{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/caf1cb928fb946e9bf77546f432f2214\" frameborder=\"0\" width=\"1670\" height=\"1252\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1252,"width":1670,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1252,"thumbnail_width":1670,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/caf1cb928fb946e9bf77546f432f2214-30047ec9ef4a3b28.gif","duration":191.893,"title":"AI product development - Vanta - 6 August 2026","description":"This Loom explains a new risk scoring option that breaks impact and likelihood into sub-factors for more granular evaluation. In the risk register settings, users can switch the scoring method to \"aggregate factors\" and choose how to combine factors using average, max, or sum. By default, it adds threat and vulnerability and lets users add and customize additional factors, including adjusting score ranges and whether a risk can be marked complete or fully approved even if a factor is missing. The heatmap updates to reflect non-integer scores when using average, and the AI agent can rescore existing risks to show the updated inherent risk calculations."}