This week host Cameron D’Ambrosi host of State of Identity is joined by Gregory Asmolov, PhD., Co-Founder and Head of R&D at PitchMe, and Dina Bayasanova, PhD., Co-Founder & CEO of PitchMe to discuss the changes we’re seeing in the shift towards skills-based future of work (even for roles that don’t yet exist). Listen for how advances in HR technologies can help companies facilitate change and identify the ‘hidden’ talent within an organization.
What is a synthetic identity and who is doing it? On this State of Identity podcast, host Cameron D’Ambrosi and Kurt Weiss, Vice President of Enterprise Sales at Ekata discuss synthetic identity and the levels of sophistication. Can it be solved, and what are the keys to solving the problem?
On this week’s State of Identity podcast, host, Cameron D’Ambrosi sits down with Aaron Goldsmid, VP of Product for Twilio Communications Platform. They discuss verified identity as a primitive of the internet and the digital “anti-fragile identity” becoming better than in real life.
How can document fraud detection help fight identity fraud? On this State of Identity podcast, host Cameron D’Ambrosi discusses building AI and machine learning models for a fraud vector with Inscribe Co-Founder and CTO, Conor Burke. This duo breaks down the challenges banks and fintechs face in combatting fraud.
Understanding where your user is physically located is critical for compliance, trust and safety, and anti-fraud applications. On this week’s State of Identity podcast, host Cameron D’Ambrosi welcomes Isabella Edmonds, Head of Government Relations at Geocomply. They discuss the shifting regulatory and industry landscape, and the role geographic signals should play within a digital identity tech stack.
What is the difference between alternative and behavioral data; how widely are they used in fintech and other verticals today? On this week’s State of Identity podcast, host Cameron D’Ambrosi and Michele Tucci, Chief Strategy Officer & MD of Americas at credolab discuss how alternative data with AI & ML algorithms can promote greater financial inclusion and improve lenders’ profitability by better understanding their customers.