Editing IPCC:AR6/WGII/Chapter-10 (section)

==== 10.5.5.2 Findings ====

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As against financing post-disaster relief and reconstruction, which has been the norm of disaster management for decades in Asia, the evolution of ex-ante risk financing in the form of risk insurance has seen a steady rise globally and in Asia. The rise in popularity for risk financing in general and insurance in specific stem from the observation that governments have recognised the burden of mainly financing the post-disaster relief and reconstruction only ( [[#Juswanto--2017|Juswanto and Nugroho, 2017]] ; [[#UNESCAP--2018c|UNESCAP, 2018c]] ; [[#ADB--2019|ADB, 2019]] ), and from the realisation of cost savings and efficiency that risk financing for risk mitigation brings overall risk reduction ( ''high agreement'' , ''medium evidence'' ). As a result, a gamut of risk-financing instruments have been introduced to finance DRR and CCA initiatives in Asia among which risk insurance has gained prominence for it provides a low-cost and easy option for individuals, provides an opportunity for the governments to effectively engage the private sector in implementation and has the ability to inculcate risk-aware decision making at various levels ( ''high agreement'' , ''medium evidence'' ) ( [[#Hazell--2017|Hazell and Hess, 2017]] ; [[#UNESCAP--2018c|UNESCAP, 2018c]] ).

Several Asian countries, including India, the Philippines and China, have a significant experience of offering agricultural insurance against typhoons, droughts and floods ( [[#Yang--2018|Yang, 2018]] ). For the most part, these insurance systems have followed a traditional indemnity-based insurance which faces several challenges in implementation including moral hazard and adverse selection, disagreements and delays in crop-damage assessments that relied upon crop-cutting experiments, often leading to a delay in processing indemnity payments, costly insurance premiums and poor insurance expansion ( ''high agreement'' , ''robust evidence'' ) ( [[#Patnaik--2017|Patnaik and Swain, 2017]] ; [[#Ghosh--2019|Ghosh et al., 2019]] ). Other factors contributing to poor penetration of insurance include limited awareness on the importance of insurance, and poor access.

To tackle the problem of costly insurance premiums, governments have subsidised the premiums ( [[#Ghosh--2019|Ghosh et al., 2019]] ). Premium subsidies have been reported to undermine the ability to convey the real cost of risks by the insured (price distortion), and have encouraged adverse selection and moral hazard ( [[#Nguyen--2019|Nguyen and Jolly, 2019]] ). On the contrary, subsidies have been suggested to address the issue of adverse selection associated with the insurance ( [[#Zhao--2017c|Zhao et al., 2017c]] ).

Despite the fact that the insurance programmes are able to obtain high participation rates due to subsidised premiums, their impact on farmers’ income seems to be insignificant especially under the conditions of low indemnities, low guarantee and wide coverage ( [[#Zhao--2016a|Zhao et al., 2016a]] ). The subsidy burden of insurance on national governments is found to be significant with an estimated equivalent of 6 billion USD spent by China alone on insurance ( [[#Hazell--2017|Hazell et al., 2017]] ). In addition, the insurance programmes in Asian countries are reporting higher producer claim ratios, and often governments have to spend more than the money being transferred to the insured through the insurance programmes ( [[#Hazell--2017|Hazell et al., 2017]] ).

To address the issues associated with traditional indemnity insurance, efforts have been made to develop weather-index insurance in Asia that bases the payouts on the rainfall or temperature index, rather than on the direct damage measurements. The parametric insurance products help avoid the delays in insurance payouts as they are based on modelled risks, rather than actual damage measurements, and control the adverse selection and moral hazard, although basis risks could be increased due to improper matching of payouts with the index ( [[#De%20Leeuw--2014|De Leeuw et al., 2014]] ). Index insurance is known to promote public–private partnerships that in turn will enhance the efficiency of overall programme delivery ( [[#Hazell--2017|Hazell and Hess, 2017]] ). Several countries, including India, Bangladesh, Thailand, Indonesia, Myanmar and the Philippines, either are currently piloting or expanding the weather-index insurance ( [[#Surminski--2014|Surminski and Oramas-Dorta, 2014]] ; [[#Tyagi--2019|Tyagi and Joshi, 2019]] ). Index insurance is constantly expanding with an estimated 194 million farmers already enrolled in China and India, which is much lower than the potential number of farmers it can reach ( [[#Hazell--2017|Hazell et al., 2017]] ).

Few significant bottlenecks that are limiting the scaling up of weather-index insurance include lack of reliable weather data, low density of weather stations leading to high basis risk, and limited data on damage and hazard for parametric modelling of the insurance ( [[#Shirsath--2019|Shirsath et al., 2019]] ). Several innovations are being tried and tested to overcome the limitations associated with the index insurance which include developing multiscale index insurance, application of remote sensing, smartphone-based near-surface remote sensing and building insurance based on vegetation indices instead of relying on weather data alone ( [[#Hufkens--2019|Hufkens et al., 2019]] ). Alternative indices, such as the NDVI, are being tested for their applications in designing index-based insurance in India ( [[#IFAD--2017|IFAD, 2017]] ). Agro-meteorology-based statistical analysis and crop growth modelling have been suggested to calibrate and rectify faulty weather indices ( [[#Shirsath--2019|Shirsath et al., 2019]] ; [[#Zhu--2019|Zhu et al., 2019]] ). Establishing automatic weather stations can improve data accuracy while preventing the delay in acquiring the weather data ( [[#Sinha--2016|Sinha and Tripathi, 2016]] ). These technological applications have already started finding space within insurance programmes designed by national governments in Asia. For example, the government of India has released new operational guidelines for the application of new technologies such as drones, remote sensing and mobile phone apps in implementation of the national agricultural insurance, which is the third largest insurance in the world ( [[#Department%20of%20Agriculture--2019|Department of Agriculture, 2019]] ).

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