In this episode, I'm sitting down with Tal Yeshanov. Someone I've known for a very long time in this industry, and one of the sharpest risk leaders I know. Tal's path into fraud started almost by accident at Google and YouTube. Then took her through building fraud programs at Eventbrite, before its IPO, and Uber during its earliest hockey-stick growth years. Tal has spent her career building holistic fraud detection systems from scratch, in industries where there was no playbook to follow.

For years, fraud teams operated off a snapshot. Device at checkout. IP at checkout. Did the payment information match? Tal walks through why that single-moment view is no longer enough. And why the shift toward an orchestration platform, one that pulls in customer journey risk signals from the moment a user lands on your site rather than just the moment they transact, is where modern fraud programs are actually headed.

The deeper theme of this episode is what happens when you stop treating fraud detection as a scoring exercise, and start treating it as a full picture. Tal shares a personal story about a rule she built early in her career that was, on paper, flawless. It caught the exact triangulation fraud pattern it was designed for. It also caught a company executive, because his girlfriend used his credit card in a different city. That's false positive reduction in fraud detection in its most human form, and it's a direct argument for upstream fraud prevention data collection: pulling in more signals earlier in the journey instead of adding more rules at the transaction point.

What you'll hear in this episode:

• How Tal moved from Google and YouTube into building fraud programs at Eventbrite and Uber with no existing playbook to follow.
• Why holistic fraud detection means tracking customer journey risk signals from first visit to transaction, not just a snapshot at checkout.
• How an orchestration platform unifies device, IP, email, and behavioral data that used to live in separate point solutions.
• A real story about false positive reduction in fraud detection, including a rule that was technically perfect and still failed a legitimate customer.
• How the same holistic approach extends to account takeover detection, including typing cadence, autofill behavior, and device history.
• Why domain expertise vs AI in fraud isn't a competition, and how agentic AI is being used right now to query databases, support customer service teams, and triage escalations.
• A candid conversation about AI replacing fraud jobs, including a real example of a company that prematurely laid off its fraud leadership.
• Why fraud team tribal knowledge doesn't transfer to an AI model, and what companies risk losing when it walks out the door.
• Tal's fraud leadership philosophy, built on transparency and empathy, and why it creates teams that stay in touch for years.
• The ongoing industry shift from risk team vs fraud team naming, and why more companies are choosing the broader term.

You should listen to this episode if you:

• Work in fraud detection, risk operations, account security, or trust and safety.
• Are evaluating an orchestration platform or trying to move your fraud program beyond point-in-time scoring.
• Want a practical, non-hypothetical look at where agentic AI actually fits in fraud operations today.
• Are a fraud leader worried about AI replacing fraud jobs on your team, or trying to make the case for why domain expertise still matters.
• Care about fraud leadership philosophy and want to build a team that stays loyal and stays sharp.