Predictive analytics and the evolving nature of risk

Predictive analytics and the evolving nature of risk | Insurance Business

Predictive analytics and the evolving nature of risk

With technology rapidly developing, risks have been evolving alongside it and may leave risk managers struggling to keep up. Previously unknown risks have emerged, while some existing ones have become more complicated.

Adriano Lanzilotto (pictured), vice president and client service manager for London operations at FM Global, spoke on how technology can be harnessed to better understand and mitigate risks.

“Technology has rapidly transformed at an unprecedented level bringing with it a spate of opportunities but also a host of vulnerabilities,” he told Corporate Risk and Insurance. “As we become ever more connected as a world, the potential for widespread cyberattacks has become more likely. The Global Risk Perception Survey (GPRS) ranked ‘massive data fraud and theft’ as the number four global risk by likelihood, with ‘cyberattacks’ ranked at number five. Cyberattacks have demonstrated time after time that they transcend borders, climates, and industries.”

Cyber is one of the least-understood risks due to its novelty, but is also one of the fastest-changing, with previous strategies quickly becoming outdated or redundant. In order to offset the unpredictable element of the evolution of risk, insurers are looking to big data solutions, such as predictive analytics, to support risk managers.

“Understandably, cyber can seem like a daunting issue for risk managers,” Lanzilotto said. “The potential severity of a cyberattack occurring, coupled with the often complex jargon associated with cyber security can sometimes make risk managers feel as though they are underqualified to effectively manage cyber security. However, to prevent being caught off guard, risk managers need to treat cyber just like any other risk. By using available data, and partnering with knowledgeable insurers, risk managers can gain a better insight into cyber-risk and implement comprehensive cyber security policies that will help businesses be more resilient to cyberattacks.”

Climate change complicates the equation
Aside from cyber risks, traditional risks such as natural hazards are changing, said Lanzilotto. Factors such as climate change and increased population in coastal areas have exacerbated many environmental-related risks such as flooding, leading to more frequent and intense risk events.

“Environmental risks have consistently dominated the GRPS, increasing the need for resilient and sustainable risk management policies to be implemented,” he said. “Risk managers need to constantly review and improve their risk management policies in line with the changing nature of risk to be able to continue to prevent disruption due to a loss event.”

As climate change contributes to stronger storms and higher sea levels, flood has become one of the top risks many businesses and communities face.

FM Global has developed a Global Flood Map to help risk managers assess their flood risk. According to Lanzilotto, the map is based off in-house data collected by field engineers, as well as additional data collected by NASA, giving an up-to-date and consistent view of flood risk, rather than a model based on potentially out-of-date historical data. The tool highlights high hazard locations (which are susceptible to one in 100 year events), and moderate hazard locations (which are susceptible to one in 500 year events).

Read more: Language around flood risk can create false sense of security - FM Global

Data as a weapon against risk
According to Lanzilotto, predictive analytics helps risk managers identify incidents that are likely to lead to a significant loss. With risk becoming increasingly complex, predictive analytics tools give risk managers the ability to analyse big data, capture the changing nature of risk, and provide insight into the most severe risks their businesses may face.

“One of the key elements of predictive analytics is access to clean and reliable data that has been consistently collected,” he said. “FM Global’s in-house data has served as their basis for their predictive analytics capabilities. This data is collected by our field engineers, who make 100,000 site visits each year, capturing 700 data points at each facility resulting in 70 million individual data points. This engineering data, based on physical conditions backed up by the expertise of our engineering colleagues, provides far greater accuracy than actuarial models.”

Read more: Why 2019 is the year of better data analytics for risk management

Due to the large amount of data collected over a long time, FM Global is able to produce a top 1,000 list of client locations with the highest likelihood to experience a large loss, he explained. To demonstrate the impact of predictive analytics, he revealed that 43% of the total loss sustained by FM Global’s insured clients in 2017 came from  these 1,000 locations, corresponding to just 2% of the company’s insured portfolio. This tool is known as ‘Locations Predisposed’ and is part of FM Global’s suite of analytics products.

Other tools include ‘RiskMark’, which benchmarks the risk quality of a client’s locations against risks such as fire and natural hazards, as well as boiler and machinery considerations. ‘Relative Likelihood’ identifies exposures at a location that are most likely to be associated with a loss. Meanwhile, ‘Equipment Factors’ assesses equipment in order to identify those most at risk of breakdown.

Quantifying what was previously unquantifiable
Lanzilotto said that in the future, analytics tools will be able to provide risk managers with data that was previously impossible to quantify. This includes the intangible effect of losses on a company, such as reputational damage after an event. It is these intangible and uninsurable elements that prove the most difficult to assess.

“As a result, it has often been difficult to persuade financially constrained executives to invest in the good risk management practices needed to avoid or mitigate it,” he said.

In 2019, FM Global created a tool allowing clients to quantify the previously unquantifiable impacts that a loss can have on factors such as market share, missed growth opportunities and negative investor sentiment.

“The Total Financial Loss Modelling tool the company has developed, based on our own data, helps empower risk managers with the tools to effectively show the C-Suite the benefits of risk management (or conversely the potential risks of not investing in risk management),” Lanzilotto said.