated approach of statistics, historical weather data, crop models
and remote sensing data that can maximise farmers’ satisfaction and optimise the loss ratio
while keeping premiums within limit.
5.3.3 The state governments in collaboration with AICI and research institutes having understanding
of crop-weather relations should scientifically delineate clusters of districts/blocks with
equitable business opportunities for the insurance industry based on climatic risk profiles of
the regions together with the number of potential farmers to be insured, crops to be insured
and infrastructure available in the region. Basic premium rates for various clusters should
also be identified to eliminate the issues of over and under-pricing. An application/module for
automated premium calculation framework (yield index schemes) should be developed and
tested for a few districts and crops on a pilot mode. 16Enhancing technology use in agriculture insurance
6. In-season Crop
Yield Loss
Assessment
(on Account Payment)
6.1 Key challenges
6.1.1 For the government as well as insurance industry it is important to keep track of
disaggregated crop conditions and losses on a real-time basis. It serves several
purposes such as satisfying demands from reinsurance industry about the probable
losses, targeting of CCEs for better loss assessment, making informed decisions
and planning for claim volume, and better preparedness for settling claims after
crop harvest. Such information is also very useful for making mid-season on-
account payments to the insured when they need compensation the most rather
than waiting for the claim settlement after the harvest of the crop.
6.2 Technology solutions
6.2.1 India has a system of crop yield estimation which is
based on traditional crop cuts, surveys and reports
from the District Agricultural Offices. Additionally, many
agencies undertake field verifications and consultations
to collect additional information on crop performance.
Many agencies like MNCFC, IMD, SAC, ICAR, IARI,
NCAER, etc., provide aggregated crop outlooks to
the government. FASAL programme of the Ministry of
Agriculture and Farmers’ Welfare is worth mentioning in
this context. It uses remote sensing inputs, crop models
and government statistics to develop crop outlooks. 17
Globally there are many such tools as FEWS NET in Africa and Caribbean, MARS in Europe,
Cropland Data Layer in USA, AMIS Crop Monitor of GEOGLAM and CropWatch of China.
With some modifications, such tools can be tailored to meet the requirements of estimating
probable crop yield losses at a disaggregated scale for the crop insurance sector.
6.2.2 Satellite weather data is now easily available. Though there are some issues about its accuracy
and the scale for final claim payment, it is of sufficient accuracy, once corrected for bias with
in situ data, to make a preliminary estimate of crop losses during the crop season. This could
be used mid-season to make initial 25-50 percent of the claim payment to the insured pending
his full settlement based on a yield index after the harvest of the crop. Such a double trigger
product would help the insured farmer in time to address his agrarian distress.
6.3 Recommendations
6.3.1 An independent tool that uses seasonal and short-term weather forecasts, historical
databases, satellite images, and current weather data should be developed to provide a double
trigger product for mid-season claim calculation and ‘on-account’ payment to the insured as
well as a yield index for final loss assessment and claim settlement. The Ministry of Agriculture
and Farmers’ Welfare should explore expanding the scope of its FASAL program for this
purpose. 18Enhancing technology use in agriculture insurance
7. Livestock and
Aquaculture
Insurance
7.1 Key challenges
7.1.1 India has 56.7 percent of world’s buffaloes and 12.5 percent of world’s cows
and bullocks. Besides, fisheries and aquaculture is one of the fast growing sub-
sectors that contributes to nearly 4.8 percent of value of output from agriculture
and allied sectors in India. India is, however, far behind in insuring its huge
livestock population as only 6 percent of the cattle population and less than 0.6
percent of the cattle owners in India are insured. Since farmers depend a lot on
livestock when crops suffer losses due to climatic stresses, it is critical that they
are provided the benefits of livestock insurance. Cattle insurance is mandatory for
availing bank credit for dairying activities. More than 90 percent of cattle insurance
premium underwritten is through this model. The different methods used for
animal identification are ear tagging, ear notching, freeze band numbering, muzzle
printing, etc. ‘No tag no claim’ is a general principle followed by all the insurance
companies. Insurance as a risk transfer mechanism is by far under-utilized in
the fishery sector also. Except for the presence of a few public sector insurance
companies and cooperative bodies at the local levels
whose scale of operation and coverage is abysmally
low, the sector has received little attention either at the
central or state levels. The private sector operation in
this arena is also limited to a few cases scattered over
time and space.
7.2 Technology solutions
7.2.1 The painful process of tagging can be replaced with the
use of new technologies such as RFID, Genome Tagging 19
or DNA testing, ZigBee mobile technology, etc. Mobile phone based technologies can be
effectively used in reducing policy inception and claim settlement time.
7.2.2 Technology can play a vital role in improving efficiency, bringing transparency and reducing
moral hazards in fishery insurance. Advanced ICT tools and GIS platforms for developing
inventory data base (on variables such as locations with GPS coordinates, date of stocking,
stock sizes, and progress of the crop; hydro-acoustics and digital video survey can be used
for assessing the crop loss, etc.) of insured farmers could be put to use, which would not
only simplify monitoring procedures but also make them transparent and the farming practice
more technology oriented. Innovative products such as weather-index and yield-index based
insurance schemes in crop sector can be extended to fisheries sector as well, to harness the
potential of technology for increasing efficiency and simplifying procedures.
7.2.3 The Government of India is presently working on mechanisms to track vessels operating in
India’s Exclusive Economic Zone (EEZ). Advanced Vessel Monitoring Systems (VMS) could be
made use of to track the fishing vessels and assess incidents such as mid-sea capsizing and
collisions. Awareness among fishermen and aqua-farmers needs to be created about various
insurance programs and the provisions involved.
7.3 Recommendations
7.3.1 The importance of livestock and aquaculture in Indian economy is growing and hence we
need to have effective insurance policies for them. There are several technologies that have
become available in recent times that can be used to increase livestock insurance. Use of
RFID technology, for example, can replace retagging of animals at policy renewal. Portability of
tag number across insurers can be operationalized for continuation of insurance. Index based
insurance schemes and ICT technologies can be piloted in livestock as well as fishery sector.
There are, however, several institutional and policy issues related to livestock and fisheries
insurance sector which need to be addressed simultaneously. The Task Force recommends
that two independent groups be established on (a) livestock and (b) fisheries and aquaculture,
to develop comprehensive insurance plans for the respective sectors. 20Enhancing technology use in agriculture insurance
8. Institutional
Mechanisms
for Technology
Use in Crop
Insurance
8.1 Key challenges
8.1.1 Agricultural insurance sector is complicated because of a very large and dispersed
population of smallholder farmers who practice agriculture in different agro-
ecologies with varying climates, farming systems, and agronomic management.
These diversities linked with weather adversities result in crop losses of large
magnitude every year at least in some states. Climate change is likely to further
increase such risks. Technology use for enrolment, loss assessment and claim
settlement is therefore a must. However, there is no formal institutional mechanism
in Indian agricultural insurance sector to develop,
manage and operationalise these technological
opportunities. It is felt that a centralised agency is
needed to coordinate among various stakeholders
including farmer groups, insurance industry, government,
banks, and technology providers. The same agency
should also be mandated to support, monitor and
improve insurance services at the national scale.
8.1.2 There is also a need for some sort of coordination
between stakeholders even at the state level, especially 21
for making technology recommendations. Every state has the related expertise in their
agricultural universities, regional/state remote sensing centres, IT agencies, and private sector.
India Meteorology Department has in every agro-ecological region a relatively ‘informal’ AFMU
(Agriculture Field Monitoring Unit) that synthesises all agricultural information related to climatic
events and provides value-added information to all stakeholders including farmers using ICT
mechanisms. The state governments should consider establishing similar formal or informal
units for crop insurance purpose where experts from agriculture, remote sensing, ICT and
insurance industry can come together to deliberate on issues related to crop insurance in the
state and advise the government and other stakeholders on all related issues.
8.2 Recommendations
8.2.1 The central government should consider urgently establishing a dedicated mechanism
either within the existing institutions or by creating a new autonomous agency to coordinate
among various stakeholders including farmer groups, industry, different government ministries
and departments, banks and technology providers related to insurance in agriculture and
allied sectors. The same agency should also be mandated to support, monitor and improve
insurance services at the national scale. This could also include efficient data collection,
storage, and transfer between the stakeholders of different agencies. Similarly, the state
governments should consider establishing formal or informal units for crop insurance purpose
where experts from agriculture, remote sensing, ICT and insurance industry can come together
to deliberate on issues related to crop insurance in the state and advise the government and
other stakeholders on all related issues.
8.2.2 Developing innovative insurance products as well as greater use of technology in implementing
and monitoring crop insurance would need budget. It is recommended that a sum of 0.25
percent of the premium every year should be made available for such purpose and should be
contributed by the central government, state government and insurance industry. 22Enhancing technology use in agriculture insurance
Annexure-I
Constitution of the Task Force
• Pramod K. Aggarwal (Chairman, Task Force), Regional Program Leader, CGIAR, Research
Programme on Climate Change, Agriculture & Food Security (CCAFS), Bolraug Institute for South
Asia, CIMMYT, New Delhi.
• Ashish Bhutani, Joint Secy. (Credit), Department of Agriculture Cooperation & Farmers Welfare,
Government of India, Krishi Bhawan, New Delhi.
• O. P. Chaudhury, Joint Secy. (ANLM), Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi.
• A.K. Joshi, Joint Secy. (Fy.), Department of Animal Husbandry, Dairying & Fisheries, Government
of India, Krishi Bhawan, New Delhi.
• CMD, NABARD or, his nominee (Gautam Sen, DGM, DFI&BT Division), NABARD H.Q., Plot No
C-24, “G” Block Bandra-Kurla Complex, P.B.No 8121, Bandra(E), Mumbai - 400051.
• U.C. Sud, Director, Indian Agricultural Statistics Research Institute, Indian Council of Agricultural
Research, Pusa, New Delhi-110012.
• Representative of Co-operative Bank (Sh. C.N. Tarpara, Chief Executive Officer), District Central
Co Op. Bank Ltd., Rajkot, Gujarat.
• Representative of the Chairman, National Dairy Development Board, Anand, Gujrat.
• S.S. Ray, Director, Mahalanobis National Crop Forecast Centre, Department of Agriculture
Cooperation & Farmers Welfare, Government of India, Pusa, New Delhi.
• Principal Secretary (Agriculture), Govt. of Andhra Pradesh.
• Principal Secretary (Agriculture), Govt. of Gujarat.
• Principal Secretary (Agriculture), Govt. of Karnataka.
• C.S. Murthy, Head Crop Monitoring & Assessment Division, National Remote Sensing Centre,
Hyderabad.
• Sanjiv Mittal, Joint Secretary (IT), Department of Electronics and Information Technology,
Government of India, New Delhi.
• M. K. Poddar, General Manager, Agriculture Insurance Company Of India Limited, 13th Floor,
Ambadeep Building, 14 Kasturba Gadhi Marg, New Delhi, Delhi 110001.
• J. P. Mishra (Member-Secretary of the task force), Adviser (Agriculture), National Institute for
Transforming India (NITI) Aayog, New Delhi 23
Annexure-II
Sub Groups
Sub-Group 1. Remote Sensing & Drones
1. Y.V.N. Krishna Murthy, Director, National Remote Sensing Centre (NRSC), Hyderabad,
Chairman
2. C.S. Murthy, National Remote Sensing Centre (NRSC), Hyderabad, Member
3. T. P. Singh, Director, Bhaskaracharya Institute for Space Applications and Geo-Informatics
(BISAG), Gandhinagar, Gujarat, Member
4. Satish Raju, Swiss Re, Vaswani Centropolis, 2nd to 6th Floor, No. 21 Langford Road,
Bengaluru, Karnataka 560027, Member
5. M Sudhakar, SkyMet, 109, 1st Floor, Kushal Bazar, 32-33, Nehru Place, New Delhi, Delhi
110019, Member
6. R. N. Sahoo, Indian Agricultural Research Institute (IARI), PUSA, New Delhi, Member Secretary.
Sub-Group 2. Decision Support Systems, Crop Modelling & Integrated Approaches
1. Alok Sikka, International Water Management Institute (IWMI), NASC, Pus, New Delhi, Chairman
2. Principal Secretary (Agriculture), Govt. of Gujarat or, his nominee, Member
3. S. S. Ray, Director, Mahalanobis National Crop Forecast Centre (MNCFC), Department of
Agriculture Cooperation & Farmers Welfare, Government of India, Pusa, New Delhi, Member
4. K.K. Singh, India Meteorological Department (IMD), Lodhi Road, New Delhi, Member
5. Kolli N. Rao, IRICBS/ Aon Benfield, Member
6. Neha Agarwal, ICICI Lombard, Member
7. Naresh Kumar Soora, Indian Agricultural Research Institute (IARI)-ICAR, PUSA, New Delhi,
Member Secretary.
Sub-Group 3. IT/ ICT in Insurance
1. S.K. Goel, Former Additional Chief Secretary - Agriculture, Government of Maharashtra,
Chairman
2. Jt. Secy., DeitY, or, his representative, Member
3. P. Krishna Reddy, International Institute of Information Technology, Hyderabad, Andhra Pradesh,
Member
4. Jt. Secy., IT, MoA&FW or, his representative, Member
5. Gautam Sen, DGM, DFI&BT Division), NABARD H.Q., Plot No C-24, “G” Block Bandra-Kurla
Complex, P.B.No 8121, Bandra(E), Mumbai - 400051, Member
6. Alok Shukla, TATA AIG Gen. Insurance, Member
7. Aniruddha Shanbaug, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), Member
8. Paresh B Shirsath, CGIAR, Research Programme on Climate Change, Agriculture & Food
Security (CCAFS), Bolraug Institute for South Asia, CIMMYT, New Delhi, Member Secretary. 24Enhancing technology use in agriculture insurance
Sub-Group 4. Crop Cutting Experiments, CCEs
1. Vijay Kumar, Principal Secretary (Agriculture), Government of Andhra Pradesh, Chairman
2. U.C. Sud, Director, Director, Indian Agricultural Statistics Research Institute, Indian Council of
Agricultural Research, Pusa, New Delhi-110012, , Member
3. State Government Representatives (Maharashtra & Karnataka), Members
4. Director, ICAR – CIAE, Bhopal, Member
5. Representative of State Cooperative Bank, Gujarat, Member
6. A.K. Srivastava, Ex-NSSO, Member
7. Representative of DES, M/o Agri. & FW, Member
8. Ashok K. Yadav, Manager, Agriculture Insurance Company of India Limited, 13th Floor,
Ambadeep Building, 14 Kasturba Gadhi Marg, New Delhi, Delhi 110001, Member Secretary
Sub-Group 5. Livestock & Aquaculture
1. Dilip Kumar, Former Director/Vice Chancellor, Central Institute of Fisheries Education-ICAR,
Versova, Andheri West, Mumbai, Maharashtra 400061, Chairman.
2. Director, Central Marine Fisheries Research Institute-ICAR, Kochi, Kerala, Member
3. Director, National Dairy Research Institute (NDRI), Karnal, Haryana, Member
4. Jt. Secy. (Fy.), Department of Animal Husbandry, Dairying & Fisheries, Government of India,
Krishi Bhawan, New Delhi, Member
5. Jt. Secy., Livestock & Animal Health, Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi, Member
6. Representative of DHAN Foundation, Kennet Cross Road, Vaidyanathapuram East Madurai 625
016, Tamil Nadu, Member
7. Representative of New India Assurance Co. Ltd., Member
8. Fisheries Development Commissioner, Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi, Member
9. Animal Husbandry Commissioner, Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi, Member
10. M. K. Poddar, General Manager, Agriculture Insurance Company of India Limited, 13th Floor,
Ambadeep Building, 14 Kasturba Gadhi Marg, New Delhi, Delhi 110001, Member Secretary 26Enhancing technology use in agriculture insurance
National Institute for Transforming India (Niti) Aayog
Government of India
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December, 2016 02Enhancing technology use in agriculture insurance
Citation:
Aggarwal, P.K., Chand, R., Bhutani, A., Kumar, Vijay, Goel, S.K., Rao, K.N., Poddar, M.K., Sud, U.C., Krishna
Murthy, Y.V.N., Ray, S.S., Murthy, C.S., Sikka, A., Shirsath, P.B., Mishra, J.P., Choudhury, M., Chaudhury, O.P.,
Joshi, A.K., Sen, G., Tarpara, C.N., Kumar, D., Sahoo, R.N., Kumar, N.S., Yadav, A.K., Singh, T.P., Kannan, H.,
Satish Raju, G., Sudhakar, M., Singh, K.K., Agarwal, N., Reddy, P.K., Shukla, A., Shanbaug, A., Srivastava,
A.K., Mehta, S., Gupta, P.K., Gopalakrishnan, A., Chandel, B.S., Duggal, R.K., Deshmukh, V., Kotwaliwale,
N., Vora, P., Kumar, S. and Lochan, R. 2016. Report of the Task Force on ‘Enhancing Technology Use in
Agriculture Insurance’. NITI (National Institute for Transforming India) Aayog, Government of India. i
List of Abbreviationsiii
Prefacev
Executive Summaryvii
1. Introduction1
2. Enrolment in Crop Insurance4
2.1. Key challenges4
2.2. Technology solutions4
2.3. Recommendations6
3. Crop Loss Assessment7
3.1. Key challenges7
3.2. Technology solutions8
3.3. Recommendations9
4. Claim Settlement11
4.1. Key challenges11
4.2. Technology solutions11
4.3. Recommendations12
5. Product Design and Development13
5.1. Key challenges13
5.2. Technology solutions14
5.3. Recommendations14
6. In-season Crop Yield Loss Assessment (on Account Payment)16
6.1. Key challenges16
6.2. Technology solutions16
6.3. Recommendations17
7. Livestock and Aquaculture Insurance18
7.1. Key challenges18
7.2. Technology solutions18
7.3. Recommendations19
8. Institutional Mechanisms for Technology Use in Crop Insurance20
8.1. Key challenges20
8.2. Recommendations21
Constitution of the Task Force22
Sub Groups23
Contents iiEnhancing technology use in agriculture insurance iii
List of
Abbreviations
AFMU Agriculture Field Monitoring Units
AIC/ AICI Agriculture Insurance Company of India Limited
AMIS Alliance Marketing and Insurance Services
App Mobile-Based Application
CBS Core Banking Solution
CCE Crop Cutting Experiments
CCIS Comprehensive Crop Insurance Scheme
CCAFS CGIAR Research Program on Climate Change, Agriculture and Food Security
CIMMYT International Maize and Wheat Improvement Center
DAC&FW Department of Agriculture, Cooperation and Farmers Welfare
DAH,D&F Department of Animal Husbandry, Dairying & Fisheries
DCCB District Central Cooperative Bank
EEZ Exclusive Economic Zone
FASAL Forecasting Agricultural output using Space, Agro meteorology and Land based
observations
FEWS NET Famine Early Warning Systems Network
GEOGLAM Group on Earth Observations Global Agricultural Monitoring Initiative
GIC General Insurance Corporation of India
GIS Geographic Information Systems
GPS Global Positioning System
IARI Indian Agricultural Research Institute
ICAR Indian Council of Agricultural Research ivEnhancing technology use in agriculture insurance
ICAR-CIFE ICAR-Central Institute of Fisheries Education
ICAR-IASRI ICAR-Indian Agricultural Statistics Research Institute
IMD India Meteorological Department
IRCTC Indian Railway Catering & Tourism Corporation Ltd
ISRO Indian Space Research Organisation
IT/ICT Information Technology and Information and Communications Technology
IVRS Interactive Voice Response System
KISAN Crop Insurance using Space Technology and Geo informatics
KVK Krishi Vigyan Kendra
MARS Monitoring Agricultural Resources
MNAIS Modified NAIS
MNCFC Mahalanobis National Crop Forecast Centre
NABARD National Bank for Agriculture and Rural Development
NAIS National Agricultural Insurance Scheme
NCAER National Council of Applied Economic Research
NCIP National Crop Insurance Programme
NDDB National Dairy Development Board
NDVI Normalized Difference Vegetation Index
NRSC National Remote Sensing Centre
PMFBY Pradhan Mantri Fasal Bima Yojana
RFID Radio-Frequency Identification
RS Remote Sensing
SAC Space Applications Centre
SAU State Agricultural University
SMS Short Message Service
UAV Unmanned Aerial Vehicles
VMS Vessel Monitoring Systems
WBCIS Weather Based Crop Insurance Scheme v
Preface
Pradhan Mantri Fasal Bima Yojana (PMFBY) is a flagship scheme of the Government of India to
provide insurance coverage and financial support to farmers in the event of failure of any of the
notified crops, unsown area and damage to harvest produce as a result of natural calamities, pests
and diseases to stabilise the income of farmers, and to encourage them to adopt modern agricultural
practices. The scheme is a considerable improvement over all previous insurance schemes in India
and is heavily subsidised by the state and central governments. The scheme aims to cover 50 percent
of the farming households within next 3 years.
During its implementation in the last one season, several challenges relating to enrolment, yield
estimation, loss assessment, and claim settlement were reported by farmers, insurance companies
as well as the state governments. It was also noted that several technological opportunities existed
for possibly leveraging support to the Indian crop insurance program for enhanced efficiency and
effectiveness. NITI Aayog of the Government of India, therefore, constituted a Task Force to deliberate
on this subject and identify such potential opportunities. This report summarises the recommendations
of the Task Force.
The Task Force constituted to address the issue of technology support to crop insurance comprised
the following 5 sub-groups: (1) Remote Sensing & Drones; (2) Decision Support Systems, Crop
Modelling & Integrated Approaches; (3) IT/ICT in Insurance; (4) Crop Cutting Experiments (CCEs); and
(5) Technologies for Livestock and Aquaculture Insurance. Each sub-group had several discussions
with experts in the respective areas, and submitted draft reports. More than 100 experts related to
professional research agencies, insurance industry, banks, and the government contributed to these
discussions. Technological options available in the country and abroad were considered by all groups.
The Task Force together with the sub-groups then deliberated on key issues and formulated its
recommendations as presented in this report. During the discussions it was realised that there were
many administrative and institutional issues that needed to be addressed in PMFBY. However, the
focus of the Task Force was on its main mandate, technology use in crop insurance. We hope these
recommendations would help the Indian crop insurance sector take full advantage of the technological
options suggested so as to increase its efficacy and effectiveness leading to reduced agrarian distress
in the country. viEnhancing technology use in agriculture insurance
The Task Force is grateful to Dr. Arvind Panagariya, Vice Chairman, Dr. Ramesh Chand, Member and
Shri Amitabh Kant, CEO of NITI Aayog for constituting this Task Force, and to Dr. Ashish Bhutani of the
Ministry of Agriculture & Farmers’ Welfare for providing the government’s point of view. The Task Force
is also grateful to Dr. Sudhir Goel, former Additional Chief Secretary, Government of Maharashtra, Mr.
Vijay Kumar, former Additional Chief Secretary, Government of Andhra Pradesh, Dr. Alok Sikka, South
Asia Director of the International Water Management Institute, Dr. YVN Krishna Murthy, Director of the
National Remote Sensing Centre, and Dr. Dilip Kumar, former Director/Vice Chancellor of ICAR-CIFE
for chairing the sub-groups and advising the Task Force. vii
Executive
Summary
The Pradhan Mantri Fasal Bima Yojana (PMFBY) is a transformative scheme of the Government of
India to provide insurance coverage and financial support to farmers in the event of failure of any of
the notified crops, unsown area and loss of harvested produce as a result of natural calamities, pests
and diseases to stabilise the income of farmers, and to encourage them to adopt modern agricultural
practices. The scheme recognises the need for technological interventions in crop insurance to
make the insurance mechanism more efficient, transparent and farmer-friendly. Considering the
complexities associated with Indian agriculture such as small and scattered land holdings, very high
eco-geographical variability, yield variability and weather aberrations, it is imperative that technologies
are effectively used to increase the efficacy and effectiveness of the insurance sector.
For effective implementation of the PMFBY several technological options have been proposed such as
remote sensing technologies (satellite and Unmanned Aerial Vehicles − UAVs), smart-phones, digital
photography, new statistical techniques and modelling approaches, and IT/ICTs. Currently, there is a
modest use of IT/ICT in the insurance sector for enrolment and other operational issues. There have
been only some piecemeal studies on the use of technologies in other arenas like yield estimation, loss
assessment and product design despite the country having a large agriculture and space research
program, which has many potential technologies suitable for the insurance sector. However, the
evidence base of these technologies, under diverse agro-ecological regions of the country, is limited
to support their nationwide implementation in crop insurance program. A
comparative evaluation of different technologies has not been done so far
and often the states, researchers and insurance players have diverse views
on their use. The key technology providers for remote sensing are research
and academic organisations and private companies whereas IT/ICT and UAV
technology suppliers are largely private players. Other technologies such
as integrated assessment modelling, and statistics are still in the domain of
national and international research institutes.
The Task Force on “Use of Technology for Agriculture Insurance” constituted
by the NITI Aayog deliberated on this subject with almost 100 leading experts viiiEnhancing technology use in agriculture insurance
from research organisations, universities, insurance industry, the government, banks and other
stakeholders to recommend the key technologies for effective implementation of the PMFBY. The Task
Force noted several administrative and institutional challenges beyond its mandate that needed to
be addressed for effective implementation of the PMFBY apart from the use of technology. The Task
Force constituted five sub-groups to do a detailed assessment of technological options and to obtain
stakeholders’ feedback on various issues. The sub-groups were on: (1) Remote Sensing & Drones;
(2) Decision Support Systems, Crop Modelling & Integrated Approaches; (3) IT/ICT in Insurance;
(4) Crop Cutting Experiments (CCEs); and (5) Technologies for Livestock & Aquaculture Insurance.
After deliberating the reports from the five thematic sub-groups, the following recommendations on
enhancing technology use in agricultural insurance were made by the Task Force largely targeted
to the concerned ministries of state and central governments for action besides the crop insurance
industry, which needs to act on some of the recommendations and share the costs of implementation:
1. To increase insurance literacy, the state governments should urgently commission the
development of a comprehensive mobile-based application (App) that has 24x7 links with the
payment gateways/e-wallets to facilitate ease of registration, online payment of premium and
issue of instant e-receipts. This should have links with the National Crop Insurance Portal available
at www.agri-insurance.gov.in. This data should be simultaneously accessible to insurance
companies, bankers and the state government departments.
2. The states should commission major campaigns during the enrolment period in every crop
season using participatory videos, and other ICT tools such as voice blasts, IVRS and SMS, to
increase awareness and insurance literacy. Together with related banks and insurance industry
they should simultaneously arrange for on-the-spot enrolment in crop insurance using the
customised mobile App.
3. To reduce farmers’ discomfort with the enrolment process, PMFBY guidelines should be relaxed
to accept geo-tagged and time-stamped digital photographs of land to establish the insurable
interest instead of manual certificates. Such photographs submitted by the farmers should be
accepted as sowing certificates if the declared crop is changed after the payment of premium.
4. Digitising geo-referenced records of land holding is critical for reducing moral hazards in crop
insurance. This work is currently being done in the states at a varied pace. Development of a
strong geo-referenced and regularly updated cadastral map base and its linkage with different
land records should be accelerated and completed in a time-bound manner. Bhumi project
of Karnataka government has shown considerable progress in this aspect and could provide
lessons for other states.
5. The Task Force is of the view that although CCEs are central to the insurance scheme, they are
not serving much purpose in their present form because of the financial, scientific, institutional
and operational challenges associated with them. Moreover, they do not necessarily provide good ix
estimates of yield loss over insurance units in a timely manner. It was noted that a combination
of these options - remote sensing, digital photography, statistical methods, and integrated crop
modelling- can provide an objective and unbiased assessment of crop yield losses well in-time
at a fraction of the current CCE costs. There is an urgent need to identify the most suitable
technology option and associated operational guidelines for every state. Capacity to undertake
such work in India is available with institutes/centres of ISRO, ICAR, and IMD, MNCFC, IT/ICT
agencies, state agricultural universities, state remote sensing centres, CGIAR research centres,
and private companies.
The Task Force, therefore, recommends that CCEs in their present form
must be replaced in a phased manner with technological solutions for crop loss assessment. The
following approach is proposed for developing protocols for loss assessment:
a. All state governments with a large stake in crop insurance should immediately commission
a 12-month project for a comparative evaluation and deciding on the suitability of
technological options for agro-ecological diversity in the state. The project should propose
the most suitable approach to provide robust estimates of crop yields at individual village/
village panchayat level along with cost-benefit analysis of the operations, and assessment
of technical capacity to implement this in an operational manner. For this work, the state
governments and insurance industry should allocate 0.20 percent premium.
b. The project should also propose a scientifically designed sampling strategy for a few very
high quality CCEs at block/tehsil/district/agro-ecological zones level in the state which can be
independently used to supplement/calibrate/validate/verify the technology proposed for loss
assessment.
c. Conducting these few and high quality CCEs should be the responsibility of the state
government and should be guided and monitored by independent experts from state
agricultural universities (SAUs) and their associated Krishi Vigyan Kendras (KVKs)/reputed
agricultural NGOs. The entire CCE must be digitally recorded so that it can be witnessed by
anyone, and be publicly available.
d. The above approach should be tested in at least 10 percent districts in Rabi 2017-18 and
Kharif 2018. Subsequently, the whole experience should be reviewed, calibrated, and applied
in the entire state from Rabi 2018-19.
e. For the time being, all CCEs should be witnessed, monitored and reported using mobile
Apps involving the staff of SAUs/KVKs, farmers, agriculture departments and insurance
companies.
6. Although there are several satellites today that can support crop insurance sector, it is
recommended that a dedicated constellation of 3-4 satellites of high to moderate resolution
(10-30 m) with 10-days frequency and with multispectral optical sensors, two microwave
satellites, and one hyper-spectral satellite may be deployed to increase the precision of crop yield
estimates/loss assessment at the village scale. xEnhancing technology use in agriculture insurance
7. Crop losses due to localised climatic events such as hailstorms, landslides, small floods and
post-harvest losses, where CCE data do not play a role, need to be supported by a mobile based
App. A separate mechanism for such data collection, visualisation and customisation needs to
be developed. The experience of the Karnataka Government for mango and grape could provide
lessons for such an App.
8. The Ministry of Agriculture and Farmers’ Welfare should expand their mobile App - CCE Agri - to
process CCEs’ data and weather data to calculate the loss and claim estimation in real-time. On
completion of the risk phase, the trigger and claim calculation should be done on the portal itself;
an SMS notification should be sent to the insured farmer and the claim due credited to his bank
account directly.
9. Historical yields at the desired insurable yields are needed for calculating the risk profile and
premiums. This data is generally not available at the desired scale. Depending upon the need
and urgency, the state governments in collaboration with AICI should commission projects to
develop such estimates of threshold yields of major crops at the desired insurable unit scale for
the past 10 years. Both agencies should make data of CCEs and block/tehsil yields available
for this purpose. The approach used should be the same as finalised for CCEs (see earlier
recommendation #5) in order to have consistency in the process for generating threshold yields
and premium rates.
10. Wherever WBCIS is to be implemented, agro-ecological region-specific weather triggers should
be redeveloped using integrated approach of statistics, historical weather data, crop models and
remote sensing data that can maximise the farmer’s satisfaction, and optimise the loss ratio while
keeping premiums within limit.
11. The state governments in collaboration with AICI and research institutes having understanding
of crop-weather relations should scientifically delineate clusters of districts/blocks with equitable
business opportunities for the insurance industry based on climatic risk profiles of the regions
together with the number of potential farmers to be insured, crops to be insured and infrastructure
available in the region. Basic premium rates for various clusters should also be identified to
eliminate the issues of over and under-pricing. An application/module for automated premium
calculation framework (yield index schemes) should be developed and tested for a few districts
and crops on a pilot mode.
12. An independent tool that uses seasonal and short-term weather forecasts, historical databases,
satellite images, and current weather data should be developed to provide a double trigger
product for mid-season claim calculation and ‘on-account’ payment to the insured as well as
a yield index for final loss assessment and claim settlement. The Ministry of Agriculture and
Farmers’ Welfare should explore expanding the scope of its FASAL program for this purpose. xi
13. The importance of livestock and aquaculture in Indian economy is growing and hence we
need to have effective insurance policies for them. There are several technologies that have
become available in recent times that can be used to increase livestock insurance. The use of
RFID technology, for example, can replace retagging of animals at policy renewal. Portability of
tag number across insurers can be operationalized for continuation of insurance. Index based
insurance schemes and ICT technologies can be piloted in livestock as well as fishery sectors.
There are, however, several institutional and policy issues related to livestock and fisheries
insurance sector which need to be addressed simultaneously. The Task Force recommends that
two independent groups be established on (a) livestock and (b) fisheries and aquaculture, to
develop comprehensive insurance plans for the respective sectors.
14. The central government should consider urgently establishing a dedicated mechanism either
within the existing institutions or by creating a new autonomous agency to coordinate among
various stakeholders including farmer groups, industry, different government ministries and
departments, banks and technology providers related to insurance in agriculture and allied
sectors. The same agency should also be mandated to support, monitor and improve insurance
services at the national scale. This could also include efficient data collection, storage, and
transfer between the stakeholders of different agencies. Similarly, the state governments should
consider establishing formal or informal units for crop insurance purpose where experts from
agriculture, remote sensing, ICT and insurance industry can come together to deliberate on
issues related to crop insurance in the state and advise the government and other stakeholders
on all related issues.
15. Developing innovative insurance products as well as greater use of technology in implementing
and monitoring crop insurance would need budget. It is recommended that a sum of 0.25 percent
of the premium collected every year should be made available for such purpose and should be
contributed by the central government, state government and insurance industry. xiiEnhancing technology use in agriculture insurance 1
1.1 Despite impressive development of agricultural infrastructure and irrigation
potential, a large part of Indian agriculture still remains exposed to climatic risks.
Crop insurance provides a safety-net for farmers to mitigate losses arising from
climatic shocks and also encourages them to continue to invest in inputs and
technology to increase yields and household income.
1.2 Although the need for crop insurance in India was debated since India became
independent, no serious efforts were made to implement it. Between 1947 and
1985, there were isolated schemes of crop insurance. These pilot schemes
were generally crop or location specific. In 1979, a scheme based on area
approach as suggested by V.M. Dandekar, linking crop insurance with credit,
was implemented by the General Insurance Corporation of India (GIC). Under this
scheme, the farmer was to be compensated in case of a shortfall in yield in the
area. The central government decided to introduce a country-wide crop insurance
scheme commencing from Kharif season of 1985 called Comprehensive Crop
Insurance Scheme (CCIS). The CCIS was also based on the approach described
by Dandekar (1979). This approach was ‘Area’ based and the farmer was liable
for compensation if there was a short-fall in the actual average yield per hectare
in the area as compared to the threshold yield as obtained on the basis of normal
yield. A few modifications and improvements were made to this Scheme and
subsequently the National Agricultural Insurance Scheme (NAIS) was launched
from Rabi 1999. This was further improved and the
Modified NAIS (MNAIS) was launched on a pilot basis
from Rabi 2010-11. It remained a pilot scheme till Kharif
2014. Subsequently it became a full-fledged scheme
under the National Crop Insurance Programme (NCIP).
Full details of these schemes, their operational details
and challenges can be found in the 2014 PK Mishra
Committee Report of the Government of India (www.
http://agricoop.nic.in/Admin_Agricoop/Uploaded_File/
Rpt_pkm2.pdf).
1. Introduction 2Enhancing technology use in agriculture insurance
1.3 A revamped, comprehensive and transformative insurance scheme called Pradhan Mantri Fasal
Bima Yojana (PMFBY) has been launched by the Government of India from Kharif 2016. The
PMFBY aims at supporting sustainable production in agriculture sector through (a) financial
support to farmers suffering crop loss/damage arising out of unforeseen events, (b) stabilization
of farmers’ income to ensure continuity in farming, (c) encouragement to farmers to adopt
innovative and modern agricultural practices, and (d) ensuring flow of credit to the agriculture
sector, which will contribute to food security, crop diversification, growth enhancement and
competitiveness of agriculture sector besides protecting farmers from production risks. It has
been conceptualised to address the operational and implementation problems of previous
schemes and incorporate various recommendations of Mishra Committee. The new scheme
will cover both yield losses and farm harvest losses, and also provide farm level assessment
for calamities. It is designed to operate across an insurable unit (village/Gram Panchayat) and
aims to double the coverage of farmers across the country from the current 23 percent of total
farming households to 50 percent in the next few years.
1.4 Use of technology has been proposed as a major input in the operations considering
the large diversity in climate, crops, cropping practices, agriculture infrastructure across
the country, and the limited capacity across government departments and implementing
insurance companies to effectively manage and monitor the scheme. However, guidelines
on what technologies to use for various insurance processes are not clearly specified in the
PMFBY and as a result not well-understood by relevant stakeholders. Several states had
requested for clarifications and guidance from the NITI Aayog to improve this understanding
and facilitate the development and implementation of relevant tools and instruments under
the PMFBY program. A Task Force was, therefore, constituted by the NITI Aayog under the
Chairmanship of Prof. Pramod K. Aggarwal of the CGIAR Research Program on Climate
Change, Agriculture and Food Security, Borlaug Institute for South Asia, CIMMYT, and under
the overall guidance of Prof. Ramesh Chand, Member, NITI Aayog to address the issues
related to the use of technology for agriculture insurance. The composition of the Task Force
is attached as Appendix A. To address the issue of technology support in crop insurance,
the Task Force constituted 5 sub-groups: 1. Remote Sensing & Drones; 2. Decision Support
Systems, Crop Modelling & Integrated Approaches; 3. IT/ICT in Insurance; 4. Crop Cutting
Experiments; and 5. Technologies for Livestock and Aquaculture Insurance. Each sub-group
had several discussions together with experts in the fields and submitted draft reports. More
than 100 experts related to professional research agencies, insurance industry, banks, and the
government contributed to these discussions. Technological options available in the country
and abroad were considered by all groups.
1.5 The Task Force concluded that several opportunities exist for applying technologies to increase
the efficacy and efficiency of the crop insurance program particularly in the process of 3
farmers’ enrolment, objective and convenient way of establishing insurable interest, developing
scientific weather triggers for WBCIS product development, data sharing among farmers and
insurers, banks and insurers and insurers and banks/farmers, and objective as well as real-
time assessment of crop yields and loss assessment due to various perils. These technologies
besides bringing objectivity to the insurance process would also increase its efficiency and cost
effectiveness. In the following sections of the document, solutions have been identified for key
challenges of the insurance sector and appropriate recommendations have been made keeping
in mind a clear focus on operational implementation. Some recommendations simplify or facilitate
the operational processes that can be implemented directly while other recommendations
propose mechanisms for establishing a stronger evidence base for technology use through rapid
but rigorous analyses. 4Enhancing technology use in agriculture insurance
2. Enrolment in
Crop Insurance
2.1 Key challenges
2.1.1 Almost 30 million farmers (25 percent of households) are covered today by the
Indian crop insurance program. The PMFBY aims to expand the coverage of
farmers across the country to 50 percent of farming households in the span of next
2 to 3 years. However, even today, the insurance cover is largely availed by the
loanee-farmers for whom this is compulsory. There is a need to increase awareness
among farmers, especially in climatic risk prone regions, and also among non-
loanee farmers, about crop insurance, risks covered, government schemes and
subsidies available and their benefits. To ensure retention of farmers in crop
insurance program on a sustained basis, satisfaction of the farmers with scheme
implementation is critical. Farmers’ satisfaction is linked to the information available
to them during enrolment about the availability of scientifically designed products,
quick enrolment process and more importantly about the claim settlement process
that is simple, quick and linked to the actual damage. A large number of co-
operative banks, which are often in the fore-front of the enrolment process, are not
yet computerised. The hard copy data flow to the banking and insurance industry
is sluggish and therefore limits enrolment as well as claim settlement.
2.2 Technology solutions
2.2.1 There are several technological opportunities today,
especially in ICT/IT sector, that can be used to
accelerate the process of enrolment in the crop
insurance program. Besides conventional extension
mechanisms such as radio, television and newspapers,
IT and ICT technologies such as mobile applications,
Kisan Call Centres, voice blasts, IVRS and SMS 5
can be used to raise the awareness of farmers about the insurance products. Further, IT
infrastructure of Gram Panchayat, Common Service Centres and internet café, etc., can be
used as insurance information centres. Participatory videos/films, where farmers record their
own experiences, and showing them to a large number of other farmer groups is becoming
a very powerful and effective tool in agricultural extension. This simple participatory process,
if linked with enrolment process, could significantly raise participation in the insurance
programs. In the near future, an insurance service on the lines of 139 by IRCTC may be
started for crop insurance.
2.2.2 Several portals have already been developed for the implementation of crop insurance;
however, none of them include holistic approaches covering all processes from customer
enrolment to claim settlement. The portals also lack connectivity with CBS, and the payment
gateway is still to be integrated. ICT can help to reach the farmers at the grass roots and
assist them in overcoming the challenges currently posed in the manual registration process.
Mobile/tablet based applications can ensure ease of registration, payment of premium and
issuance of e-receipts. A mobile App for dissemination of crop insurance has already been
developed. The mobile App facilities should be extended to enrol non-loanee farmers with
payment gateways. Further, the enrolment process with banks and national portal should be
available 24×7 till the cut-off date.
2.2.3 In respect of loanee-farmers, the insurance portal’s bulk uploading facilities should be
improved. The National Crop Insurance Portal available at www.agri-insurance.gov.in has
been designed as an integrated platform for all stakeholders – states, insurance companies,
banks and farmers. Different states have different hierarchies and they need to be integrated
with the portal so that all missing links like the Revenue Circle in Maharashtra, Firka in Tamil
Nadu, and Nyaya Panchayat in Uttar Pradesh, etc., can be covered. The codes and fields
of CBS and the National Portal also need to be matched so as to facilitate seamless flow
of data. Banks with CBS capability already have the details of loanee-farmers opting for
agricultural credit and that information can be directly transferred to the National Portal for
their enrolment. Online web-form or excel sheets uploaded with correct codes could be used
till the time CBS is connected.
2.2.4 The absence of digitized land records and cadastral maps creates big hurdles in the
enrolment process. A strong geo-referenced cadastral map base and its linkage with details
of the land records will help in controlling the menace of over reporting of the insured area
and easing the enrolment process. The responsibility of providing land records should
be given to the concerned government department instead of the farmers. Lessons from
the Bhumi project of the Karnataka could be very educative. Database protocols of using 6Enhancing technology use in agriculture insurance
standard coding patterns for the land records should be followed by every state for seamless
integration into the National portal.
2.2.5 As per the present guidelines of the PMFBY, a sowing certificate is required if declared crop
is changed after the enrolment, sometimes necessitated by various exigencies. This causes
confusion, increases administrative load and discourages farmers from enrolment in the
insurance program.
2.3 Recommendations
2.3.1 To increase insurance literacy, the state governments should urgently commission the
development of a comprehensive mobile-based application (App) that has 24x7 links with the
payment gateways/e-wallets to facilitate ease of registration, online payment of premium and
issuance of instant e-receipts. This should have links with the National Crop Insurance Portal
available at www.agri-insurance.gov.in. This data should be simultaneously accessible to
insurance companies, bankers and state government departments.
2.3.2 The states should commission major campaigns during the enrolment period in every crop
season by using participatory videos, and other ICT tools such as voice blasts, IVRS and
SMS, to increase awareness and insurance literacy. Together with related banks and insurance
industry they should simultaneously arrange for on-the-spot enrolment in crop insurance with
the use of customised mobile App.
2.3.3. To reduce farmers’ discomfort with the enrolment process, PMFBY guidelines should be
relaxed to accept geo-tagged and time-stamped digital photographs of land to establish the
insurable interest instead of manual certificates. Such photographs submitted by the farmers
should be accepted as sowing certificates if the declared crop is changed after the payment of
premium.
2.3.4. Digitising geo-referenced records of land holding is critical for reducing moral hazards in crop
insurance. This work is currently being done in the states at a varied pace. Development of a
strong geo-referenced and regularly updated cadastral map base and its linkage with different
land records should be accelerated and completed in a time-bound manner. Bhumi project
of Karnataka government has shown considerable progress in this aspect and could provide
lessons for other states. 7
3. Crop Loss
Assessment
3.1 Key challenges
3.1.1 Accurate loss or damage assessment is the most important component of an
insurance scheme for all stakeholders. This assessment is currently done using
either a weather index (for WBCIS) or a stratified CCE when yield is used as an
index. Weather indices have not worked well in the past due to limited density of
weather stations, their maintenance, and large spatial and temporal variability in
weather.
3.1.2 Currently in the country around 9 lakh CCEs are being conducted for General
Crop Estimation Survey. With the requirement of carrying out at least 4 CCEs per
insurable unit of village/village panchayat for each crop, this number may become
very large considering there are around 2.3 lakh village panchayats in the country.
Assuming that 40 lakh CCEs would need to be done and each CCE costs a
minimum of 1000 rupees, it would cost more than Rs. 400 crore every year to
conduct CCEs. Since CCEs need to be generally conducted within a time frame
of 15-20 days in a season, there will be a massive need of trained manpower to
manage, monitor and report them in time. Carrying out so many CCEs rigorously
is extremely difficult and time consuming. Over the
years CCEs have lost their credibility owing to such
complexities, human bias, measuring errors, high labour,
time and cost intensive design, and their limitation in
covering spatial and temporal basis risks, objective
monitoring, reporting and verification process. It is
also noted that the states often have two sets of yield
estimates - one for production statistics and the other
for payment of crop insurance claims. This brings further
confusion and subjectivity in the estimates of crop yield
and losses. 8Enhancing technology use in agriculture insurance
3.1.3 Localised calamities such as hailstorms, flash floods, and post-harvest rains have
increasingly become a source of concern. In the last few years, we have witnessed
widespread hailstorms in some villages of Maharashtra, localised floods in some parts of
Rajasthan and unseasonal rainfalls after harvest of crops in many states. Loss assessment
due to these remains a challenge because of verification methods.
3.2 Technology solutions
3.2.1 Fortunately, there are a number of technological solutions available today that can support
objective assessment of crop losses at the desired scale. These include satellite based
remote sensing (RS), Unmanned Aerial Vehicles (UAVs), digital geo-referenced photographs,
integrated crop yield assessment models, and statistical sampling techniques. Remote
sensing technique is rapid and the technology is used routinely for acreage estimation and
in combination with regression/crop models to estimate yields in many parts of the world,
especially in non-cloudy (such as Rabi) seasons. UAVs appear to be promising, especially
under cloud (Kharif) conditions, but there are many key challenges with linking their signals
with crop performance, possible interference with national security guidelines, and their
costs-benefits, which are not yet fully understood. There are as yet no clear success stories
with UAVs for crop loss assessment in India although they can play a critical role for the
assessment of localised perils such as hailstorms and flood related damages. More research
is needed to fully understand their scope and limitations before they can be employed for
crop loss assessment. Similar are the limitations of the picture based technologies where loss
libraries are yet to be developed based on systematic and rigorous scientific experiments.
An integrated approach linking RS signals and crowd-sourced agronomic inputs with crop
models can provide a very suitable tool for loss assessment. Initial experiments done by
the Maharashtra Government, KISAN project of the Ministry of Agriculture and many other
independent agencies in this respect appear to be promising. Small area statistical sampling
design approach is another promising approach to reduce the number of CCEs if suitable
and easily measurable yield proxies could be identified.
3.2.2 However, all these tools have been tested in research mode or in small pilots in a few states.
There is an urgent need to examine their suitability for operational purpose on a large-scale,
which should include understanding the scope, limitations in loss assessment, costs-
benefits, technical capacity in different regions to implement, monitor, report and verify in a
given time frame and developing protocols to be followed. This has to be complemented by
a scientifically designed CCE sampling strategy where a small number of high quality CCEs
are conducted, monitored and reported by experts from SAUs, KVKs or other competent
agencies. These institutions have large scientific and technical capacity and routinely do 9
such sampling for their own purposes. Such CCEs can be used to calibrate/validate/verify/
supplement various technological solutions.
3.3 Recommendations
3.3.1 The Task Force is of the view that although CCEs are central to the insurance scheme, they are
not serving much purpose in their present form because of the financial, scientific, institutional
and operational challenges associated with them. Moreover, they do not necessarily provide
good estimates of yield loss over insurance units in a timely manner. It was noted that remote
sensing, digital photography, statistical methods, integrated crop modelling, and a combination
of these options can provide an objective and unbiased assessment of crop yield losses well
in-time and at a fraction of the current CCE costs. There is an urgent need to identify the most
suitable technology option for every state and associated operational guidelines. Capacity
to undertake such work in India is available with institutes/centres of ISRO, ICAR, and IMD,
MNCFC, IT/ICT agencies, state agricultural universities, state remote sensing centres, CGIAR
research centres, and private companies.
The Task Force, therefore, recommends that CCEs
in their present form must be replaced in a phased manner with technological solutions for
crop loss assessment. The following approach is proposed for developing protocols for loss
assessment:
a. All state governments with a large stake in crop insurance should immediately commission
a 12-month project for a comparative evaluation and deciding on the suitability of
technological options for agro-ecological diversity in the state. The project should propose
the most suitable approach to provide robust estimates of crop yields at individual village/
village panchayat level along with cost-benefit analysis of the operations, and assessment
of technical capacity to implement this in an operational manner. For this work, the state
governments and insurance industry should allocate 0.20 percent premium.
b. The project should also propose a scientifically designed sampling strategy for a few very
high quality CCEs at block/tehsil/district/agro-ecological zones level in the state which can
be independently used to supplement/calibrate/validate/verify the technology proposed for
loss assessment.
c. Conducting these few and high quality CCEs should be the responsibility of the state
government and should be guided and monitored by independent experts from state
agricultural universities and their associated Krishi Vigyan Kendras/reputed agricultural
NGOs. The entire CCE must be digitally recorded so that it can be witnessed by anyone,
and be publicly available. 10Enhancing technology use in agriculture insurance
d. The above approach should be tested in at least 10 percent districts in Rabi 2017-18 and
Kharif 2018. Subsequently, the whole experience should be reviewed, calibrated, and
applied in the entire state from Rabi 2018-19.
e. For the time being, all CCEs should be witnessed, monitored and reported using mobile
Apps involving the staff of SAUs/KVKs, farmers, agriculture departments and insurance
companies.
3.3.2 Although there are several satellites today that can support crop insurance sector, it is
recommended that a dedicated constellation of 3-4 satellites of high to moderate resolution
(10-30 m) with 10-days frequency and with multispectral optical sensors and two microwave
satellites and one hyper-spectral satellite may be deployed to increase the precision of crop
yield estimates/loss assessment at the village scale.
3.3.3 Crop losses due to localised climatic events such as hailstorms, landslides, small floods and
post-harvest losses, where CCE data do not play a role, need to be supported by a mobile
based App. A separate mechanism for such data collection, visualisation and customisation
needs to be developed. The experience of the Karnataka Government for mango and grape
could provide lessons for such an App 11
4. Claim
Settlement
4.1 Key challenges
4.1.1 Accurate loss assessment and its timely reporting are prerequisites for faster
and accurate claim settlement. Satisfaction of farmers with insurance is mainly
associated with quick claim settlements. Owing to the complex nature of loss
assessment associated with CCEs, large delays running into 6-12 months have
been observed in the process of claim settlement and transfer of money to the
farmers. Normally, the cut-off date for data (yield/weather) submission of CCEs
is fixed at one/two months from harvesting time but this is not always followed.
Sometimes, the submission of yield data by the various agencies involved in the
process is done in a piece-meal manner. There are quality issues as well with the
submitted data. Submitted data may not be acceptable to the industry since it is
based on less than the requisite number of CCEs. Occasionally the submitted CCE
data is also revised.
4.1.2 Although the process of submission of weather data in WBCIS is much easier, but
certification, data quality checks and replacement of missing datasets take time
and cause delayed submission.
4.1.3 Claims are also partially delayed by the lack of automation in claim calculation and
direct transfer of the payments to the insured farmer.
4.2 Technology solutions
4.2.1 The efficiency of the claim settlement process can be
considerably enhanced by automation. A mobile App
(CCE-Agri) has already been developed by the Ministry
of Agriculture and Farmers’ Welfare to digitize and
witness the CCEs. The CCEs data through this App is
directly uploaded to the web portal. Protocols further 12Enhancing technology use in agriculture insurance
need to be developed to process CCEs data and calculate loss and claim estimation. For
weather index insurance scheme, the weather data flow should be assured to the portal on a
real-time basis. On completion of the risk phase, the trigger and claim calculation should be
done on the portal itself and accordingly a notification should be sent to the farmer about the
claim. Once the claim is assessed based on the crop loss or weather index, it should instantly
be directly credited to the bank account of the insured farmer. The entire process of claim
settlement and transfer of money has to be shared with the insured farmer through the SMS
alert at each stage.
4.3 Recommendations
4.3.1 The Ministry of Agriculture and Farmers’ Welfare should expand their mobile App - CCE-Agri -
to process CCEs data and weather data to calculate the loss and claim estimation in real-time.
On completion of the risk phase, the trigger and claim calculation should be done on the portal
itself and an SMS notification be sent to the insured farmer and the claim due credited directly
to his bank account. 13
5. Product
Design and
Development
5.1 Key challenges
5.1.1 Designing an appropriate insurance product and suitably pricing it require a good
analysis of available crop yield data, threshold yields (based on the last 7 years)
and various other factors at the village/panchayat level in PMFBY. Such data is
normally available only at district level and at block level in some states. For some
minor crops, such yield series do not exist. This causes problems in designing
a suitable product. Even for WBCIS, triggers are often used without a scientific
basis resulting in payments when risks and consequent yield losses are minimal or
vice-versa.
5.1.2 PMFBY is implemented in the states by insurance companies who compete for
business by quoting their premium rates. These companies quote premium rates
based on their business strategy. It was informed to the Task Force that the rates
quoted in the last season for the same crop in the same state/district sometimes
varied by 8 times. In the absence of any mechanism with the governments to
calculate the burning cost or loss cost for addressing the issues of over and
under- pricing by the insurance providers and its
relation with the climatic risks in the region, the decision
making by the state government becomes difficult.
5.1.3 The states are currently using a cluster approach where
several districts are pooled and given to one insurance
company for business over a period of time. This is
perhaps done based on administrative convenience for
providing sufficient long-term business to companies.
However, since this does not have a link to climatic
risks and volume of business, such clusters become 14Enhancing technology use in agriculture insurance
unequal leading to unfair competition. Small companies may often find it difficult to participate
in large clusters with large insurable risks.
5.2 Technology solutions
5.2.1 Several statistical, remote sensing and modelling approaches have the potential to generate
yield series at the insurable units by using proxies of historical weather, crop management
details, NDVIs, and district/block level crop yields. However, they have not yet been applied
for this purpose in our country. If data on block level yields of high quality CCEs done in past is
made available, it should be possible for practitioners familiar with the above tools to construct
such historical yield series with some confidence.
5.2.2 Integrated approach of using statistics, dynamic weather and satellite data and crop growth
models has been shown to result in scientifically designed agro-ecological region- specific
weather triggers that can maximise farmers’ satisfaction and optimise loss ratio while keeping
premiums within limit. Such methodologies need to be encouraged. For some crops, if the
yield and weather relationship is not clearly established, pilot projects can be undertaken on the
lines of the All India Coordinated Research Projects for identification of WBCIS triggers.
5.2.3 Various tools and products are available that characterise climatic risks of India even by
cropping season. Gridded weather data has also been made available by the IMD and
various other global agencies that can support such characterisation. Such data on climatic
risks together with the number of potential farmers to be insured, crops to be insured and
infrastructure available in the region should be used to scientifically delineate clusters with
equitable business opportunities for the insurance industry.
5.3 Recommendations
5.3.1 Historical yields at the desired insurable yields are needed for calculating risk profile and
premiums. This data is generally not available at the desired scale. Depending upon the need
and urgency, the state governments in collaboration with AICI should commission projects to
develop such estimates of threshold yields of major crops at the desired insurable unit scale
for the past 10 years. Both agencies should make the data of CCEs and block/tehsil yields
available for this purpose. The approach used should be the same as finalised for CCEs
(see earlier recommendation #5) in order to have consistency in the process for generating
threshold yields and premium rates. 15
5.3.2 Wherever WBCIS is to be implemented, agro-ecological region-specific weather triggers should
be redeveloped using integrated approach of statistics, historical weather data, crop models
and remote sensing data that can maximise farmers’ satisfaction and optimise the loss ratio
while keeping premiums within limit.
5.3.3 The state governments in collaboration with AICI and research institutes having understanding
of crop-weather relations should scientifically delineate clusters of districts/blocks with
equitable business opportunities for the insurance industry based on climatic risk profiles of
the regions together with the number of potential farmers to be insured, crops to be insured
and infrastructure available in the region. Basic premium rates for various clusters should
also be identified to eliminate the issues of over and under-pricing. An application/module for
automated premium calculation framework (yield index schemes) should be developed and
tested for a few districts and crops on a pilot mode. 16Enhancing technology use in agriculture insurance
6. In-season Crop
Yield Loss
Assessment
(on Account Payment)
6.1 Key challenges
6.1.1 For the government as well as insurance industry it is important to keep track of
disaggregated crop conditions and losses on a real-time basis. It serves several
purposes such as satisfying demands from reinsurance industry about the probable
losses, targeting of CCEs for better loss assessment, making informed decisions
and planning for claim volume, and better preparedness for settling claims after
crop harvest. Such information is also very useful for making mid-season on-
account payments to the insured when they need compensation the most rather
than waiting for the claim settlement after the harvest of the crop.
6.2 Technology solutions
6.2.1 India has a system of crop yield estimation which is
based on traditional crop cuts, surveys and reports
from the District Agricultural Offices. Additionally, many
agencies undertake field verifications and consultations
to collect additional information on crop performance.
Many agencies like MNCFC, IMD, SAC, ICAR, IARI,
NCAER, etc., provide aggregated crop outlooks to
the government. FASAL programme of the Ministry of
Agriculture and Farmers’ Welfare is worth mentioning in
this context. It uses remote sensing inputs, crop models
and government statistics to develop crop outlooks. 17
Globally there are many such tools as FEWS NET in Africa and Caribbean, MARS in Europe,
Cropland Data Layer in USA, AMIS Crop Monitor of GEOGLAM and CropWatch of China.
With some modifications, such tools can be tailored to meet the requirements of estimating
probable crop yield losses at a disaggregated scale for the crop insurance sector.
6.2.2 Satellite weather data is now easily available. Though there are some issues about its accuracy
and the scale for final claim payment, it is of sufficient accuracy, once corrected for bias with
in situ data, to make a preliminary estimate of crop losses during the crop season. This could
be used mid-season to make initial 25-50 percent of the claim payment to the insured pending
his full settlement based on a yield index after the harvest of the crop. Such a double trigger
product would help the insured farmer in time to address his agrarian distress.
6.3 Recommendations
6.3.1 An independent tool that uses seasonal and short-term weather forecasts, historical
databases, satellite images, and current weather data should be developed to provide a double
trigger product for mid-season claim calculation and ‘on-account’ payment to the insured as
well as a yield index for final loss assessment and claim settlement. The Ministry of Agriculture
and Farmers’ Welfare should explore expanding the scope of its FASAL program for this
purpose. 18Enhancing technology use in agriculture insurance
7. Livestock and
Aquaculture
Insurance
7.1 Key challenges
7.1.1 India has 56.7 percent of world’s buffaloes and 12.5 percent of world’s cows
and bullocks. Besides, fisheries and aquaculture is one of the fast growing sub-
sectors that contributes to nearly 4.8 percent of value of output from agriculture
and allied sectors in India. India is, however, far behind in insuring its huge
livestock population as only 6 percent of the cattle population and less than 0.6
percent of the cattle owners in India are insured. Since farmers depend a lot on
livestock when crops suffer losses due to climatic stresses, it is critical that they
are provided the benefits of livestock insurance. Cattle insurance is mandatory for
availing bank credit for dairying activities. More than 90 percent of cattle insurance
premium underwritten is through this model. The different methods used for
animal identification are ear tagging, ear notching, freeze band numbering, muzzle
printing, etc. ‘No tag no claim’ is a general principle followed by all the insurance
companies. Insurance as a risk transfer mechanism is by far under-utilized in
the fishery sector also. Except for the presence of a few public sector insurance
companies and cooperative bodies at the local levels
whose scale of operation and coverage is abysmally
low, the sector has received little attention either at the
central or state levels. The private sector operation in
this arena is also limited to a few cases scattered over
time and space.
7.2 Technology solutions
7.2.1 The painful process of tagging can be replaced with the
use of new technologies such as RFID, Genome Tagging 19
or DNA testing, ZigBee mobile technology, etc. Mobile phone based technologies can be
effectively used in reducing policy inception and claim settlement time.
7.2.2 Technology can play a vital role in improving efficiency, bringing transparency and reducing
moral hazards in fishery insurance. Advanced ICT tools and GIS platforms for developing
inventory data base (on variables such as locations with GPS coordinates, date of stocking,
stock sizes, and progress of the crop; hydro-acoustics and digital video survey can be used
for assessing the crop loss, etc.) of insured farmers could be put to use, which would not
only simplify monitoring procedures but also make them transparent and the farming practice
more technology oriented. Innovative products such as weather-index and yield-index based
insurance schemes in crop sector can be extended to fisheries sector as well, to harness the
potential of technology for increasing efficiency and simplifying procedures.
7.2.3 The Government of India is presently working on mechanisms to track vessels operating in
India’s Exclusive Economic Zone (EEZ). Advanced Vessel Monitoring Systems (VMS) could be
made use of to track the fishing vessels and assess incidents such as mid-sea capsizing and
collisions. Awareness among fishermen and aqua-farmers needs to be created about various
insurance programs and the provisions involved.
7.3 Recommendations
7.3.1 The importance of livestock and aquaculture in Indian economy is growing and hence we
need to have effective insurance policies for them. There are several technologies that have
become available in recent times that can be used to increase livestock insurance. Use of
RFID technology, for example, can replace retagging of animals at policy renewal. Portability of
tag number across insurers can be operationalized for continuation of insurance. Index based
insurance schemes and ICT technologies can be piloted in livestock as well as fishery sector.
There are, however, several institutional and policy issues related to livestock and fisheries
insurance sector which need to be addressed simultaneously. The Task Force recommends
that two independent groups be established on (a) livestock and (b) fisheries and aquaculture,
to develop comprehensive insurance plans for the respective sectors. 20Enhancing technology use in agriculture insurance
8. Institutional
Mechanisms
for Technology
Use in Crop
Insurance
8.1 Key challenges
8.1.1 Agricultural insurance sector is complicated because of a very large and dispersed
population of smallholder farmers who practice agriculture in different agro-
ecologies with varying climates, farming systems, and agronomic management.
These diversities linked with weather adversities result in crop losses of large
magnitude every year at least in some states. Climate change is likely to further
increase such risks. Technology use for enrolment, loss assessment and claim
settlement is therefore a must. However, there is no formal institutional mechanism
in Indian agricultural insurance sector to develop,
manage and operationalise these technological
opportunities. It is felt that a centralised agency is
needed to coordinate among various stakeholders
including farmer groups, insurance industry, government,
banks, and technology providers. The same agency
should also be mandated to support, monitor and
improve insurance services at the national scale.
8.1.2 There is also a need for some sort of coordination
between stakeholders even at the state level, especially 21
for making technology recommendations. Every state has the related expertise in their
agricultural universities, regional/state remote sensing centres, IT agencies, and private sector.
India Meteorology Department has in every agro-ecological region a relatively ‘informal’ AFMU
(Agriculture Field Monitoring Unit) that synthesises all agricultural information related to climatic
events and provides value-added information to all stakeholders including farmers using ICT
mechanisms. The state governments should consider establishing similar formal or informal
units for crop insurance purpose where experts from agriculture, remote sensing, ICT and
insurance industry can come together to deliberate on issues related to crop insurance in the
state and advise the government and other stakeholders on all related issues.
8.2 Recommendations
8.2.1 The central government should consider urgently establishing a dedicated mechanism
either within the existing institutions or by creating a new autonomous agency to coordinate
among various stakeholders including farmer groups, industry, different government ministries
and departments, banks and technology providers related to insurance in agriculture and
allied sectors. The same agency should also be mandated to support, monitor and improve
insurance services at the national scale. This could also include efficient data collection,
storage, and transfer between the stakeholders of different agencies. Similarly, the state
governments should consider establishing formal or informal units for crop insurance purpose
where experts from agriculture, remote sensing, ICT and insurance industry can come together
to deliberate on issues related to crop insurance in the state and advise the government and
other stakeholders on all related issues.
8.2.2 Developing innovative insurance products as well as greater use of technology in implementing
and monitoring crop insurance would need budget. It is recommended that a sum of 0.25
percent of the premium every year should be made available for such purpose and should be
contributed by the central government, state government and insurance industry. 22Enhancing technology use in agriculture insurance
Annexure-I
Constitution of the Task Force
• Pramod K. Aggarwal (Chairman, Task Force), Regional Program Leader, CGIAR, Research
Programme on Climate Change, Agriculture & Food Security (CCAFS), Bolraug Institute for South
Asia, CIMMYT, New Delhi.
• Ashish Bhutani, Joint Secy. (Credit), Department of Agriculture Cooperation & Farmers Welfare,
Government of India, Krishi Bhawan, New Delhi.
• O. P. Chaudhury, Joint Secy. (ANLM), Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi.
• A.K. Joshi, Joint Secy. (Fy.), Department of Animal Husbandry, Dairying & Fisheries, Government
of India, Krishi Bhawan, New Delhi.
• CMD, NABARD or, his nominee (Gautam Sen, DGM, DFI&BT Division), NABARD H.Q., Plot No
C-24, “G” Block Bandra-Kurla Complex, P.B.No 8121, Bandra(E), Mumbai - 400051.
• U.C. Sud, Director, Indian Agricultural Statistics Research Institute, Indian Council of Agricultural
Research, Pusa, New Delhi-110012.
• Representative of Co-operative Bank (Sh. C.N. Tarpara, Chief Executive Officer), District Central
Co Op. Bank Ltd., Rajkot, Gujarat.
• Representative of the Chairman, National Dairy Development Board, Anand, Gujrat.
• S.S. Ray, Director, Mahalanobis National Crop Forecast Centre, Department of Agriculture
Cooperation & Farmers Welfare, Government of India, Pusa, New Delhi.
• Principal Secretary (Agriculture), Govt. of Andhra Pradesh.
• Principal Secretary (Agriculture), Govt. of Gujarat.
• Principal Secretary (Agriculture), Govt. of Karnataka.
• C.S. Murthy, Head Crop Monitoring & Assessment Division, National Remote Sensing Centre,
Hyderabad.
• Sanjiv Mittal, Joint Secretary (IT), Department of Electronics and Information Technology,
Government of India, New Delhi.
• M. K. Poddar, General Manager, Agriculture Insurance Company Of India Limited, 13th Floor,
Ambadeep Building, 14 Kasturba Gadhi Marg, New Delhi, Delhi 110001.
• J. P. Mishra (Member-Secretary of the task force), Adviser (Agriculture), National Institute for
Transforming India (NITI) Aayog, New Delhi 23
Annexure-II
Sub Groups
Sub-Group 1. Remote Sensing & Drones
1. Y.V.N. Krishna Murthy, Director, National Remote Sensing Centre (NRSC), Hyderabad,
Chairman
2. C.S. Murthy, National Remote Sensing Centre (NRSC), Hyderabad, Member
3. T. P. Singh, Director, Bhaskaracharya Institute for Space Applications and Geo-Informatics
(BISAG), Gandhinagar, Gujarat, Member
4. Satish Raju, Swiss Re, Vaswani Centropolis, 2nd to 6th Floor, No. 21 Langford Road,
Bengaluru, Karnataka 560027, Member
5. M Sudhakar, SkyMet, 109, 1st Floor, Kushal Bazar, 32-33, Nehru Place, New Delhi, Delhi
110019, Member
6. R. N. Sahoo, Indian Agricultural Research Institute (IARI), PUSA, New Delhi, Member Secretary.
Sub-Group 2. Decision Support Systems, Crop Modelling & Integrated Approaches
1. Alok Sikka, International Water Management Institute (IWMI), NASC, Pus, New Delhi, Chairman
2. Principal Secretary (Agriculture), Govt. of Gujarat or, his nominee, Member
3. S. S. Ray, Director, Mahalanobis National Crop Forecast Centre (MNCFC), Department of
Agriculture Cooperation & Farmers Welfare, Government of India, Pusa, New Delhi, Member
4. K.K. Singh, India Meteorological Department (IMD), Lodhi Road, New Delhi, Member
5. Kolli N. Rao, IRICBS/ Aon Benfield, Member
6. Neha Agarwal, ICICI Lombard, Member
7. Naresh Kumar Soora, Indian Agricultural Research Institute (IARI)-ICAR, PUSA, New Delhi,
Member Secretary.
Sub-Group 3. IT/ ICT in Insurance
1. S.K. Goel, Former Additional Chief Secretary - Agriculture, Government of Maharashtra,
Chairman
2. Jt. Secy., DeitY, or, his representative, Member
3. P. Krishna Reddy, International Institute of Information Technology, Hyderabad, Andhra Pradesh,
Member
4. Jt. Secy., IT, MoA&FW or, his representative, Member
5. Gautam Sen, DGM, DFI&BT Division), NABARD H.Q., Plot No C-24, “G” Block Bandra-Kurla
Complex, P.B.No 8121, Bandra(E), Mumbai - 400051, Member
6. Alok Shukla, TATA AIG Gen. Insurance, Member
7. Aniruddha Shanbaug, Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), Member
8. Paresh B Shirsath, CGIAR, Research Programme on Climate Change, Agriculture & Food
Security (CCAFS), Bolraug Institute for South Asia, CIMMYT, New Delhi, Member Secretary. 24Enhancing technology use in agriculture insurance
Sub-Group 4. Crop Cutting Experiments, CCEs
1. Vijay Kumar, Principal Secretary (Agriculture), Government of Andhra Pradesh, Chairman
2. U.C. Sud, Director, Director, Indian Agricultural Statistics Research Institute, Indian Council of
Agricultural Research, Pusa, New Delhi-110012, , Member
3. State Government Representatives (Maharashtra & Karnataka), Members
4. Director, ICAR – CIAE, Bhopal, Member
5. Representative of State Cooperative Bank, Gujarat, Member
6. A.K. Srivastava, Ex-NSSO, Member
7. Representative of DES, M/o Agri. & FW, Member
8. Ashok K. Yadav, Manager, Agriculture Insurance Company of India Limited, 13th Floor,
Ambadeep Building, 14 Kasturba Gadhi Marg, New Delhi, Delhi 110001, Member Secretary
Sub-Group 5. Livestock & Aquaculture
1. Dilip Kumar, Former Director/Vice Chancellor, Central Institute of Fisheries Education-ICAR,
Versova, Andheri West, Mumbai, Maharashtra 400061, Chairman.
2. Director, Central Marine Fisheries Research Institute-ICAR, Kochi, Kerala, Member
3. Director, National Dairy Research Institute (NDRI), Karnal, Haryana, Member
4. Jt. Secy. (Fy.), Department of Animal Husbandry, Dairying & Fisheries, Government of India,
Krishi Bhawan, New Delhi, Member
5. Jt. Secy., Livestock & Animal Health, Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi, Member
6. Representative of DHAN Foundation, Kennet Cross Road, Vaidyanathapuram East Madurai 625
016, Tamil Nadu, Member
7. Representative of New India Assurance Co. Ltd., Member
8. Fisheries Development Commissioner, Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi, Member
9. Animal Husbandry Commissioner, Department of Animal Husbandry, Dairying & Fisheries,
Government of India, Krishi Bhawan, New Delhi, Member
10. M. K. Poddar, General Manager, Agriculture Insurance Company of India Limited, 13th Floor,
Ambadeep Building, 14 Kasturba Gadhi Marg, New Delhi, Delhi 110001, Member Secretary 26Enhancing technology use in agriculture insurance
National Institute for Transforming India (Niti) Aayog
Government of India
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