Page - 16 - in options, Volume summer 2019

W hen floods rise from the New Meuse River in Rijnmond- Drechtsteden, Rotterdam, homes and businesses are at particular risk. Not only do they lie outside the Dutch city’s protective dyke system, but many are uninsured because premiums are expensive. Mathematicians have however found that high premiums are unnecessary. According to Yuri Ermoliev, a researcher in the IIASA Advanced Systems Analysis (ASA) Program, insurance companies could lower their prices, safeguard citizens from catastrophic losses, and still make a profit. Research shows that if you plot size of loss against frequency, the result is not a normal bell curve but a distorted one with a “fat tail”. Insurers need the right tools to deal with fat-tailed risks. The commonly used approach is “annual average loss”, which suits frequent, low-consequence risks like car accidents, but can’t tackle the peculiarities of occasional catastrophes. “It is like planning for a trip where the temperature will mostly be -10°C but there’s a chance it could fall to -50°C,” explains ASA Program Director Elena Rovenskaya. “If you make clothing decisions based on an averaged temperature it could be disastrous”. Ermoliev and his colleagues separated out high risk, unlikely scenarios in the fat tail and treated them differently, allowing premiums to be calculated in a more sophisticated way. “In the example of Rijnmond-Drechtsteden, the model yielded lower premiums without making the insurance business unsustainable,” says Rovenskaya. Climate change also imposes direct costs for banks, such as increased maintenance for infrastructure, and the transition costs of resculpting themselves for a low-carbon existence. Legislation to discourage coal use, for example, might make loans in that sector more risky. Banks therefore have a thirst for scenario data about how investments and prices may change. Former IIASA researcher David McCollum, IIASA Energy Program Director Keywan Riahi, and counterparts from the Potsdam Institute for Climate Impact Research, worked with 16 international banks under the Task Force on Climate-Related Financial Disclosures to help banks plan for the future. They used the MESSAGEix-GLOBIOM model to simulate the effect of climate policies on land use, and energy production and distribution over decades. The banks particularly wanted projections for energy and food prices, greenhouse gas emissions, and energy mix. These projections were fed into another model to see how a bank with loans to multiple companies might fare. McCollum found that while banks, like policymakers, wanted to look decades ahead, they also wanted near-term results and more granularity. “They don’t just care about the total number of gigawatts of coal power versus solar or wind power for China in a certain year, but also how many solar photovoltaic modules are needed and where that production might take place,” he explains. “The project took a lot of bridging between disciplines. You’d be surprised how few large banks and other corporates do Written by: Aislin g Irwin Financial risk in the spotligh t IIASA RESEA RCHERS LOOK ED AT VARIO US ASPECTS OF GLOBAL FINA NCIAL RISK FROM A SYST EMS ANALYSI S PERSPECTI VE www.iiasa.ac.at16 Options Summer 2019