People were shocked.

Today? Honestly, not so much.

Now the threat is cheaper, faster, and harder to spot. Document checks can be bypassed. Selfies can be bypassed. Even 3D liveness checks, the ones that looked unbeatable not that long ago, can be bypassed.

Not a good look.

So in this episode, I want to talk about what fraud teams actually do next. Because if your KYC fraud prevention strategy still assumes that a clean KYC pass means a clean user, you are already behind.

The answer is layering. But not the lazy version where you just buy more KYC vendors and hope one of them saves you. I mean real multi-layer fraud defense: device intelligence, behavioral biometrics, behavioral signals, identity intelligence, device telemetry, post-signup fraud monitoring, and KYC vendor orchestration used in the right sequence.

Because a KYC check is a signal. It is not a verdict.

What you’ll hear in this episode:

• A breakdown of why KYC bypass prevention has become harder as fraud kits get cheaper and more specialized
• Why KYC fraud checks, document checks, selfies, and 3D liveness can no longer carry the whole fraud prevention strategy
• How device intelligence asks different questions than a KYC vendor
• Why behavioral signals and behavioral biometrics can expose what a document check misses
• How identity intelligence helps connect emails, phone numbers, addresses, and documentation into a more cohesive picture
• Why post-signup fraud monitoring and high-risk user monitoring matter after account opening
• How step-up verification can add friction only when the risk actually justifies it
• Why KYC vendor orchestration can be useful for a small, high-risk segment
• How fraudster ROI changes when fraud teams stop relying on a single point of failure

A practical conversation about layered fraud defense, operational blind spots, and why modern KYC fraud detection depends on connecting signals instead of trusting one onboarding result.

Who should listen:

• Fraud leaders and fraud operators
• Risk and compliance teams
• FinTech teams managing onboarding and account opening fraud
• Trust and safety professionals
• Identity verification and KYC teams
• Teams evaluating behavioral biometrics, device intelligence, and synthetic identity detection

Basically, if your fraud stack still depends heavily on one KYC vendor, or if device telemetry is collected but barely used, or if onboarding and transaction monitoring teams are still operating in silos this episode is probably going to feel uncomfortably familiar.

Honestly, that stack fails every time eventually.

Years ago, Matt Vega interviewed me on one of my first podcast appearances. And now, somehow, here we are, roles reversed, with Matt joining me for the first full interview episode of The Saturday Fraud Strategist.

Honestly, not a bad way to start.

In this episode, Matt and I talk about what it actually takes to build real-time fraud prevention from zero. Not the polished vendor version. The real version. The one with hiring decisions, messy processes, fragile fraud prevention tech stacks, disconnected vendors, and systems that look impressive right up until they break.

Not a good look.

While real-time fraud detection sounds like a technology problem, the conversation goes deeper. We talk about people, process, product, real-time fraud monitoring, tactical friction, fraud prevention guardrails, AI readiness, and why teams need to move upstream before the money is gone.

Because once the payment moves, especially in real-time transaction monitoring or real-time payment environments, you are not preventing fraud anymore. You are documenting the damage.

What you’ll hear in this episode:

• A breakdown of Matt Vega’s people, process, and product framework for real-time fraud prevention
• A practical discussion of how to build a fraud prevention strategy from zero
• Insight into hiring for curiosity, trust, flexibility, and actual problem-solving ability
• A conversation about reactive vs proactive fraud prevention in real-time payment environments
• A focused look at upstream fraud detection, tactical friction, and why friction done right can increase trust
• Practical considerations for building a fraud prevention tech stack where vendors, signals, and workflows actually communicate
• A discussion of AI fraud prevention, machine learning fraud detection, and agentic AI in fraud prevention

Listeners can expect a conversation that moves from theory to operating reality, and from operating reality to practical decisions fraud teams can actually use.

Who should listen:

• Fraud leaders and fraud professionals
• Risk, compliance, and cybersecurity teams
• Fintech, banking, and payments teams
• Product leaders building real-time payment experiences
• Fraud operations teams moving from manual review to automation
• Founders, operators, and executives building fraud prevention programs from scratch

Anyone evaluating fraud detection rules, behavioral biometrics, device intelligence, KYC fraud prevention, account takeover prevention, or the best fraud prevention tools for their stack.

The discussion is designed for professionals who are committed not only to detecting fraud, but to building systems that can scale without becoming fragile.

Okay. Apparently, the narrative was that rules are better than AI.

Honestly, I get why it looked that way. I talk about rules vs AI in fraud prevention quite a bit. But that is not really the point.

The point is control.

AI fraud prevention, fraud prevention AI, AI fraud detection, machine learning fraud prevention, all of it sounds great until the person responsible for money movement and customer acquisition has to approve the change. Then accuracy is not the only thing that matters. Trust matters. Explainability matters. Strategy visibility matters. And if leaders do not feel in control, they will choose worse fraud tools.

Not because they are irrational.

Because breaking the business is, technically speaking, not a good look.

What you will hear in this episode:

• A breakdown of why the “rules vs AI in fraud prevention” debate misses the bigger issue
• Why leaders often choose fraud detection rules over stronger AI fraud tools
• How fraud risk management changes when the process touches money movement and customer acquisition
• Why fraud decisioning depends on trust, not just model accuracy
• What fraud AI tools often get wrong about explainability
• How chargeback rate optimization can become more useful when users can compare low, medium, and high-risk strategies
• Why AI trust in fraud prevention depends on clear KPIs, plain answers, and visible tradeoffs
• Listeners can expect a conversation that moves from “which tool performs better?” to the more uncomfortable question: who actually feels safe enough to make the decision?

Who should listen:

• Fraud leaders and fraud operators
• Risk and compliance teams
• Product teams building fraud AI tools
• Financial institution leaders evaluating AI fraud prevention
• Fraud technology vendors and solution architects
• Anyone involved in fraud decisioning, chargeback rate optimization, or machine learning fraud prevention

Basically, if you have ever looked at a model and thought, “The performance is better, so why won’t they use it?” this one is for you.

It’s been six months since I joined Sardine. And I figured it makes sense to explain how I got here, because honestly, the decision wasn’t hard, but it wasn’t simple either.

This isn’t just about changing roles. It’s about moving from fraud prevention consulting into something broader, where I can connect content, product, and strategy in a way that actually helps fraud fighters do their job better.

And along the way, it raises a bigger question: what does an effective fraud prevention strategy actually look like when you’ve been on the practitioner's side for long enough?

What you will hear in this episode:

• A personal breakdown of why I moved from solo consulting back into a team
• Why “freedom” in consulting isn’t always what it seems
• How I think about fraud prevention strategy after years in the field
• What made Sardine stand out as a fraud prevention platform
• Why practitioner-led content matters more than ever
• How fraud prevention solutions should actually be built and evaluated

Who should listen:

• Fraud fighters working in fintech fraud prevention and enterprise fraud prevention
• Risk, compliance, and product teams evaluating fraud prevention solutions
• Professionals working in fraud prevention consulting
• Anyone thinking about the gap between vendor promises and real-world fraud operations
• Anyone trying to build or choose a fraud prevention platform that actually works

If you’ve ever asked yourself whether the tools you’re using really solve your problems, this one will probably resonate.

Someone used my email to create a profile on Coffee Meets Bagel. When the platform froze the account, the scammers opened another one. Same email. Same details. Instantly. By the third account, customer support still hadn't replied.

What starts as fake dating profiles doesn't stay there. They become romance scams. Then a loss your FI absorbs while the dating platform moves on with no accountability for the identity verification failure and no skin in the game.

Dating platforms have no chargebacks, no regulatory pressure, and no reason to fix the lack of account takeover detection. So who actually bears the cost, and why are we still waiting for them to care about APP fraud prevention?

What this episode covers

• How dating app identity theft becomes a gateway to romance scams and APP fraud
• Why dating platforms have no structural incentive to prevent account misuse
• What the upstream fraud trail looks like, and who ends up paying downstream

Who should listen

• Fraud ops teams at FIs and fintechs
• Teams working with identity verification systems
• Risk and compliance professionals tracking APP fraud vectors
• Anyone watching romance scam trends

Chen Zamir goes deep on fraud strategy at the intersection of business growth, customer experience, and risk management. No news digests, no vendor pitches, no recycled content. Just real talk for fraud professionals, product managers, and executives who want to think sharper about risk.

New episodes every Saturday.

Subscribe and join a community that's already changing how the industry thinks about fraud. Got a question or topic you want covered? Drop a comment or reach out directly.

Chen reads everything.