Ask Karisse anything: Refund fraud, negative lists, and fraud team structure
In this episode, I’m answering listener questions on a mix of topics that fraud teams deal with all the time, even if they do not always get discussed in the same conversation. We get into refund fraud questions, universal negative lists, and fraud team structure, which might sound like separate issues at first glance. But they really are not. They all connect back to how teams make decisions, how they share information, and how they build processes that actually hold up under pressure.
I also start with a few stories from a recent Fraud Fighters Happy Hour hosted by Fraudology. And yes, that includes banana fraud. Because apparently that needed to be a thing. But those stories are part of the point. Fraud is rarely just about one tactic or one bad actor. It is usually about patterns, weak spots, and the small signals that tell you where a business is exposed.
That is why this episode matters. If you work in fraud prevention, operations, trust and safety, or risk, you already know that good outcomes do not come from isolated answers. They come from understanding how fraud team organization, reporting structure, and day-to-day decisioning all work together. Right. That is where things either hold up or start to unravel.
Here is what that framework means in practice:
- Fraud team structure influences how quickly issues get escalated and resolved
- Refund fraud questions often reveal bigger gaps in policy, operations, or ownership
- Negative lists only work well when the team using them has strong judgment and clear governance
- Fraud reporting structure can shape how seriously fraud risk is understood across the business
What you’ll hear in this episode:
- My answers to listener questions about fraud team structure and fraud operations setup
- A practical discussion of refund fraud questions and why they are often more complicated than they sound
- How universal negative lists can help, where they can fail, and what teams need to think through
- A look at fraud happy hour stories, including a memorable example of banana fraud
- Why fraud team best practices usually come back to clarity, ownership, and communication
You should listen to this episode if you:
- Are thinking through fraud team structure or fraud team organization at your company
- Want practical answers to ecommerce fraud questions from an operator’s perspective
- Need a better handle on fraud reporting structure and fraud leadership questions
- Are evaluating whether negative lists fit your fraud prevention program
- Care about online fraud education that is grounded in real operational experience
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Episode notes & key takeaways
Why fraud team structure affects more than org charts
Let’s break this down.
A lot of people hear the phrase fraud team structure and think this is mainly about reporting lines. Who reports to whom. Whether fraud sits under payments, operations, risk, customer experience, or finance. That matters, of course. But the bigger issue is how that structure affects speed, visibility, and accountability.
Because fraud does not happen neatly inside one department.
If your team sees refund abuse, promo abuse, account takeover, or merchant disputes in real time, but has no clear path to influence policy or product decisions, that is a problem. If fraud is buried too far away from decision-makers, the business often ends up reacting late. And if ownership is fuzzy, everyone notices the problem and nobody really owns the fix.
That is where fraud team organization becomes operational, not theoretical.
Here is what I want teams to think about:
- A strong fraud team structure creates faster escalation paths for emerging issues
- Fraud reporting structure should give teams access to decision-makers, not just dashboards
- Merchant fraud structure often needs cross-functional input from operations, support, product, and payments
- Fraud leadership questions usually point back to authority, alignment, and clear ownership
How refund fraud questions reveal bigger operational gaps
Refund fraud is one of those topics that sounds straightforward until you actually start pulling on the thread.
A listener question about refund fraud questions might sound like it is only about chargebacks, return abuse, friendly fraud, or customer claims. But when you look closer, it usually turns into a much bigger conversation about policy design, customer experience, training, tooling, and who gets to make exceptions.
And that matters.
Because a weak refund process is not just a loss issue. It is a consistency issue. A training issue. A signal-sharing issue. Teams can end up rewarding abusive behavior without realizing it, especially when support, fraud, and finance are all working from slightly different assumptions.
I’ve seen this playbook before.
The companies that handle refund abuse best usually are not the ones with the most complicated policy language. They are the ones with the clearest internal rules, the strongest feedback loops, and the discipline to track patterns instead of treating every case like a one-off.
- Refund fraud questions often expose confusion around thresholds, exceptions, and ownership
- Fraud prevention Q\&A gets more useful when teams connect case-level stories to broader patterns
- Ecommerce fraud questions around refunds should include both abuse risk and customer experience tradeoffs
- Common fraud topics like refunds become much easier to manage when teams document and review edge cases
What universal negative lists can and cannot do
Negative lists are one of those tools that sound simple. And sometimes they are. But only up to a point.
In simple terms, a negative list is a shared record of information linked to past abuse. That could be email addresses, devices, cards, shipping details, or other signals that tell your team, “We’ve seen this before, and it did not end well.” The appeal is obvious. If you can identify repeat abuse faster, you can stop wasting time rediscovering the same bad patterns.
But when people ask about universal negative lists, the real question is usually this: how much should we trust them?
That is where things get interesting.
A negative list can absolutely help. It can speed up review. It can flag linked behavior. It can support analysts who are trying to make fast, consistent calls. But it is not magic. If the inputs are messy, the ownership is unclear, or the context is missing, the list itself can become part of the problem.
Right.
Because a bad list does not just miss fraud. It can create avoidable friction for legitimate users too.
- Negative lists work best when teams understand why an entity was added, not just that it was added
- Fraud team best practices should include governance, review standards, and expiration logic for shared lists
- Fraud operations setup matters because list quality depends on disciplined input and maintenance
- Online fraud education should include the limits of shared negative signals, not just the benefits
Why the stories matter more than they seem
I start this episode with stories from Fraud Fighters Happy Hour for a reason. On the surface, they are entertaining. Banana fraud definitely earns that category. But those stories are not just there for fun. They are there because fraud operators learn a lot from the weird stuff.
Honestly, some of the most useful fraud lessons come from the examples that sound too odd to be real. Those are the cases that force teams to ask better questions. How did someone think to exploit that? What weak process made that possible? Why did nobody notice sooner? And what looks silly on the surface but points to a bigger pattern underneath?
That is why I like using stories in fraud prevention Q\&A.
They help make the mechanics visible. They help teams remember the lesson. And they remind us that fraud is rarely static. Attackers adapt. Businesses improvise. Controls age. And sometimes the strangest case is the one that tells you exactly where your blind spot is.
The big takeaway from this episode is pretty simple. Fraud team structure, refund fraud, and negative lists might look like separate topics, but they all come back to the same thing: whether your organization is built to recognize patterns and act on them. Good teams do not just answer the question in front of them. They use the question to find the process behind it. That is usually where the real work is.
