Presentation is loading. Please wait.

Presentation is loading. Please wait.

Www.rmsi.com Delivering a world of solutions Index Based Insurance – an innovative approach towards agricultural risk financing mechanism Inderjit Claire.

Similar presentations


Presentation on theme: "Www.rmsi.com Delivering a world of solutions Index Based Insurance – an innovative approach towards agricultural risk financing mechanism Inderjit Claire."— Presentation transcript:

1 Delivering a world of solutions Index Based Insurance – an innovative approach towards agricultural risk financing mechanism Inderjit Claire October 2007

2 Delivering a world of solutions Background – a general perspective High exposure of low income countries to weather risks (drought, floods…), pests and diseases Lack of insurance and other risk management tools Need of innovative approaches to deal with the nature of agricultural risks Rainfall and economic performance in Andhra Pradesh

3 Delivering a world of solutions Background – Traditional Vs Index Based Insurance Financial protection against adverse weather conditions Contracts can be structured as insurance or derivatives Based on the performance of a specified weather index during the risk period Payouts are made if the index crosses a specified trigger level at the end of the contract period Protect against yield volatility Multi-peril Crop Insurance High Administrative Costs Moral Hazard Adverse Selection Index-Based Weather Insurance Rainfall is a proxy for damage Objective triggers and structured rules for payouts Improved correlation between need and provision More on Index Based...

4 Delivering a world of solutions Goals The goal is to meet the demands of various stakeholders – Farmers – Insurers – Delivery channels – Marketing agencies/organizations etc Steps involved in the design and validation of the weather insurance pilots – Demand assessment » Ensuring initiatives were in response to perceived and expressed needs of farmers and their interest groups – Identification of key insured parties : compulsory or voluntary – Determination of key perils » The most important factor in insurance design – Decision on crops to be covered – Loss assessment procedures – Rating – Identify possible complementary role of Government

5 Delivering a world of solutions Weather Insurance Product Development – a ladder

6 Delivering a world of solutions Desk Research Evaluation of weather and crop yield data – Availability of weather data » Temporal » Spatial, » Limitations – Availability of crop yield data » Temporal » Spatial » Limitations Collection of relevant research – IMD Crop calendar – Refer ICAR publications on Field and Plantation crops – Meeting with agrometeorologists, agronomists » To identify essential crop pheonphase risks » Critical crop growth stages and their dependencies to rainfall affecting yield – Review of insurance products being offered, if any! – Local climatology Stage 1 - Desk Research Literature review - draw lessons from past experiences Data availability Crop yield data CCE data/insurance units level Mandal/district level Selection of area weather data -Daily -weekly Selection of crops - Identify preliminary risks

7 Delivering a world of solutions Data Analysis Stage 2 - Data analysis Sanity checks -Data consistency -Data quality -Data limitation 1. Weather Data cleaning and enhancement - Replacement of missing and erroneous values through spatial and temporal interpolation/correlations 2. Detect data discontinuities -Through one or multiple stations values 4. Evaluation of crop yield data - For mandal/ district level validation as proxy of weather 3. Weather simulation (WXGEN) -To generate 100 yrs of data using Markov chain model

8 Delivering a world of solutions Field Research Stage 3 - Field Research 1.Demand assessment -Examine the risk structure of specific key crops 2. Determination of key perils -a key factor in insurance design 3. Decision on crops to be covered -another key factor 4. Identify crop growing season -Key crop growth stages and duration 5. Significance of specific weather parameters -Analysis on index able weather perils 6. Critical/ strike for weather parameters -Definition of strike and exits for the payouts -Definition of daily rainfall floor -Periodic rainfall caps -Daily level excess rainfall limits etc

9 Delivering a world of solutions Contract Design Stage 4 – Preliminary contract design Identification of insurable risks (Key Perils) Production risks due to adverse weather conditions 1.Drought/ Deficient rainfall Sowing cover e.g. failed sowing/ germination failure Phenophase – wise cover e.g. Vegetative Growth, Flowering, Grain Filling etc. 2.Excess rainfall 3.Frost (temperature based index) 4.High Winds 5.Satellite NDVI based cover

10 Delivering a world of solutions Weather Contract Design Overarching Objective To design contracts that cover both magnitude and frequency of deviations of key weather parameters from requisite levels. The challenge was to do it in an integrated manner (under a single cover) while ensuring robustness of the contracts

11 Delivering a world of solutions Weather Contract Design (Choice of Key Product Components) Choice of caps and floors Choice of triggers/ limits Choice of indemnity payment levels Choice of period & stages of cover Interchangeability between indices and actual weather parameter values Choice of sum assured under various covers Overall flexibility in setting product parameters

12 Delivering a world of solutions Coverage of Weather Risks – Cotton, Mahabubnagar District Harvest Stages Sowing & Germination Vegetative Growth & Flowering Boll Formation & Boll Development Deficient Rainfall for Vegetative Growth & Flowering Deficient Rainfall for Boll Formation & Boll Development Perils Inadequate Rainfall for Sowing Covers for Crop Stages after Germination days 50 days 40 days Ploughing

13 Delivering a world of solutions Bundled Product Payouts - Historical Data

14 Delivering a world of solutions Risk assessment Risk profile of the areas – importance of weather risk in this profile Availability of yield data and agronomic information Issues related to basis risk – topographic make-up, presence of microclimates Weather data and infrastructure – presence of weather stations, satellite information, historical data Time period – key seasonal milestones

15 Delivering a world of solutions Data Availability Rainfall data for Anantapur and Mahabubnagar Blocks – Field visit - 4 mandals in Anantapur and 6 Blocks in Mahabubnagar – IMD weather data – Anantapur » Rainfall data available for years (upto 2003) – Mahabubnagar » Rainfall data available for years (upto 2003) Crop Yield Data – Mandal level – District level Primary/Secondary information collected – Field survey – Agro meteorological/ agronomic information – Literature review – e.g., ICAR publications, iKisan etc

16 Delivering a world of solutions Data Availability Crop Calendar

17 Delivering a world of solutions Probabilistic Drought Assessment – a framework Production losses Stochastic normal & drought events Historical weather Hazard Module Simulated Weather Generator Vulnerability Module Crop Yield Model Planting Area Model Crops Soil Mgmt. Customized from rapid onset disaster modeling framework Probabilistic drought risk assessment model – Hazard module – Vulnerability module – Economic module

18 Delivering a world of solutions Hazard Module – Historical Weather Mandal level Rainfall data used Is 1988 – 2003 data enough (18-25 years) for non-parametric analysis? Simulations produce more tail (extreme) events

19 Delivering a world of solutions Historical Weather – analyzing hazard Data cleansing - Sanity checks – Spatial and temporal consistency – No de-trending Rainfall is lowest in Anantapur District Coefficient of Variation is highest – Anantapur – Mahabubnagar Rainfall risk is very high in these two districts

20 Delivering a world of solutions Hazard module – validation of stochastic weather events The exceedance probability curves for both annual rainfall in historical and simulated data show the same trend (zero exceedance probability is equal to 800 in both the cases and rainfall with exceedance probability as 1 is just below 200). Therefore the corresponding yield and rainfall curves from historical and simulated data are in line with each other.

21 Delivering a world of solutions EPIC simulated yield – Generated at Mandal level – Mandal level rainfall data used – Management inputs taken from ANGRAU – Field based inputs used Reported yield – Available at both Mandal and district level Results validated – drought years Agro-met model Vulnerability Model - Crop model

22 Delivering a world of solutions 22 Vulnerability Mapping State of Andhra Pradesh Crop Yield Simulations - For each model – Using historical data and then – Simulated weather events Vulnerability Mandal level Across six districts of AP Covers both high and low vulnerable areas

23 Delivering a world of solutions Vulnerability Model - validations The yield deviations of the simulated data is in the same range as the historical yield data

24 Delivering a world of solutions Losses Exceedence Probability loss Average Annual loss Probable Maximum loss

25 Delivering a world of solutions Key Issues Technical Issues – Basis risk » Introduction of Mandal-level weather stations can help to mitigate intra-district heterogeneities » Farm level issue may prolong until density of weather stations improves substantially – Daily level measurement of rainfall and its dissemination to end-clients » Regular and timely communication of weather data to facilitate better tracking of indemnities – Asymmetries in geographical demarcation of insurance units needs consideration » Interpolation of weather data between existing and proposed weather stations to offset asymmetries due to administrative demarcation – Traditional MPCI will not get covered » Fire, hail storm etc – Pricing at every Mandal will NOT carry the same degree of confidence » Shall depend on quality and availability of weather data applied » Will require supporting field data and local knowledge » Allow premium adjustment based on experiences and underlying risk Administrative Issues – Geographical and administrative equivalent of Mandal does not exist in any other pilot state except A.P. – Banks covered during the field research have expressed difficulties in two insurance schemes –

26 Delivering a world of solutions Early Rice Late Rice Satellite based insurance contract design

27 Delivering a world of solutions Overview 12 June July August May 2006 FCC Classified Basis for approaching the new Classification – Spectral signatures

28 Delivering a world of solutions Crop mapping – Supervised Classification technique – Area Estimation – Accuracy Assessment Ex: Wheat NDVI Analysis Graph showing reported vs mapped acreage figures for wheat crop in the district. The difference is of %. NDVI analysis – NDVI value computation using available values

29 Delivering a world of solutions NDVI based insurance product for wheat in Farrukhabad tehsil of Farrukhabad district Ex: Indemnity Payout Structure for NDVI Based Cover Payout Structure Crops having satellite derived rescaled mean NDVI values greater than 181 will receive no compensation Between 181 and 180.5, farmers will receive 2 rupees for 0.5 value of deficit Between and 179, farmers will receive 4 rupees for 0.5 value of deficit Between 179 and 175, farmers will receive 5 rupees per value of deficit Between 175 and 173, farmers will receive 10 rupees per value of deficit Payout structure is based on the slabs for a standard sum assured of Rs 100

30 Delivering a world of solutions At the household level: – Gives farmers greater flexibility in investment decisions – Banks have greater interest in lending – Farmers see potential in investing in their farms For governments: – Provides government contingent financing – Allows the cost of drought risk to be smoothed over time – Provides some predictability to drought financing and buys time for other emergency responses to take affect – Provides government a level of autonomy Conclusions


Download ppt "Www.rmsi.com Delivering a world of solutions Index Based Insurance – an innovative approach towards agricultural risk financing mechanism Inderjit Claire."

Similar presentations


Ads by Google