Reinsurance News

CyberCube reveals Version 4.0 of Account Manager

29th November 2022 - Author: Kassandra Jimenez-Sanchez -

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Cyber risk analytics provider CyberCube, has released Version 4.0 of Account Manager, its software-as-a-service (SaaS) application for single risk re/insurance underwriters.

cybercube-logoThe latest version of Account Manager includes a variety of improvements including new data, usability enhancements, as well as scoring and signal refinements.

New financial quantification insights have also been introduced, the firm noted, leveraging CyberCube’s industry-leading catastrophe loss modelling for single-risk evaluation needs, to help carriers proactively assess their CAT exposure at the point of underwriting.

John Anderson, CyberCube’s Principal Product Manager for Account Manager, said: “For too long, insurance carriers have been relegated to using solutions designed for other purposes to inform their decisions.

“Account Manager Version 4.0 is the next gen solution underwriters have been demanding. It combines many elements including our world class CAT model, attritional and large loss model, proprietary security signals and data, in a highly intuitive and underwriter centric layout. This tool empowers underwriting teams, enabling meaningful guideline setting, and is prime for adoption.”

Mohammad Al Boni, CyberCube’s Lead Data Scientist, said: “We strive to continuously study and analyse our data and analytics, applying several advanced techniques such as multivariate statistical analysis and predictive forecasting. Account Manager Version 4.0 demonstrates the high degree of rigor we apply to ensure we are validating and producing cutting edge analytics.”

Earlier in the year, CyberCube also launched an updated version of Portfolio Manager (PM), a cyber risk modelling platform used by re/insurers and brokers. The new version focuses on deepened modelling of two key scenario classes, cloud outage and mass malware, and also includes general data updates on company firmographics, technical dependencies and security scores.