The GIACIS Food Security risk insurance project in Ethiopia Geodata for Innovative Agricultural Credit Insurance Schemes A Dutch-Funded G4AW project

Kees de Bie (23 Nov.’16; WUR-Alumni Netwerk, Enschede)

The Project The Index Why Success

Alimni Meeting: Climate Adaptation practiced in Urban and Rural environments

The minister explained that the collaboration in the G4AW program is a fine example of the role business can play in tackling climate change. Ploumen naar Marrakesh voor VN Klimaatconferentie

Lilianne Ploumen: In Ethiopia a consortium made up of financial institutions, the University of Twente and the Ethiopian national meteorological agency is providing insurance against climate risks, such as unexpected drought, for millions of smallholders. Better data allow more accurate risk estimates to be made, keeping premiums affordable. According to Ms Ploumen, ‘The program will support at least 3 million smaller food producers over the coming years, and probably more, as technology becomes more sophisticated and more affordable.’

Focus on Droughts in Ethiopia NOT acceptable anymore by Ethiopians!!

2008: PM Meles Zenawi states there can be NO more famine ever in Ethiopia

25 Jan 2016 Foreign financial assistance is already arriving and, combined with money committed by the Ethiopian government, totals about $360m to confront the drought's aftermath. But the overall emergency response could cost $1.4bn.

Drought is NOT Famine!!

18 March 2016: Ethiopia’s prime minister has urged the international community to increase its support towards the ‘Horn of Africa’ state as 10 million people face going hungry.

But v.recently: 2015 Early Season – such a drought did not happen since 2008!

and again: 2015 Late Season – same areas were hit twice in one year!

This makes the 2015 drought UNIQUE

These farmers lost their ability to recover

Insurance-ABC • •

Based on: World Bank Agricultural Risk Management Training Materials.

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Loss assessment cost in small farmer systems Not suited to complex perils, especially drought and pest

Basis risk is key challenge Technically complex Needs good (meteo/RS) data & models

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Not suited where farms are small High premium and admin.costs Moral hazards

Yield histories not available High basis risks at local level

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Most past efforts concern Trial-and-Error Pilots

Abstract: • Many pilot projects have experimented about every possible insurance design under diverse conditions, involving farmers, cooperatives, micro-credit institutions, governments, commercial banks, insurance and reinsurance companies.

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The indices, which play a pivotal role in the insurance schemes, also constitute one of their main weaknesses. Very little crop modelling and forecasting knowledge is put to use in index design, and only occasionally do remote sensing data and advanced statistical methods play a part.”

The editors state that years of scientific experience by : • Agronomists • Meteorologists • Remote Sensors • Early warning experts • Natural resources scientists • Statisticians • Insurance brokers and ALL their linkages are still poorly utilized.

Has all needed knowledge & disciplines !!

Intro

The Index Why Success

GIACIS Highlights: Technology

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Offers a GeoData-driven DROUGHT risk-mitigation (insurance) product

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Index-based (NOT Indemnity-based, NOT Crop-based, NOT Impact-based, but Exposure-based)

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Remotely Sensed Index: Hyper-Temporal NDVI-data (Spot-VGT & Proba-V)

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Underpinned by FOUR business models (extreme low-costs solutions) • • • •

Farmers Insurance Companies Credit suppliers Digital financial technology company

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100% Scalable and Flexible

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Solid statistics: • • • •

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NDVI = Greenness (active chlorophyll)

10 day intervals at a 250m resolution

Threshold NOT derived from 16 year pixel-based repeats only Full use of country-level stratification defining Crop Production System zones NOT Sample statistics, but Population statistics (use of percentiles) Full alignment to local growing seasons and terrain variability

Data capturing (GeoNetcast), pre-processing (Ilwis), and interpretations, all fully carried out by Eth.partners

GIACIS Highlights: Technology Higher basis risk

Selected Index NDVI

Climatological Drought

response to Agronomic Drought

The credit amount is insured, based on NDVIperformance during the Is very area specific growing season Is crop a-specific

More accurate / Less errorpropagation

Lower basis risk

GIACIS Highlights: Organizational

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A PPP with few partners based on maximizing complementarity (systematic synergetic approach) • Provides financial inclusion • Promotes agricultural investment • Brokers sustainable production methods • Provides risk transfer tools • Uses branchless banking technology

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Upgraded from a Project to a Program: • • • •

Managed now by an all Ethiopian PPP No longer managed as a Pilot scheme Part of the 5-years Growth and Transformation Plan (GTP-II) First state approved Micro-Insurance product in Ethiopia

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Targets smallholder farmers (80% < 0.5ha) with an aim of 15m HH insured in 2025

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Aims to boost purchase of agricultural inputs (through change in risk avoidance behavior)

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Makes an insured credit package (bundled) locally available

Intro The Project Why Success

Country zonation The Zonation at a 1x1 km resolution !! Hyper-Temporal NDVI-data are

“information-rich”

This is CLIMATE, etc

They reflect an ‘evidence-based’ response

of the land cover to soil/terrain/climate/land use/etc.

Weather creates seasonal anomalies

Greener SPOT-VGT: NDVI (DN-values)

(May’98 – Dec’13; 36 images/year; downgraded resolution)

The annual behavior of 60 Crop Production System Zones that cover the highlands of Ethiopia

Selected CPS-Zones, depicted as Gradients

Different zones relate to differences in growing seasons, crops grown, crop calendars, etc.

By CPS-Zone ONLY assess data within the Growing Season 30 zones are clearly associated with cereal cultivation (T-W-B-M-S)

10-day steps

The ‘growing season’ as extracted by CPS-Zone

Defines by zone the period of the actual growing season

Apply set thresholds to individual pixels Climatology by zone with thresholds

actual ndvi-data of 1 pixel

16 annual repeats

Weather impact on NDVI by pixel translates into payouts

Payout amounts (0-100%)

The final payout amount will be an averaged value for the whole season

Intro The Project The Index

• Gvmt acts/decides FOR farmers [knows what is needed] • Gvmt creates and tasks ATA to invoke/guide agr. transformations • Gvmt sets GTP-II goals (5 pillars) • Gvmt defines needed laws and regulations

 This ENDS dissensus!!

• ATA implements a credit scheme • Kifiya (private) has financial technology and agent network Credit MUST be insured: • Farmers are jailed if they default • Credit comes from a revolving fund that cannot “dry-up”

• Gvmt acts/decides FOR farmers [knows what is needed] • Gvmt creates and tasks ATA to invoke/guide agr. transformations • Gvmt sets GTP-II goals (5 pillars) • Gvmt defines needed laws and regulations  This ENDS dissensus!!

• GIACIS was approved and developed all required modalities

• Gvmt tasks EIC to prepare a microinsurance product

• GIACIS presents it product to many potential clients, including EIC • EIC states: we define our own according to OUR requirements • But: EIC could not manage

 The Minister of Finance acted on this “deadlock”  GIACIS was requested to officially present its product  Then, very fast, he approved the product as a state-insurance product  He tasked PFEA to manage the new PPP  He ordered EIC to sell the product and the MoA to 100% cooperation  He and the PM discussed the product with Swiss-Re  PFEA organized the public launch of the sales season  The PM organized premium-costs subsidies for 2017  ATA signed the needed link to get credit insured, etc.

Thank You