#62 - What you lose when you choose flexible fraud integrations

Last month I was on a call with a fintech CTO reviewing their fraud vendor integration plan.

"We're keeping it simple," he told me. "Just the core API. Status callbacks and label feedback? That's phase two, maybe Q3."

"And when's your go-live?" I asked.

"Next month."

I've heard this exact conversation at least fifty times in my career, both as a vendor and a consultant.

And I can tell you with near certainty: phase two never happens.

Here's why that matters more than you think.

Why vendors love flexibility

From a vendor's perspective, flexibility is expensive.

The more flexible your data schema, the harder it is to build sophisticated features on top of it.

Think about it: velocity checks require structured, predictable data. Geo-mismatch logic needs consistent address formats. ML models need clean, uniform feature sets.

When vendors let you "send whatever you want," they're basically saying: "We'll store it, but good luck getting any real value from it."

That fancy custom field you're passing? It's sitting in a database somewhere, but it's not feeding their risk scores. It's not part of their behavioral models. It's certainly not being monitored or optimized.

Want them to actually use that data? That requires custom development which is only really relevant to their top accounts. Are you one?

Now, to be fair to the vendors, they're playing the same game everyone else is. They just want deals to close faster. 

If reducing implementation timelines, or removing objections from engineering teams gets them there—great! It’s better than offering a discount, right?

So vendors genuinely see their platform’s flexibility as an edge: "You can send us any data you want! Custom fields! No problem!"

But what they don't emphasize (or sometimes realize) is that flexibility comes with performance trade-offs.

Why fintechs love flexibility

What’s not to love?

I get to “customize” my integration? Check.

I save on my most precious resource—time, better known as engineering days? Check.

See, I get it. Engineering resources are scarce. Your product roadmap is already packed. You need fraud protection yesterday, not in six months. All true.

So the risk team makes a deal: "Give us the bare minimum integration and we'll go live next month instead of next quarter."

Your CPTO is happy (are there still fintechs with this role separated?), the vendor is happy, your risk team is happy. Everyone signs off.

Except here's what nobody tells you: the quality of your integration directly determines your ROI.

Invest 20% of what you should? You'll get 20% of the results.

Let’s go one level deeper and explore this.

Flexibility’s true cost

Here’s one pattern I’ve been coming across for the better part of a decade, which is especially painful to watch:

Teams integrate the vendor's decision API: they send the event data, get back a score and rule hits. Based on that, they’ll make their approve/block decision.

And that's it.

What they skip:

Status callbacks - telling the vendor what actually happened. Did you approve it? Block it? Why? Was it your decision, the vendor's recommendation, or some other system?

Fraud labels - feeding back chargebacks, confirmed fraud, returns/refunds, etc.

Why do teams skip these? Because they usually require extra engineering work. These status updates are usually stored on different databases than your main events database.

For the engineering team, it’s not just about integrating three databases instead of one, it’s about joining the data correctly and avoiding attributing the wrong status to an event. That’s work.

So teams punt on it, or find a “cheap” way to send those separately (SFTP anyone?). Some even convince themselves they’ll get to it “next quarter”. 

Spoiler alert: they won't.

But why is that important? Without proper feedback loops, you're flying blind in two critical ways:

First, you can't diagnose your own system.

Sure, you can see your overall approval rate in your internal dashboards. But which specific fraud rule is sabotaging your conversion? Which model threshold is catching 60% false positives?

You won't know. Because the vendor can't tell you if they don't know which decisions were actually executed and which ones were overridden by your other systems.

Second, you're not training the vendor's models for your business.

Vendors train their ML models on feedback from across their client base. The more data they have from your business, the better they perform for you.

But if you're not sending fraud labels back? Their models stay generic. They don't learn your specific fraud patterns and they don't adapt to your evolving customer behavior.

Even worse: their models degrade faster for you than for other clients, because they're not getting the data they need to stay fresh.

I consistently see teams run with minimal integrations for 6-12 months, and then suddenly fraud spikes.

Now they want that perfectly tuned, custom-fit model they were promised in the sales deck, but their vendor doesn't have the data.

What can you do about it

Here's the hard truth: you cannot cheat on ROI.

The more you invest in integration, the better your results. Period.

But here's how to be smart about it:

Before you start integration, ask your vendor:

"What parts of this integration are marked 'optional' but would significantly improve performance if we included them?"

Get specifics. Status callbacks? Label feedback? Custom data enrichment? Real-time aggregations?

Then do the math. What's the ROI of each one?

You might find 1-2 items that are relatively cheap to implement but deliver outsized benefits.

If you're starting small, plan for scale:

It's totally fine to launch with a minimal integration for a pilot use case. Many times it's the smart move.

But document what you skipped and why. Map out which additional integration work you'll need before expanding to other flows and account for that engineering work.

Don't let "phase two" become "never."

The bottom line

Most fraud prevention failures aren't about picking the wrong vendor.

They're about implementing the right vendor wrong.

The gap between your sales demo and your production results? That gap is filled by the integration work you skipped to go live faster.

Have you seen this play out at your company? How did you balance integration costs with performance needs? Hit reply and let me know.

In the meantime, that’s all for this week.

See you next Saturday.

P.S. If you feel like you're running out of time and need some expert advice with getting your fraud strategy on track, here's how I can help you:

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