Toby BEHRMANN explained how parametrics can contribute to smart decisions for climate disaster relief. Traditional data analytics make use of limited, disparate and proprietary data sources, which makes access to these data and interpretation difficult. Parametric Impact Indexes are unambiguous, universal and actionable. They make data such as climate data more transparent, accessible and easier to understand, allowing effective utilisation through programmes financing preventive measures. Parametrics allow these programmes to anticipate needs of the target group before a disaster takes place and to act swiftly at a time when their support is needed.
Parametric Impact Indexes enable direct and appropriate action by financial institutions after climatic events. For example, climate data for a typical tropical cyclone will be converted into a numerical score of only 5, whereas data for a super typhoon will be converted into a score of 50. The cyclone will only trigger a warning to the clients of the financial institution, whereas the super typhoon will trigger recovery lending. Such indexes could also be developed for other perils such as extreme temperatures or earthquakes.
The process of turning big data into pre-arranged financial solutions for disaster-relief programmes consists of four steps. The first step is to understand the client’s risk and exposure. The second step is building an impact index. The third step is structuring a financial solution. The fourth step is enabling the client to fund the programme. The clients are organisations with exposure on the ground, such as microfinance institutions. For other financial institutions, such as lender or insurance companies, these pre-arranged financial solutions expand their market to a new segment for disaster risk mitigation that they were previously not able to serve due to lack of knowledge on the risks.
In response to a question on the accuracy of the predictions by the Parametric Impact Indexes, Behrmann explained that the climate models can be used to anticipate events in the future, but also allows the analysis of data from the past. This implies that the validity of the models can be proven, which is particularly relevant for convincing private actors to use these models for their financial services or to provide funding.
Kevin HUTTLY presented the African, Asian and Americas Resilience in Disaster Insurance Scheme (ARDIS). ARDIS assists with recovery lending to support victims of high impact events and was designed to address the credit flight response by microfinance institutions. On average, disasters cause a 20% reduction in loans by financial institutions when money is most needed by the affected communities. Recovery lending is the investment of money immediately after a disaster into the affected communities. The objective of ARDIS is to use climate data and catastrophe planning for recovery lending to reignite livelihoods and community economies and respective growth of microfinance institutions.
ARDIS builds on hazard climate indexes by Global Parametrics to have a recovery lending system in place before disasters happen. With such a system in place, financial institutions can protect themselves against climate risks and may be able to obtain lower interest rates.
Key findings of a recovery lending evaluation in Africa showed that recovery lending was affordable and did not lead to client over-indebtedness. Microfinance institutions experienced a growth in loan requests. The evaluation has shown that financial institutions can make better informed decisions in their lending process using climate data. According to Huttly, recovery lending corrects a flaw in microfinancing and is not just for disasters with catastrophic impact.
Maria Theresa ABOGADO presented a case on forecast-based financing. Although donors are very generous for the 81 million people annually affected by disasters, Abogado argued that climate disaster relief can be made much more efficient by investing in disaster preparedness.
The programme Building Resilient, Adaptive & Disaster Ready Communities (B-READY) aims to improve the financial resilience of poor and vulnerable households to mitigate disaster risks and manage shocks and stresses. The programme builds the capacity of local humanitarian actors to develop and deliver user-centric financial products for vulnerable families in the Philippines. The resilience model of B-READY enables typhoon forecasting, based on climate modelling, triggers a typhoon alert and provides pre-emptive cash on debit cards of the target population. B-READY uses weather parametric forecasting to predict weather patterns and signal the likelihood of a typhoon striking in a certain community. Pay-outs are triggered when indicators exceed a pre-determined threshold.
Development of forecast-based financing requires cooperation with the government, financial institutions and the clients. In partnership, they can achieve that people are better prepared for disasters and lower climate risks.
In a discussion on the lessons learned from recovery lending, Huttly reiterated that giving victims of a disaster more donor money is not necessarily the right answer. Recovery lending, in conjunction with emergency response, can get people back on their feet without causing over-indebtedness.
One person from the audience asked how difficult it is to give a credit scoring to victims of disasters. Huttly explained that credit scoring is irrelevant after a disaster, because the client is in debt and has no credit worthiness. Behrmann stressed again that improving the understanding of risks of disasters allows financial institutions to manage those risks and provide services to people in the disaster area. Maria added that post-disaster relief can be more expensive than forecast-based financing.
Another person from the audience expressed concerns over the potentially high risks of forecast-based financing. Huttly answered that it’s a joint responsibility of different stakeholders to cover the risk and that it is important for financial institutions to assess their exposure across their portfolio.
Lukas WELLEN asked what the panellists needed from other players in the microfinance sector. Abogado requested that financial institutions develop customised solutions for each type of possible natural disaster to ensure that clients have access to credit before disaster strikes.
Wellen asked Behrmann about the quality of Global Parametrics’ data and asked Huttly how interested financial institutions outside the ARDIS programme can work with their products. Behrmann explained that Global Parametrics uses models that are open source, independently verified and consistent across the world. Increasing the client portfolio of Global Parametrics will help to further improve their climate models. Huttly explained that the recovery lending solutions are still under development and may become available to external parties in the future. The objective is to set up an education programme on recovery lending.
Finally, Huttly was asked for his view on the business model of APA, the insurance company that won the 2019 European Microfinance Award on ‘Strengthening Resilience to Climate Change’. Huttly answered that his own organisation has been involved in similar holistic business models for agrifinance which combine input supplies, technical assistance and financial products, including insurance to farmers. Their experiences were not all positive. Managing expectations and undesirable farmer behaviour such as side-selling, have proven to be problematic. Nonetheless, Huttly believes that such business models have potential to be developed further.