Understanding and predicting human behaviour is one of the greatest challenges to modellers of both pandemics and cyber risks, according to a new report from CyberCube.
The report focuses on the lessons that pandemic and cyber modellers could learn from each other. According to the report, Viruses, contagion and tail-risk: Modelling cyber risk in the age of pandemics, the potential for political decisions and the public’s response to affect the duration and severity of both pandemics and cyber risks is critical to successful modelling.
The ways in which modellers represent the interactions between human-created risks is critical to building effective models, the report said. Although pandemics originate from pathogens, the challenge is how models can illustrate a range of outcomes based on individual and societal reactions that can affect the spread of diseases or cyber threats.
The report also found that a dearth of data can impede progress for both types of modellers. Since the start of the 20th century, there have been fewer than 12 major global pandemics – and although there have been thousands of cyber incidents since the advent of the internet, there have been very few significant systemic incidents. That means there is not a wealth of data to assess the potential impact of such events, the report said.
“It’s clear that lessons can be learnt and applied to cyber risk modelling from understanding how pandemic models have evolved,” said Oli Brew, head of client success at CyberCube. “AS the COVID-19 pandemic continues, even though there are differences between computer and human viruses, parallels are emerging in the modelling, the methodologies and the data challenges. There is real value in learning from interdisciplinary teams in how to balance the needs of accuracy and precision in developing models to meet the market needs. At a minimum, the need for a creative, but reality-based imagination to represent forward-looking risks is critical.”
“In both cyber risk and pandemics, there is a need to consider accumulation risk,” said Dr. Hjalmar Böhm, senior actuary at Epidemic Risk Solutions, a dedicated epidemic risk at Munich Re. “For example, a pandemic is a key consideration for life insurers, and a high mortality event could create significant economic loss. A solid approach to controlling accumulation risk exposure needs to be the basis for every business model to control epidemic risk insurance.”
“There are parallels with modelling the global spread of a disease and how cyber systems are connected – both are network issues,” said Nita Madhav, CEO of pandemic modelling firm Metabiota. “The impact of mitigation risk and early action can potentially make a difference. Furthermore, you can be asymptomatic with COVID-19; similarly, you may not know if a cyber intruder has already infiltrated your network.”