Geospatial intelligence revolution in insurance and risk management

Source(s): United States Geospatial Intelligence Foundation

By David J. Alexander et al.

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Over the last three years, nearly three in four Americans have been impacted by disasters (hurricanes, floods, fires, and violent extremism) either directly or indirectly through an immediate family member or friend. From 2016–2018, 37 states and two territories received presidentially declared disasters. These disasters cost the U.S. taxpayer a cumulative total of $457 billion and 3,663 lost lives. The vast majority of these costs were incurred from damage to public buildings, infrastructure, and natural ecosystems. These statistics, when taken alone, are disturbing, but when coupled with other statistics are even more alarming. They show that U.S. disaster risks are not just of concern to lives and property, but also to our way of life as they threaten the fiscal solvency and fabric of the nation. These trends are taking an unprecedented physical, financial, and psychological toll on America, affecting our global, national, and economic security in unprecedented ways. How do we reverse these trends without technological advancement and innovation? How are the key sectors such as insurance and risk management adapting to the rapid pace of the evolving hazards and threats landscape and technological innovation? And what is the current and future role of GEOINT in disaster insurance and risk management?[2]

Convergence of GEOINT with Insurance and Risk Management

GEOINT has emerged as a uniquely valuable tool for public safety, homeland security, disaster management, and risk reduction. It is helping our communities to become more fully protected, connected, and aware as well as economically secure. GEOINT is at the center of a growing convergence between technologies such GIS, remote sensing, artificial intelligence (AI), IoT, high-performance computing, platforms such as small sats, drones, in situ sensors, and smart devices, and techniques in data science, digital forensics, sentiment analysis, forecasting, and predictive analytics. The new GEOINT economy is providing a means for better allocating our scarce resources to achieve optimal advantage and address some of our most pressing global, national, and regional challenges.

The insurance and risk management sectors are playing a more prominent and important role in managing disaster risks. GEOINT is underpinning much of the new innovation and expansion that is occurring in these sectors (commonly referred to as InsurTech). InsurTech refers to the use of technology innovations to disrupt and transform the current insurance industry that is heavily entrenched in traditional indemnity insurance models. As the needs of consumers and suppliers in the insurance and risk markets are becoming more complex, GEOINT is becoming more ubiquitous, responsive, easier to access, and useful. This is allowing InsurTech the ability to optimize traditional indemnity offerings (more refined actuarial tables and risk profiles, automated claims processing) and to introduce new products and services, such as customized policies (endorsements for earthquake, flood, etc.), event-driven coverage (parametric insurance), dynamic pricing based on observed behavior (pay-by-the-mile auto insurance), and micro-indemnity insurance for recreational activities (i.e., drones, skydiving, etc.).

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Possibilities Are Limitless

What becomes evident from analyzing current and emerging trends in insurance and risk management is that much of the innovation occurring in InsurTech is not possible or feasible without GEOINT. GEOINT is transforming insurance and risk management across the public and private sectors, enabling coverage for assets previously thought of as uninsurable, delivering solutions for closing the protection gap, and driving economic growth and expansion of the GEOINT, insurance, and risk management sectors. GEOINT is powering the evolution of parametric insurance and catastrophic risk models which are among the most significant developments in risk management and insurance over the last 30 years. Aided by increased computational power and high-quality, high-resolution, and timely GEOINT datasets, probabilistic simulations from these models are allowing stakeholders to quantify exposures, measure risk potential, and manage financial consequences. These models are becoming critical tools in combating the threat of natural and human-made catastrophes and are powering a revolution in the risk management and insurance industries.

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