#44 - Why PSPs are getting fraud VAS wrong

Many of the prospect calls I have are with PSPs wondering if I can help them build fraud prevention technology.

Usually, though, they don’t want to build it for their own internal risk controls.

Instead, they want to offer it as a Value Added Service (VAS) product to their clients–merchants, fintechs, etc.

As someone who built and ran a fraud vendor that partnered with PSPs, I believe that it makes strategic sense.

Offering VAS products is one of the main ways PSPs can differentiate in today’s highly commoditized market.

It helps win deals, increases product stickiness, and creates new revenue channels.

What does not make sense is how most PSPs are thinking about it.

Let’s talk about it.

Fraud VAS - build or buy?

The most common mistake I see PSPs make is trying to build this on their own.

I get why. On the surface, it looks like a straightforward task: “All we need is an API (check), payment data (check), and what is left is to train an ML model for fraud detection.”

Nothing can be further from the truth.

The first reason is that fraud detection technology seems quite simplistic from the outside.

But in reality, the “simple task” of training an ML model becomes a black hole for resources in the effort to showcase competitive performance.

It’s not about configuring the algorithm. It’s about acquiring 3rd-party data sources, developing velocity checks, dealing with false positives and dirty fraud labels, managing different client segments and regions, and the list goes on.

This isn’t only about the required effort to launch it.

Fraudsters adapt, and so do behavioral patterns. The cost of maintaining fraud detection models over time is bigger than what many of the uninitiated suspect.

Side note: You can ​read more here about general build vs. buy decisions in fraud tech.​

However, there’s a much bigger reason why building fraud tech is not the sensible strategy–VAS is a product, not technology.

Here’s the thing:

Let’s assume for a second you’ve developed a fantastic ML model for fraud detection. You are now able to return fraud scores in your payments API.

So what?

Do clients now know how to use it? Which score cutoff to choose? Can they better analyze their fraud patterns? Review their chargebacks? Investigate suspicious payments? Block that pesky address that keeps requesting refunds?

The answer to all of the above is still “no”.

Which clients buy fraud services from PSPs?

Let’s take a step back for a moment.

If we’re developing a product, we need to consider–what do clients want?

But in order to answer this question, we also need to consider who these clients are. Specifically, which clients would buy fraud prevention services from their PSP and not directly from a vendor?

To answer this question, we can review the distinct pros and cons for buying fraud services directly from your PSP:

Pros:

• I already know and trust my PSP

• Minimal engineering resources required, if at all

• One vendor to manage both payments and fraud

Cons (by not working directly with a fraud vendor):

• PSPs offer less customization

• PSPs cover only payment flows (no onboarding, login, etc.)

• PSPs likely have leaner APIs that skip many relevant data points

• PSPs have fewer dedicated resources (=performance not optimized)

• If I’m working with multiple PSPs (payment methods, regions, load-balancing), my fraud prevention would be fragmented as well

What can we learn from this list? Mainly that there are several distinct groups that would rather buy fraud services from their PSP than directly from a vendor.

These are:

• Small merchants: Cannot afford the resources, and/or cannot deal with the operational overhead.

• Low-fraud merchants: Do not require best-in-class technology and would deprioritize fraud management investments in general.

• High-risk merchants: Funnily enough, high-risk verticals (gaming/gambling, adult, CBD, etc.) are also a prime target. Often they choose to work in parallel with both direct vendors and their PSPs as they are less margin-sensitive and put importance on performance optimization.

What do these clients need?

What this teaches us is that the type of clients that choose to work with their PSP on fraud prevention does not have it as a top priority (aside for high-risk merchants).

In turn, this also hints that they don’t spend a lot internally.

They don’t have a large fraud team, if at all.

They would probably love it if someone else could take care of it for them. Someone just like you.

And here lies the crux:

More often than not, clients who work with their PSPs on fraud prevention need professional services as much–if not more–as they need the tools and technology.

Instead of building amazing UI and UX features, PSPs are often asked to support their clients with their specific fraud management needs.

This can be as simple as recommending the right model cutoff score, or as comprehensive as analyzing emerging fraud patterns and recommending remediation steps.

The reason I believe most PSPs miss this crucial point is that these needs are not necessarily clear to the merchants themselves.

Often they encounter fraud for the first time, think AI is the solution (like it is for all humanity’s problems), and expect that by just receiving a score fraud would solve itself.

In essence, we have two non-expert parties that believe they are aligned on expectations when in reality they are both wrong.

To conclude…

Does that mean that PSPs should never build their own fraud VAS products?

No. Evidently both Stripe and Adyen are doing really well on that front. The question is whether you can afford to invest the same.

But even if the answer is no, there are still many viable paths that are open to you.

And this is exactly where we’ll pick things up next week.

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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