By Robert McGarvey
Talk with credit union AML/BSA staffers as well as senior executives and you will hear a torrent of woe is me complaining about rising workloads, intransigent regulators, too tight budgets, and inadequate resources.
And then there is a new report from Aite Group’s Julie Conroy – based on extensive interviews with over 40 BSA/AML experts – and the title tells you the theme: The AML of Tomorrow: Here Today.
In the second paragraph Conroy puts out the good news: “Advanced technologies such as machine learning, robotic process automation (RPA), and natural language processing and generation are helping to even the playing field by enhancing both detection and operational efficiency. The even better news: Regulators are gradually growing comfortable with the use of these advanced technologies for AML.”
Read that again. What she is insisting is that financial institutions now have access to technologies that will let them keep pace with – maybe get a step ahead of – criminals who want to launder money.
The stakes are high. Two credit unions in the past decade have effectively been put out of business because of AML deficiencies – Bethex and North Dade.
No credit union wants to be linked with money laundering. But, frankly, trying to keep up with this with a small staff who are doing everything by hand is a loser’s tactic.
How much money is laundered annually? Nobody knows. The United Nations has estimated it’s somewhere between $800 billion and $2 trillion. The high end is about the GDP of Brazil and more than Italy’s. That’s a lot of money in motion and, accordingly, you have to assume that the people who have put it in motion are savvy, wily, and of course know exactly the defenses used by banks and credit unions.
Accordingly, FIs are spending a lot to defend themselves – much of it on payroll. Conroy cited a report from the Clearing House that estimated that major US FIs spent $8 billion on compliance in 2017. She also noted that one large US FI interviewed for her report employed more than 5000 in compliance and “can’t hire fast enough.”
All those workers push out an avalanche of SARs. In 2013 they filed 1.22 million. By 2017 that rose to 2.03 million.
Conroy also pointed to a numerical disconnect that frustrates AML workers and their bosses. “the fact remains that there are on average only 1,200 moneylaundering- related convictions per year in the U.S., compared with over 1 million SARs filed per year.”
In other words: is all the work really worth the effort and expense?
It gets worse. In many institutions, said Conroy, business line execs grumble that AML teams are “hassling” their customers, making it harder to do the business that brings in money to the FI. AML, in many institutions, is seen as a nuisance that wastes money while making it harder to make money.
Wrote Conroy: “All of this points to the need for the AML function to find technology that enables precise detection while minimizing false positive noise.”
She continued: “The trifecta of increasing criminal sophistication, a steady increase in regulatory expectations, and under-resourced AML departments are bringing AML efforts to a breaking point. As a result, financial services firms are beginning to embrace technologies such as machine learning, RPA [robotic process automation], and natural language processing and generation.”
“Today’s AML function can no longer rely on legions of AML analysts, investigators, and rules-based automation. The use of advanced technologies is needed to aid AML departments in the gathering, filtering, and meaningful assessment of data from multiple sources in multiple formats.”
That prescription puts fear in the hearts of many credit union leaders – they worry about the costs and also the complexities of advanced technologies.
But Conroy has this absolutely right. The only way to stay ahead the AML wars is with technology that can automate much detection and even reporting. There just aren’t enough AML staffers to be hired and so they get paid ever more.
But – and this is crucial – many of them are burning out, even quitting.
The machines won’t quit on you.
What should your next step be?
In her report Conroy reviews the many technology options out there. Get the report, read her reviews.
And then what? Her advice is simple: accept that you can’t wait, delay is not an option.
She added: “Try starting small. Cloud-based solutions can be implemented in modules that wrap around or interact with legacy systems to improve performance without a ‘rip and replace’ scenario. In this way, FIs can address the most pressing system deficiencies relatively quickly with less impact to budget and IT resources.”
It’s good advice.
Just don’t wait.