Mule networks enable organised financial crime by moving illicit funds through the financial system. This article explains why disrupting these networks is critical to stopping fraud at scale and how contact centres are playing an active role in identifying and disrupting mule activity.
Organised financial crime depends on one fundamental capability: the ability to move, launder and withdraw the proceeds of crime. Mule networks provide the organised system of accounts, people and processes that make this possible.
These networks exploit the same financial systems that legitimate customers and businesses rely on – payment rails, bank accounts, communication channels and digital services. By abusing this shared infrastructure, fraudsters are able to operate at scale, making their activity repeatable, efficient and increasingly difficult to track and contain.
Disrupting mule networks is therefore essential if we are to successfully combat fraud and organised crime.
Mule networks underpin fraud and financial crime
Fraud and financial crime is often discussed in terms of typologies: authorised push payment (APP) fraud such as romance or other impersonation scams that trick consumers into making payments; account takeover, where fraudsters ‘hack’ people’s accounts and initiate transactions, or fraud involving synthetic or stolen identities. While these crimes differ in how money is stolen, they converge at the same point: once funds are obtained, they must be moved.
To support this movement, organised crime groups require access to large numbers of accounts and money services, spread across institutions and geographies. They must continuously source new mule accounts, rotate identities and reuse effective methods to reduce detection risks. As a result, while individual accounts and participants may change, the underlying coordination, infrastructure and behaviour persist.
This repeatability makes large-scale fraud viable – and it also creates patterns that can be detected when activity is viewed across time, channels and organisations, if you know where to look.
Regulatory pressure to disrupt money mule networks
As the key financial enabler for serious organised crime and terrorism, mule activity sits squarely within the financial services sector’s global anti-money laundering and financial crime prevention obligations. The pressure to monitor and prevent these crimes is high, and the consequences of failing to do so are significant.
Weak controls in the financial services ecosystem have far-reaching implications for global banking relationships, investment confidence and economic growth. Vulnerable individuals are also left exposed to exploitation, amplifying social harm alongside personal financial loss.
To mitigate these risks, international bodies such as the Financial Action Task Force (FATF) place jurisdictions under increased monitoring where deficiencies are identified, while national regulators like the UK’s Financial Conduct Authority (FCA) levy multi-million-pound fines on firms found to have inadequate anti-money laundering controls. In parallel, the UK’s Payment Systems Regulator (PSR) also requires banks to reimburse victims of authorised push payment scams, further increasing the financial and operational stakes.
Together, these factors intensify the need to find smart, efficient ways to disrupt mule networks wherever possible.
Following the signals mule networks leave behind
Traditional fraud controls are often optimised to stop individual transactions or accounts. While necessary, this approach can result in a “whack-a-mole” dynamic: individual events are blocked, but the underlying network remains intact.
Mule networks cannot avoid interacting with regulated systems altogether, so fraudsters deliberately distribute their activity across time and channels so that no single interaction appears suspicious. In doing so, however, they still leave consistent signals across a wide range of touchpoints, including the devices used to make contact (such as mobiles or laptops), account opening, transaction flows, biometric and behavioural patterns and communication channels.
Different technologies already identify and monitor aspects of this activity. No single solution provides a complete picture, but together they do offer the raw material needed to expose network behaviour. As a result, more effective mule disruption often comes from shifting focus away from individual outcomes and towards connected activity.
When signals are linked across systems, channels and time, patterns emerge that are invisible at the level of isolated events.
Contact centres as a practical point of counter-fraud traction
One area where we find organisations are increasingly seeing traction in disrupting mule activity is the contact centre. This is one of the few places where mule networks must repeatedly surface in order to operate.
Organised crime groups frequently interact with contact centres to progress new account applications, query or amend transactions, initiate chargebacks, increase overdrafts or lines of credit, or change contact and payment details, for example. Taken in isolation, these calls often appear routine. In aggregate, they can reveal organised activity.
Common indicators include calls from numbers already known to be implicated in crime and the same numbers contacting about multiple different accounts. The same recognisable voices, devices and calling behaviour can also often be linked across accounts and business areas.
Our clients have had particular success by linking contact centre activity with other fraud signals, connecting accounts, devices, voices and phone numbers back to the same underlying criminal groups. This approach enables early identification of mule networks and intervention before funds are moved, and for one leading global bank this has led to prevented losses in the £thousands.
A systems approach to mule network disruption
No single control, team or technology can dismantle mule networks alone. Effective disruption requires pressure from multiple angles: across channels, organisations and stages of the fraud lifecycle. Ultimately, the goal is not perfection, but friction – making networks harder, slower and more expensive to operate.
When signals are connected and shared, the economics of organised fraud begin to change. Organisations that look beyond individual transactions and focus on networks, patterns and early signals are better positioned to protect customers, reduce losses and weaken organised crime at scale.
