Fraud prevention software: How fraud fighters can build products that solve real problems
Guest: Patrick Chen
Today I’m talking about fraud prevention software from a very different angle than most people do. Usually when we talk about fraud tools, the conversation starts with what vendors are selling, what controls are missing, or which platform is supposed to solve the latest problem. But in this episode, I wanted to talk about something more interesting than that. What happens when fraud fighters themselves start building the products they always wished they had?
That is exactly why I invited Patrick Chen to join me.
Patrick has spent years solving complex risk problems with technology at some of the largest online companies and platforms out there, and now he is the co-founder of Spec. We talk about the problem space across ecommerce and financial services, why so many current tools are not enough for where fraud is headed next, and what it looks like to build fraud prevention software with more flexibility, more raw data, and a lot more room for practitioners to shape the solution.
And honestly, this conversation matters a lot.
Because if you work in fraud, you already know there are real gaps between the problems teams face every day and the products available to solve them. Refund fraud. Policy abuse prevention. Risk decisioning. Identity verification. Transaction monitoring. The list goes on. And too often, fraud teams are forced to adapt to rigid tools instead of being able to design workflows around the reality of the abuse.
That is the bigger theme here.
This episode is really about the future of fraud prevention software, but it is also about something more personal for people in this industry. It is about intellectual property. It is about practitioner insight. And it is about the idea that the people closest to the problems might also be the right people to build the next generation of solutions.
Here is what that means in practice:
- Fraud prevention software gets better when it is shaped by people who understand the abuse firsthand
- Fraud fighters often know exactly where existing fraud detection software falls short, especially around workflow flexibility and visibility
- Payment fraud prevention and ecommerce fraud prevention require tools that can adapt to how abuse actually changes
- The future of a fraud management platform may depend on giving practitioners more control over what gets built
What you’ll hear in this episode:
- Why Patrick Chen believes fraud prevention software needs to evolve beyond the tools that got the industry this far
- How raw data, flexibility, and infrastructure can improve risk decisioning and fraud workflows
- Why fraud fighters are uniquely positioned to design products for policy abuse prevention, refund fraud, and other real problems
- How a marketplace model could create new opportunities for practitioners to build and benefit from their own ideas
- Why I was excited to share the first independently designed refund fraud module built for the Spec marketplace
You should listen to this episode if you:
- Work in fraud, risk, payments, trust and safety, or product and want a better view of where fraud prevention software is headed
- Have felt frustrated by rigid fraud detection software that does not match the real problem you are trying to solve
- Care about ecommerce fraud prevention, payment fraud prevention, and fraud management platform design
- Want to think more strategically about transaction monitoring, behavioral analytics, device fingerprinting, and identity verification
- Have ever thought fraud fighters should have more ownership in the products built for this industry
If you liked this episode, be sure to subscribe and review the podcast on iTunes, Spotify, YouTube, or wherever you listen to podcasts. It really helps with getting the word out.
Episode notes & key takeaways
Why fraud prevention software needs a new approach
Let’s break this down.
One of the clearest themes in this conversation is that the fraud tools that helped the industry get to this point may not be enough to take it through the next decade. That is not because those tools were useless. A lot of them were incredibly important. It is because fraud keeps changing, business models keep changing, and the environments teams are trying to protect are getting more complex.
That is the problem.
A lot of fraud prevention software still expects teams to adapt their work to the product, instead of helping the product adapt to the way fraud actually behaves. And when that happens, practitioners end up working around the tool instead of through it. They build spreadsheets. They create side processes. They ask engineering for one more exception. They lose time trying to get visibility into something they should have been able to see already.
I have seen this playbook before.
The issue is not just detection. It is flexibility. It is workflow. It is whether teams can actually investigate, act, and improve fast enough when the risk pattern shifts. That is why this conversation with Patrick matters. It is not just about a new product. It is about a different philosophy of how fraud prevention software should work in the first place.
A few practical takeaways:
- Fraud prevention software needs to support how fraud teams work, not force them into rigid workflows
- Fraud detection software is less effective when teams have to build manual workarounds to close visibility gaps
- Risk decisioning improves when practitioners can shape logic around real abuse patterns
- A modern fraud management platform should provide flexibility, transparency, and usable raw data
Why practitioners are often the best people to build fraud products
This is where things get especially interesting.
A lot of industries assume product ideas should come from founders, engineers, or executives first, and then get validated by practitioners later. But in fraud, some of the best product ideas are already sitting inside the teams doing the work every day. They know where investigations stall. They know where transaction monitoring falls apart. They know which signals matter and which workflows waste time.
And that matters.
Because when fraud fighters build products, they tend to start with a real operational pain point instead of a broad category promise. They are not guessing what the problem might be. They are usually trying to solve something they have already dealt with repeatedly.
That is a much stronger starting point.
Patrick talks about this really well through the vision behind Spec, especially the idea that fraud fighters should have more opportunity to develop and benefit from intellectual property tied to the problems they understand best. Honestly, I think that is one of the most compelling parts of the whole conversation.
Here is what stands out:
- Fraud fighters often have product insight that comes directly from solving real operational problems
- Fraud prevention software built by practitioners is more likely to reflect actual risk workflows
- Product ideas around policy abuse prevention, chargeback prevention, and account takeover protection often come from lived experience
- The people closest to the fraud problem are often the people best equipped to define what a better solution looks like
Why flexibility and raw data matter so much in risk infrastructure
Here’s what’s actually happening.
A lot of fraud teams do not just need a yes-or-no answer from a tool. They need context. They need to see the underlying data, understand why a decision was made, and build logic that reflects the nuances of their own environment. That is especially true when you are dealing with payment fraud prevention, identity verification, behavioral analytics, or transaction monitoring across very different types of businesses.
That is why infrastructure matters so much.
Patrick talks about wanting to create a platform with the raw data and flexibility teams wish they had when they were building risk infrastructure inside large online marketplaces. And honestly, that makes sense. Because if you have ever worked in fraud, you know how frustrating it is when the platform can technically detect something, but you still cannot get to the signal in a way that helps you act on it.
Right.
The point is not just to have more data. It is to have usable data. Data that helps teams build better workflows, better risk decisioning, and better outcomes without needing constant engineering rescue every time the pattern changes.
A few practical takeaways:
- Raw data matters because fraud teams need to understand the signal, not just the score
- Flexible infrastructure helps teams adjust more quickly when abuse patterns change
- Behavioral analytics and device fingerprinting are more useful when teams can interpret and operationalize the data well
- Transaction monitoring works better when the platform supports investigation and action, not just alert generation
Why refund fraud is a perfect example of the gap in the market
This is the part I was especially excited to talk about.
Refund fraud is one of those problems a lot of retailers know is real, but the market has not always given them enough transparency or control to deal with it well. Teams end up piecing together different sources of information, trying to prove patterns manually, or relying on tools that were never really designed for the type of policy abuse prevention they need.
That usually does not end well.
Because when a problem is visible but not well-supported by the existing product landscape, companies either underreact or build their own patchwork process. Neither is ideal. That is exactly why I shared the “secret” I had been keeping for a while about the first independently designed module on the Spec marketplace, focused on refund claims fraud.
And yes, I was excited about that for a reason.
Because it showed what this model can actually look like in practice. A real fraud problem. A practitioner-designed solution. More transparency for retailers. More autonomy. More usable workflows. That is a much more interesting direction than waiting for generic vendor roadmaps to maybe catch up later.
A few things worth paying attention to:
- Refund fraud is a strong example of where practitioner-designed software can solve a very specific market gap
- Policy abuse prevention requires more targeted workflows than many traditional tools provide
- Fraud prevention software should give retailers more transparency into the abuse patterns affecting them
- A marketplace approach can help bring niche but high-value fraud solutions to life faster
Why this conversation is really about ownership, not just tooling
Honestly, this is the bigger takeaway for me.
Yes, this episode is about fraud prevention software. Yes, it is about infrastructure, flexibility, and better products. But underneath all of that, it is also about ownership. Who gets to define the problems that matter. Who gets to build the solutions. And who benefits when a better idea comes out of real fraud experience.
That is the part that holds up.
Fraud fighters have spent years solving hard problems inside companies that often did not have enough time, enough engineering support, or enough appreciation for how much insight they were generating. So the idea that those same practitioners could now design marketable products, solve real industry problems, and directly benefit from their expertise is a pretty important shift.
And honestly, I think it is a healthy one.
The big takeaway from this episode is pretty straightforward. Fraud prevention software needs to become more flexible, more practitioner-driven, and more grounded in the real problems teams are trying to solve every day. Whether the issue is refund fraud, identity verification, chargeback prevention, transaction monitoring, or broader risk decisioning, the people closest to the work often have the clearest view of what better looks like. The industry should make a lot more room for that.
That is the part I would pay attention to.
