Breakthrough insights combined with data improves the underwriting process for cybersecurity policies

In a move designed to predict the risk of cyber-attacks on businesses, Experian unveiled its new cybersecurity risk model – a groundbreaking innovation that combines Experian’s robust collection of financial and business data to optimize the insurance industry’s cyber underwriting solutions. This new cybersecurity risk model could improve the underwriting process for cybersecurity policies and identify areas where businesses may be vulnerable.

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As a leading provider of business data and analytical insights, Experian maintains credit information on approximately 25 million active U.S. businesses and provides comprehensive, third party-verified information on nearly 100 percent of all U.S. companies. Experian’s cybersecurity risk model utilizes proprietary business data and algorithms to identify the connections between companies, employees, dark web behaviors, and data breaches. This solution scores the likelihood that a specific business is at an elevated risk of a cyber event and benchmarks a business against its industry peers. Experian’s cybersecurity risk model uses innovations in cybersecurity to improve efficiency across all stages of the insurance life cycle to mitigate risk.

“Cyber-attacks are costly to businesses and consumers alike, with damages expected to cost in excess of $6 trillion annually.¹ This exposure to cyber insurers is growing and we’re committed to helping them,” said Brian Bond, senior vice president of product, marketing, and strategy for Experian’s Business Information Services. “The data and insights from our new cybersecurity risk model allows insurance underwriters to have a more holistic picture of businesses’ cyber risk so they can write more accurate policies that ultimately mitigate risk. We also envision a broader application of this solution across industries in the future.”

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Developed by Experian DataLabs, the company’s research and development group,  Experian’s cybersecurity risk model uses machine learning to bring together data elements, build linkages, and construct a model that may more effectively predict cyber risk based on many critical factors including the cyber exposure of employees.

“The market is dependent on breakthrough experimentation to continue powering opportunities for problems that previously never existed,” said Christer Dichiara, senior vice president of Experian DataLabs, North America. “Our cybersecurity risk model is a prime example of how Experian is committed to being early adopters of any technology that might improve the power of data for our clients and consumers.”

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