FAIRCON21
Case Study - Accelerating FAIR Analyses by 10x with Industry Data
Ben Gowan, Data Science Manager, RiskLens
Justin Theriot, Sr. Data Scientist, RiskLens
FAIR Institute members can watch the video of this FAIRCON21 session in the LINK member community. Not a member yet? Join the FAIR Institute now, then sign up for LINK.
Justin and Ben explained that data for analysis should be
Justin gave a deeper look at data refinement at RiskLens, showing how raw data from thousands of loss events gets filtered by industry, geography, data type, threat actors, threat type and other categories. As an example of the subtle differences among industries, for instance, Justin noted that
(Justin presented an extensive white paper on RiskLens data science research at the 2021 SIRACon. RiskLens incorporates the research in its product as data helpers, loss tables and contact packs including industry-specific data and scenarios ready for analysis.)
This sophisticated approach, “enables your reporting and scenario scoping to be driven by precise industry estimates that are not just generic assumptions,” Ben added.
Ben and Justin called the practical application of prepared industry data the “flywheel effect.” As Ben said, “a beneficial and reinforcing process is called into place” as FAIR analysts “10x not just speed but the amount of analyses that can be run and the robustness and utility of them.”
The wheel starts spinning from a standing start with industry data that augments or substitutes for in-house data as an organization begins FAIR analysis. A quick win follows, using data plus the RiskLens Rapid Risk Assessment capability to identify top risks, then on through the cycle to advanced, more automated workflows as the organization builds its stores of scenarios and data on the RiskLens platform. “What used to take a week now takes an hour,” Ben said.
Get more detail – see all of the RiskLens presentation at FAIRCON21: Case Study - Accelerating FAIR Analyses by 10x with Industry Data (FAIR Institute membership required).