{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/ab0d7c6335fa48ef8302120016b37eb0\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/ab0d7c6335fa48ef8302120016b37eb0-02252eadb754b0d9.gif","duration":153.901,"title":"Introducing minFraud Risk Score Reasons 🚀","description":"Hi, I'm Miguel Atienza, Director of Product at MaxMind. Today, I introduce a new beta feature - minFraud Risk Score Reasons, providing understandable reasons for every score. Learn how to use this data for forensic investigations, post-incident analysis, pattern analysis over time, and to enhance your machine learning models. Your feedback on how this feature can assist you is highly appreciated!"}