---
title: What’s New in Merchant Fraud, with Dajana G.
source_page: https://www.sardine.ai/media/the-saturday-fraud-strategist/episodes/merchant-fraud
canonical: https://www.sardine.ai/media/the-saturday-fraud-strategist/episodes/merchant-fraud
format: text/markdown
date: 2026-08-31T04:01:00.000Z
description: Merchant fraud is evolving fast. The realities of first party fraud, refund abuse, fraud as a service, and the vulnerabilities most merchants are missing…
---

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# What’s New in Merchant Fraud, with Dajana G.

**Published:** 2026-08-31T04:01:00.000Z

Merchant fraud is evolving fast. The realities of first party fraud, refund abuse, fraud as a service, and the vulnerabilities most merchants are missing…

I have been wanting to have this conversation for a while.
Dajana Gajic-Fisic has 26 years in merchant fraud. She started at Macy's in 2000, calling Visa and Mastercard in multiple languages to manually verify addresses at the point of sale. She has watched e-commerce fraud detection evolve from its earliest form through chip and pin migration, the explosion of online fraud, and now the AI era. She is currently VP of Fraud Strategy at The Wolfe Companies, working in the gift card space, which if you think has no fraud, you would be wrong.
What I liked most about this conversation is that Dajana is not someone who talks about merchant fraud from the sidelines. She fights it every day, including building out merchant fraud ring detection processes from scratch and figuring out how to detect merchant fraud attacks before they ever reach a payment page. That gives her a perspective on what is actually happening right now versus what the industry tends to talk about.
We covered a lot of ground. One thing I want to flag before you dive in. This is one of those conversations where we keep coming back to basics. Not because the threat landscape is simple. But because getting the basics right is actually how you handle whatever the threat landscape throws at you next. I thought that was worth saying up front.
What you’ll hear in this episode:
Why e-commerce fraud trends follow predictable patterns when the environment shifts, and what the chip and pin migration of 2015 tells us about AI today
How Dajana thinks about AI powered fraud attacks as a practitioner who is actively fighting them, not just theorizing about them
Why first party fraud and refund abuse in ecommerce may be the number one threat for merchants right now, not AI
How fraud as a service has made it possible to commit refund fraud without any technical knowledge, and what that means for merchant fraud teams
Why nearly fifty years of chargeback dispute rules regulation have not kept pace with the environment merchants are actually operating in
The cross-merchant fraud intelligence sharing story that could have prevented six months of losses at another merchant's business
Why end to end fraud monitoring is one of the most neglected basics in merchant fraud prevention strategies
Dajana's 360 approach to fraud operations, which separates the fraud process into four parts and maps how they feed each other
Why merchant fraud KPIs like chargeback rate alone tell an incomplete story and what to measure alongside them
How the lines between merchant fraud vs bank fraud are blurring at the identity and behavior layer
You should listen to this episode if you:
Work in e-commerce fraud detection and want a practitioner's view on what is actually changing versus what is being overhyped
Are dealing with first party fraud, friendly fraud chargebacks, or refund abuse and want to hear how someone with 26 years of merchant fraud experience thinks about it
Have felt frustrated that merchant fraud collaboration and intelligence sharing stops at your immediate network
Are building or restructuring your fraud team structure and want a framework that actually scales
Lead a merchant fraud team and are trying to figure out how to get upstream of the payment rather than catching fraud at checkout
Want to understand how merchant cyber security collaboration is evolving and what convergence actually looks like in practice on the merchant side
Are newer to the space and want a fraud fighter career development perspective from someone who grew up inside the industry
### Episode notes & key takeaways
AI fraud isn't new, it's a faster version of an old problem
One of the things I loved most about this conversation is how Dajana refused to let AI be treated as some unprecedented threat. She took me back to 2015, the chip-and-PIN shift, and honestly, I’d completely forgotten how disruptive that moment was until she brought it up. Fraud moved from brick-and-mortar to e-commerce almost overnight, and most fraud teams didn’t see it coming because information just didn’t travel the way it does now. Her point, and I think it’s the right one, is that the discipline itself doesn’t change. Only the speed and sophistication of the tools attacking it do.
Machine learning has quietly been part of fraud tooling for over a decade. It’s not new, we just didn’t call it AI back then.
The 2015 chip-and-PIN liability shift pushed fraud from brick-and-mortar onto ecommerce almost overnight, a disruption comparable to what AI threatens now.
I keep coming back to her framing here. Focus on what fraud actually looks like, not on chasing whatever technology happens to be behind it.
Why automated attacks are easier to catch, not harder
This is the part of the conversation that genuinely surprised me. I went in assuming AI-driven fraud would be harder to detect, and Dajana pushed back hard on that. Her argument is that automation actually makes an attack more obvious once you know what you're looking for, which is really the foundation of good merchant fraud ring detection. The real danger isn't invisibility, it's speed, how much you can lose in the window before you catch it.
Bot-driven and automated attacks show up as clear anomalies in traffic, even if they're difficult to trace back to a specific actor.
I walked away thinking the real risk isn’t that these attacks are undetectable. It’s how much damage happens before detection.
Her advice, and it’s simple but it works, is to look for anomalies first, then dig into the pattern once something looks off.
First-party misuse is the threat getting the least attention
Dajana named this as her biggest pain point of the last twelve months, and I think she’s right that it doesn’t get nearly enough airtime compared to AI. She pointed to social media normalizing chargebacks and false refund claims as an easy way to get free products, and honestly, that trend concerns me more.
MRC's global fraud report ranks refund and policy abuse as a top threat across nearly every region and merchant size.
What struck me is her estimate that fewer than half of merchants are even fully measuring the impact of this, which means the real number is probably much worse than what gets reported.
"Fraud as a service" groups filing refund claims on behalf of everyday people for a cut. That’s a genuinely new wrinkle on an old problem.
the case for industry-wide intelligence sharing
Dajana told a story here, an address manipulation fraud ring that took her over two days to detect. One of the most sophisticated attacks she’s dealt with, and she only caught it because of ethical alerts. She was able to share the information and help others in a small informal WhatsApp group of merchant peers. Meanwhile, another merchant didn’t catch the same attack for six months due to the lack of information sharing.
The attackers slowly altered shipping addressed and identity details in small increments specifically to avoid looking suspicious.
Once detected, sharing the pattern informally with a handful of merchant peers stopped the attack across multiple sites almost immediately, proof of what real fraud collaboration for merchants can actually accomplish.
Without that kind of informal information sharing, the same attack pattern can sit undetected at other companies for months, invisible to their own merchant fraud visibility efforts.
Fraud, compliance, and cybersecurity are converging
Dajana’s role has expanded well beyond traditional fraud prevention into risk more broadly, compliance, AML, the works. And she made a case I found pretty compelling. Fraud today is about identity and behavior, not isolated transactions.
The same bad actors are often responsible for fraud, compliance risk, and cybersecurity incidents, making merchant cyber security collaboration a natural next step rather than a nice-to-have.
Fraud signals on the merchant side and the financial institution side are starting to look remarkably similar, both centered on identity and behavior patterns, which is exactly where merchant fraud vs bank fraud starts to blur.
Even something as simple as sharing a BIN number tied to suspicious activity can help another merchant or bank get ahead of an attack without touching anyone’s private data.
The 360 approach: Monitor, identify, mitigate
I really liked how Dajana broke down her framework here. She structures fraud operations around four connected functions: prevention, investigation, reporting, and strategic planning. But she was clear these are functions to fulfill, not necessarily new teams to build from scratch. Really a blueprint for fraud team cross-functional collaboration done right.
Existing teams and reports across the organization, customer service, finance, BI, can often be repurposed to serve fraud prevention needs rather than duplicating effort.
Monthly or quarterly cross-functional planning meetings with marketing, product, and customer service help fraud teams anticipate business changes before they look like anomalies.
End to end fraud monitoring, catching risk signals well upstream of the transaction itself, gives fraud teams more opportunities to stop an attacker before financial loss occurs. This is upstream fraud detection in practice, not just theory.
Why approval rate matters as much as chargeback rate
Dajana closed with a critique I want every fraud leader listening to sit with. A low chargeback rate means nothing if you’re achieving it by blocking too many good customers.
A 0.01% chargeback rate paired with a 50% approval rate is not a success story, it's a sign of overcorrection.
Approval rate, false positive rate, and chargeback rate need to be evaluated together, not as independent metrics. This is really the starting point for any real merchant fraud benchmarking effort.
I think this is why good fraud prevention often becomes invisible to leadership. It’s working, so nobody notices. This makes having clear metrics to show your impact even more important.
### Final takeaway
If there’s one thing I hope sticks with you from this conversation, it’s that merchant fraud doesn’t get solved by chasing whatever threat is newest. It gets solved by getting your basics strong enough that the newest threat doesn’t rattle you.
Build real upstream fraud detection instead of waiting for an attacker to reach your payment page, take merchant fraud visibility seriously enough to actually measure first-party misuse instead of writing it off as a cost of doing business, and embrace fraud collaboration for merchants instead of treating every attack as a problem you are facing alone.
Dajana has spent 26 years learning this, including the corners of e-commerce and gift card fraud prevention that most people wrongly assume are low-risk. My honest hope for this episode is that it convinces at least one fraud leader listening to share information with a peer instead of sitting on it. That’s how we actually get ahead of this, instead of comparing war stories about it after the fact.
Resources & links
Not ready to stop the conversation about my, and hopefully your, favorite subject? Subscribe to The Saturday Fraud Strategist newsletter.
Connect with Dajana G. | LinkedIn
VP of Fraud Strategy, The Wolfe Companies
Founding Member, The House of Fraud
CEFI-Pacesetters 2019
2020 Merchant Team of the Year
Connect with Chen Zamir | LinkedIn
Host of The Saturday Fraud Strategist
Helping fintechs build smarter fraud defenses
Co-author of “The Fraud Fighter’s AI Playbook”