Disaster risk finance

Innovative financial instruments can make funds available to respond to and recover from hazards much more quickly

The Natural Environment Research Council (NERC), the Department for International Development (DfID) and the Economic & Social Research Council are funding projects to address the topic of building resilience to natural-hazard-related disasters using financial instruments. Projects are working to apply environmental and social science research to the design, development, refinement and validation of financing instruments to help developing countries respond to and recover from extreme weather and natural-hazard-related disasters.

The overarching goal of these projects is to have an effect on the developing world. To achieve this, projects are working closely with practitioner project partners who have a role in the design, development and application of innovative financing mechanisms for developing countries (for example, non-governmental organisations (NGOs), policymakers, disaster risk-management actors, and insurance companies).

Project resources

Satellite data for Weather Index Insurance-AgricuLtural EaRly warning system (SatWIN-ALERT)

Institute

University of Reading

Project website

https://satwin.iri.columbia.edu/

Background

For the more than 200 million farmers in Africa who depend on rain-fed agriculture, drought is a matter of life and death. Their vulnerability is often aggravated by a lack of access to risk management tools such as insurance, which also limits their ability to take productive risks on their farms.

Index insurance is an affordable alternative to traditional insurance, where compensation is based on measured losses. Index insurance bases compensation on environmental conditions (indices) which affect agriculture and are easy to measure (such as rainfall, levels of vegetation, and yield). However, insurers face challenges in defining indices for drought which reduce basis risk (the risk that compensation will not be in line with observed losses).

SatWIN-ALERT is a new system which will support the insurance community in defining indices, and enable aid agencies and governments to identify events and take action to support farmers who are facing uncompensated losses.

Aims

The project aims to develop an operational system which empowers farmers to benefit from robust financial instruments, based on state-of-the-art models, observations and forecasts.

Approach

SatWIN-ALERT is a system which allows data from satellite observations, environmental conditions, seasonal and sub-seasonal forecasts, and socio-economic research to be integrated into the design of insurance indices.

Project site

Malawi, Nigeria, Senegal, Malawi, Zambia and Ethiopia

DRiSL: The Drought Risk finance Science Laboratory

Institute

University of Sussex

Background

There is a growing momentum in the humanitarian system to move away from funding models based on post-disaster appeals, and towards obtaining and distributing funds before a disaster occurs.

This shift can enable frontline humanitarian organisations and government agencies to save lives by mobilising more collaboratively, more predictably, and in anticipation of crises. Acting before a disaster to distribute money, drought-resistant seeds, or animal fodder, or to prepare supplies such as food, medicine and hygiene kits, reduces the impacts of a disaster and can be carried out a lower cost than traditional post-disaster humanitarian response.

For this to occur, trustworthy forecasts of hazards like storms, floods and droughts, and credible information about the people and systems exposed to these hazards, are needed. Forecast-based and disaster risk financing initiatives use this information to anticipate potential disasters and set pre-agreed triggers for the release of finance which can be used to take early action.

However, this information must also be accessible to, useful for and, crucially, trusted by humanitarian and government agencies. There is currently no method to provide an independent review of the scientific credibility of these systems. This is a stumbling block in the adoption of these ground-breaking initiatives by the organisations which would put the information into action.

Aims

DRiSL will support humanitarian practitioners to use forecast information in a way that will support their decision-making, so that they are able to take early action based on trustworthy information.

Approach

The project will assess a range of global drought models in regard to their uncertainty and ability to depict emerging food security crisis. Global data products will be explored alongside data on the ground of drought and food security events.

Project site

Pakistan, Zimbabwe and Madagascar

Mitigating basis risk in weather index-based crop insurance: harnessing models and big data to enable climate-resilient agriculture in India

Institute

University of Manchester and the International Food Policy Research Institute (IFPRI)

Background

The livelihoods of millions of smallholder farmers across the developing world are under threat from extreme weather events, such as droughts, floods, and heatwaves, with risks projected to increase significantly in future years due to climate change.

Crop insurance can protect farmers from the financial risks posed by these extreme weather events, supporting them to overcome poverty traps and invest in climate-smart agriculture, building resilience and enhancing food security.

However, traditional insurance models, where compensation is based on verified losses, are time consuming, present high transaction costs, and can lead to disputes and delays that deter farmers from purchasing insurance. Parametric insurance, such as weather index-based insurance, is an alternative model which can address these issues and provide a cost-effective, reliable alternative to protect farmers against risks posed by extreme weather and climate change.

However, current weather index-based insurance products often struggle to reliably capture actual yield losses farmers experience, severely limiting their ability to protect farmers from climate-related risks. This project will apply science to the design of smarter index insurance products that meet the needs of farmers, insurers, and governments.

Aims

The overall aim of this project is to improve the performance of weather index-based insurance by combining state-of-the-art environmental modelling, crowdsourced data from farmers, and bug datasets to develop insurance contracts that deliver reliable and timely payouts to smallholder farmers in the event of a weather shock.

Approach

The project will combine crop simulation modelling, satellite and smartphone imagery of crop growth, and high-resolution gridded estimates of spatial weather variability to accurately predict weather-related crop yield losses at field levels in smallholder agricultural systems.

Project site

India

Improving the Role of Information Systems in Anticipatory Disaster Risk Reduction (IRIS)

Institute

London School of Economics & Political Science

Background

Humanitarian agencies are able to use weather (and other) forecasts to act in anticipation of humanitarian crises. For example, when a heatwave or hurricane is forecast, supplies can be moved into position early and emergency supplies positioned or pre-distributed. This reduces the overall impact and the cost of responding to the disaster.

However, financing in advance of a disaster requires a high level of confidence in the forecast, to avoid the possibility of misallocated or wasted resources. Many forecasts are currently available but not all are accompanied by an assessment of the forecast quality. For example, it may be that the forecast is over-confident, predicting an event more times than it is actually observed, or it could be under confident, failing to predict events which do then occur.

Aims

Allowing humanitarian agencies to act confidently in anticipation of humanitarian crises, and to effectively implement forecast-based financing schemes such as insurance or anticipatory funding allocation.

Approach

Developing and demonstrating a general method of measuring and displaying the information content of forecasts, using a novel idea which is based on existing research and freely available data.

Integrated Threshold Development for Parametric Insurance Solutions for Guangdong Province China (INPAIS)

Institute

University of Birmingham

Background

Tropical cyclones affect the economic and social development in China, leading to major losses in the country, especially Guangdong Province. Parametric insurance has the potential to support resilience, and effective response, to tropical cyclones.

SwissRe in Beijing has been developing parametric insurance programmes for the Guangdong provincial government, but faces two key challenges: first, it is extremely difficult to accurately estimate losses caused by tropical cyclones at sub-regional or prefecture levels, so some specific areas are likely to receive too much or insufficient compensation. Secondly, the information available about losses caused by tropical cyclones is extremely limited, making it difficult to assess the frequency, intensity and impact of these disasters.

Aims

INPAIS aims to improve the assessment of hazard risk, and therefore the accuracy of the trigger points at which compensation is released in Guangdong Province, facilitating rapid response and recovery.

Approach

INPAIS will use the Storm Severity Index to measure the severity of tropical cyclones and collect information to support assessment of losses at prefecture level.

The project will also use an operational forecast archive to estimate how frequently and intensively tropical cyclones can be expected to occur so that triggers for compensation can be refined and mechanisms to distribute payouts can be improved.

Project site

China

Coastal Ecosystem Recovery Financing for the Future (CERFF): developing insurance products to enhance response and recovery from tropical cyclones

Institute

University of York, Cefas, Overseas Development Institute, and Willis Towers Watson

Background

Coastal ecosystems, such as coral reefs, mangroves and seagrass beds, can provide protection against tropical cyclones, as well as supporting sectors such as fishing and tourism. However, extreme storm surges can damage these ecosystems, reducing their capacity to protect coastal communities from storms that can cause deaths and damage property, as well as providing food and income, and controlling erosion.

Financial investment in active restoration of these ecosystems is feasible and can be cost-effective over small areas. When large areas of habitat are damaged, setting aside areas of the ecosystem as reserves may be a more cost-effective approach, but people who depend on the ecosystem for their livelihoods, such as fishermen, need to be compensated financially for loss of short-term earnings.

Insurance of these ecosystems could provide a solution to allow for immediate funds to be made available, whether for restoration or as compensation to fishermen. The availability of such an insurance product would enable rehabilitation of the reef or seagrass bed following an extreme storm surge to recover their protective and livelihood-related functions.

Aims

The CERFF team will develop an insurance product which will enable rapid responses to extreme events, reducing the impact of tropical cyclones by supporting preparedness and rapid response.

Approach

The CERFF project brings together applied scientists and academics from natural and social sciences and the humanities, with a leading global broking and solutions company. It builds on extensive marine data and combines it with species distribution modelling and economic assessment of the value of coastal ecosystems to communities.

Project site

Grenada

Financial planning for natural disasters: the case of flooding risk in Central Java

Institute

Loughborough University

Background

As documented by the World Risk Index, Indonesia is among the most exposed of all countries to risk of natural hazard-related disaster. Only Japan and a number of small island states are more exposed. At the same time, as a large and geographically diverse middle-income country, Indonesia arguably has more scope than island nations for managing and diversifying at least some of the financial cost of these disasters at national level, using government transfers and private insurance. While the market for private insurance is well developed in Greater Jakarta, there is relatively little uptake of insurance protection against natural hazard-related disasters elsewhere in Indonesia, including Central Java.

Aims

Loughborough will co-develop with our local partners and the flooding consultancy JBA associates a 'decision support framework' (or DSF) with demonstration software implemented in R and a series of analyses ('case studies') illustrating the use of loss and financial modelling to plan ahead for the financial consequences of extreme flood events.

Our project seeks to develops tools and analytical frameworks for modelling and managing the financial costs of extreme flooding events in Surakarta and Semarang, two of the main cities in Central Java. This will include the use of private insurance and other instruments of risk transfer to cope with the financial consequences of extreme flood events.

Loughborough is working with local universities UNS and UNDiP, and other stakeholder groups, to:

  • develop analyses of the costs of local flood insurance provision.
  • understand the attitudes of households and managers of public sector assets (such as hospitals and schools) to purchasing risk protection.
  • engage with regional and national policy makers on development of insurance and other tools of disaster risk finance.

Approach

A major task has been extending InaSAFE - an established tool which produces realistic natural hazard impact scenarios for better planning, preparedness and response activities –to calculate the financial losses and assess the costs of protection from extreme flooding events in Semerang and Solo.

The project’s application of InaSAFE combines data on levels of rainfall and flooding with information about the location of housing and other buildings, and supplementary information about financial vulnerability to flooding events. The project has also developed a simple framework for estimating the costs of insurance provision in a sparse data environment, such as that of central Java. Loughborough is also developing and testing a graphical user interface with users to illustrate the financial losses caused by flooding, and explore their willingness to pay premiums for financial protection. This is further supported by survey work with households, managers of public sector assets and policy makers to understand existing arrangements for coping with risk, and the potential for improved disaster risk finance tools to manage the financial burden of extreme floods.

Project site

Indonesia