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What is Reasonable Suspicion in AML?
Frequently AML operators ask themselves this question. Especially when they only have half the picture, based on transaction monitoring data. In this post we will provide opinion on what is reasonable suspicion in AML. This is not legal advice, if you need qualified legal advice you should seek an attorney/lawyer.
US law – reasonable suspicion
Reasonable suspicion is a legal standard of proof in US law that is less than probable cause, the legal standard for arrests and warrants, but more than an “inchoate and unparticularised suspicion or ‘hunch'”; it must be based on “specific and articulate facts”, “taken together with rational inferences from those facts”, and the suspicion must be associated with the specific individual.
UK Law – reasonable suspicion
In UK law reasonable suspicion is defined by Lord Denning as;
“Suspicion in its ordinary meaning is a state of conjecture or surmise where proof is lacking: “I suspect but I cannot prove.” Suspicion arises at or near the starting-point of an investigation of which the obtaining of prima facie proof is the end. When such proof has been obtained, the case is complete; it is ready for trial and passes on to its next stage. It is indeed desirable as a general rule that an arrest should not be made until the case is complete. But if arrest before that were forbidden, it could seriously hamper the police.”
“To give power to arrest on reasonable suspicion does not mean that it is always or even ordinarily to be exercised. It means that there is an executive discretion. In the exercise of it many factors have to be considered besides the strength of the case … There is no serious danger in a large measure of executive discretion in the first instance because in countries where common law principles prevail the discretion is subject indirectly to judicial control.”
Lord Devlin noted that “the test of reasonable suspicion prescribed by the Code is one that has existed in the common law for many years,” and continued, citing Dumbell v Roberts  1 All ER 326:
“The police are not called upon before acting to have anything like a prima facie case for conviction … Prima facie proof consists of admissible evidence. Suspicion can take into account matters that could not be put in evidence at all.”
The Privy Council’s judgment was quoted with approval by the High Court of Australia in George v Rockett (1990) 170 CLR 104.
An AML operator frequently works blind. With disparate and dis-jointed IT systems in many cases they have to manually draw together data to establish suspicion of money laundering or terrorist financing. A costly and time consuming process.
This balancing act causes difficulties because freezing an innocent customers account could be commercially difficult for the bank; especially when they aren’t a criminal, haven’t laundered any cash and are not a terrorist!
Having one side of transactions and incomplete customer data causes untold difficulties because of this. The question of ‘suspicion’ or not is one for the individual AML operator. It is likened to a scale where at ‘1’ you have innocence and ’10’ irrefutable belief, suspicion is around a ‘7 or 8’. You have enough reasonable doubt as to the innocence of a transaction/customer but not enough to definitively say they are committing criminal acts. This should trigger a SAR report and possible further bank action such as freezing accounts. It should most definitely instigate further monitoring of the customer/account. See our red flag post to identify some areas to provide reasonable cause to suspect.
With data misaligned, out of date, inaccurate and conflicting the job of an AML operator is difficult at the best of times. This is where data management and governance is critical to aid the decision making process.
Additionally, the use of external, verified and weighted data can assist the AML team to make more informed decisions. Especially with the large volumes of false positives, some of which might actually not be false.
The CYW team are working to create a full suite of intelligence data available to AML operators. Adding to bank internal data with other institute records, appropriately anonymised so no one knows the requester of the data and no one knows who responded either. We, acting in the middle, encrypt all data before it leaves an institutes firewall and it is only decrpyted (and anonymised as to its sender) when it arrives inside the requesting banks firewall. This protects the data as it never leaves an institute.
We also collate data from other sources to provide relevant, timely, weighted and graded intelligence to inform decision making. This data comes from a range of sources including directly from criminal convictions and criminals themselves.
Utilising AI and blockchain technology the CYW solution is currently being designed by users for users. Follow us to stay informed.
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