The graphic illustrates an example of movement of funds through a mule network. Prior to receiving fraudulent funds, mule account holders make small arbitrary credits and debits to establish a payment history.
In this context, the £10,000 payment from a fraud victim looks atypical and can be used as a reliable fraud indicator.
Differentiating between legitimate and suspicious activities from a vast number of daily interactions and transactions can be complex. While it’s easier to spot patterns within an organisation’s own customer interactions, difficulty arises when tracking patterns that involve external entities, especially when funds transfer outside the bank’s direct oversight.
The foundation for effectively identifying and interrupting more mule accounts rests on the ability to understand the parties involved more holistically, from digital and physical identities and associated attributes, events and behaviours, to the parties’ accounts, interactions and transactions.
Multi-dimensionality is an important differentiator for effective fraud prevention strategies. A more effective approach should look beyond financial transactions and use broader data to intercept mule accounts more efficiently and help prevent the flow of fraudulent funds.
Multiple solutions can execute in tandem, consolidating insights across physical, digital and email dimensions for a robust perspective that helps support the race toward identifying and preventing money mule activity.
LexisNexis® Digital Identity Network® crowdsources insights across thousands of businesses globally, building one of the largest unique repositories of digital identity intelligence that grows more powerful with each transaction.
LexisNexis® Digital Identity Network® helps shed light on mule operations spanning multiple institutions and allows organisations to make highly-informed risk assessments, not just on transactions, but on the behaviours of the entities making transactions and on hidden associations between the devices and phone numbers they use.
Continuous pattern analysis, rule modelling and optimisation through a machine learning mule model connects insights from an incredibly diverse network of intelligence to help predict the likelihood that an account is being used for mule activity, helping ensure organisations can make the most of the data-driven solutions at their disposal.
The professional services team at LexisNexis® Risk Solutions can develop, train and test the machine learning mule model and can work with customers to identify and mitigate the unique fraud threats they may be facing – even if this requires thinking from a fraudster’s point of view to make their criminal activities as hard to operate as possible.
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