Before the flip: spotting money mule risk inside your boarded accounts

Exclusive Synectics research confirms what many banks have suspected: money muling has shifted. The primary exploitation point is no longer new accounts, but the customers you already know and trust.

Gold-standard point-of-application checks have limited how far organised networks can get with new mule recruits. In response, herders now target established customers with clean histories: the type who wouldn’t meet a typical threshold for ongoing mule screening.

These accounts are highly attractive. They’re trusted, stable, and checked infrequently after the initial post-onboarding period. Yet, when those accounts are continuously screened, a considerable number of confirmed mules are found. 75% more than would have been detected at onboarding, in fact.

The money laundering battleground has moved inside the customer book, where behaviour evolves gradually and blends into normal activity until it’s too late.

Before a good customer turns risky, what changes?

No one decides to become a mule overnight. Pressure, misinformation, or manipulation can push vulnerable individuals into laundering money. Some are exploited victims, while others start small and get drawn deeper into organised APP scam networks.

Regulators and consumer advocacy groups are increasingly recognising the grey space between “safe” and “criminal”. Ongoing mule screening approaches must recognise it too.

To meet the mule threat where it’s emerging, subtle vulnerability signals must be flagged early and interpreted quickly.

A finding from RUSI underscores precisely why: 15% of mule-linked funds leave an account within a day. In that brief window, genuine savings disappear and criminal proceeds are pushed offshore – and through your infrastructure.

Ongoing screening gives teams the ability to intervene before the flip, or sharpen your in-flight controls when an illicit transaction begins.

The data signals that make ongoing screening effective

Banks with high-performing on-book mule strategies are combining shared and internal mule intelligence with a real-time view of what “normal” customer behaviour genuinely looks like. Effective models share the following data features as standard:

• Confirmed mules – both internal and across organisations
• High-risk associations forming beyond immediate contacts
• Cross-sector signals, that show mounting vulnerability before it reaches you
• Digital and service interaction changes that suggest pressure or manipulation

This broad, deep intelligence builds the context needed to judge whether a new piece of information is of note, or a warning sign to be acted on. Aside from confirmed mules, none of these signals would raise an alarm individually. But together, they can indicate coercion or laundering long before rigid thresholds catch up.

Turning complexity into confidence

More risk migrating into existing accounts can create pressure, especially without a staggered approach. But the insight gathered through ongoing mule screening becomes a powerful asset.

• It focuses referrals where they’re genuinely needed
• It improves prioritisation so investigations go deeper in the right places
• It sharpens transaction controls by enriching context

Crucially, it does all of that without unfairly challenging good customers or missing those approaching a tipping point.

With the right intelligence in place, ongoing screening becomes a practical and powerful extension of your current strategy. It gives banks greater confidence at the moment it matters most, where risk now emerges: within the accounts you already know.