In the context of Cyber insurance, technology and data is often used as shorthand to describe the rapid uptake and multifaceted use of external scanning methods by (re)insurers.
However, having access to data alone doesn’t guarantee success. Insurers must ensure they can rigorously translate this access into actionable insights across their business.
In 2022, Gallagher Re built a machine-learning model and combined it with historical claims to better understand which elements of external scanning would have been more predictive of claims at the point of underwriting. This paper presents the key insights from the study into the ability of the data to predict cyber claims, as well as to outline upcoming trends with insurers’ uptake of outside-in technology.
