A handful of financial institutions have made waves in international news due to lawsuits and multi-million-dollar fines. The issue is that they chose, whether intentionally or unintentionally, to be noncompliant with BSA and AML regulations—a costly decision.
SYSTRAN hears from our clients in the banking sector that the possibility of fines for noncompliance forces them to continually monitor and assess their organization to ensure that there are no compliance issues. But one of the largest underlying reasons for non-compliance is a poor method for the translation of multi-languages that doesn’t ensure every communication channel is monitored. Machine translation is the solution to this very real and prevalent problem.
Bad actors are everywhere, inside, and outside of your organization. Using MT across the board gives you a pulse on what is happening globally across your organization (and in every language) to prevent similar fines from happening to you.
Here are some of the hardest lessons learned regarding AML enforcement actions for Fortune 50 companies that did not have a language monitoring system in place to track global activity.
- Westpac – $1.3 Billion
Westpac, one of Australia’s largest banks, has been under fire for years. In addition to being fined for charging fees to the dead in 2022, Westpac was fined a record setting $1.3 billion in 2020 as part of an AML suit where they failed to meet AML obligations.
Lesson Learned: Don’t invoice dead people.
- Robinhood – $30 Million
Investment platform Robinhood was fined $30 million for significant failures when dealing with compliance regarding BSA and AML obligations.
According to Superintendent of Financial Services in New York, Adrienne Harris, Robinhood “failed to invest the proper resources and attention to develop and maintain a culture of compliance.” This failure led to significant violations, particularly with its transaction monitoring system.
Robinhood’s internal processes were understaffed and did not provide enough resources to cover their potential risks, which created significant shortcomings in compliance. As Robinhood continued to grow, its compliance team did not grow with them, leaving gaps in coverage and increasing the risk of noncompliance throughout the company.
Lesson Learned: Leverage machine translation technology and AI to pick up the slack where you don’t have enough staff to ensure sufficient coverage. This violation would have been detected earlier if automated processes were in place.
- Helix – $60 Million
Helix and Coin Ninja were Darknet services that allowed users to anonymously launder an estimated $300 million through cryptocurrency.
Larry Dean Harmon, the operator of cryptocurrency mixing services Helix and Coin Ninja, was charged a $60 million fine. In addition to money laundering fines, he agreed to forfeit more than 4,400 bitcoins with a value estimated at more than $200 million.
Lesson Learned: Refuse anonymous laundering and only accept laundering from “known” bad actors.
- USAA Federal Savings Bank – $140 Million
USAA was charged a $140 million fine for violating BSA by lacking an adequate AML program. The bank admitted it willfully failed to report transactions. The bank was fined $60 million for noncompliance in 2022, with an additional settlement of $80 million for persistent noncompliance issues going back to 2016.
Lesson Learned: Quit willfully failing to report. Standardizing training resources across languages can go a long way in closing this gap.
- MoneyGram – $8.25 Million
MoneyGram failed to maintain an effective and compliant AML program and faced an $8.25 million fine. This fine was charged because of MoneyGram’s lack of supervision over only six agents. The agents made dramatic increases in transactions without any reasonable explanation and, in a 17-month period, transferred more than $100 million to China.
Because MoneyGram had already taken significant steps to improve its AML programs, the fine was reduced to this lower amount.
Lesson Learned: A.I. is smarter than you. Let a machine detect suspicious activity so you don’t get lost in the language. If you’re dealing with international deals, have machine translation integrated so there is automatic transparency in all communications.
- Wells Fargo Advisors – $7 Million
Wells Fargo failed to file at least 34 suspicious activity reports between April 2017 and October 2021. Rather than dispute the charge, Wells Fargo agreed to pay $7 million to settle the charges of noncompliance.
While Wells Fargo had an AML system in place, the system failed to reconcile the different country codes used to monitor foreign wire transfers. The result of this failure was that Wells Fargo unable to file a timely report of suspicious activity for at least 25 of those 34 suspicious activities.
Lesson Learned: Leverage Smart Machines, rather than dumb machines. It’s too expensive, even when you settle! Machine translation can help streamline the monitoring process to make sure you’re never behind schedule.
- Capital One – $390 Million
Due to willful and negligent violations of BSA, Capital One was fined $390 Million. Capital One admitted to failing to implement and maintain an AML program and neglecting to file thousands of suspicious activity reports (along with thousands of CTRs) between 2008 to 2014.
In addition to money laundering, this opened the doors for millions of dollars in suspicious transactions to go unreported.
Lesson Learned: Never wait to report suspicious activities. Automated MT and AI solutions would have identified issues when they happened so that the problem didn’t grow for years.
- ABN Amro – $574 Million
ABN Amro was fined $574 million after being prosecuted by Dutch officials because of their AML procedures. They had previously been cited for their weak AML processes, but the improvements added were insufficient, leading to this fine.
Lesson Learned: Weak AML processes can result in prosecution.
- AmBank – $700 Million
AmBank, in conjunction with the acts of former Malaysian Prime Minister Najib Razak, was fined $700 million for several counts of money laundering, abuse of power, embezzlement, and breach of trust.
Lesson Learned: Working with criminals can cost you.
- DNB ASA – $48.1 Million
Norway’s largest lender, DNB ASA, was fined over $48 million for failing to comply with AML regulations. In addition to noncompliance with BSA and AML regulations, the bank faces corruption charges.
Lesson Learned: Corruption doesn’t pay.
The Key Takeaway – Global Compliance Isn’t Optional
Too many companies ignore compliance regulations or don’t have adequate coverage and training. But, compliance isn’t optional. AML fines on banks apply even when just one employee fails to follow compliance regulations.
Regardless of the compliance processes you have in place, if you cannot monitor every communication in every language, you are at risk of huge fines like those described above. However, you can reduce that risk significantly by leveraging AI that watches for illegal actions at scale and eliminates the temptation for employees to seek out non-compliant solutions.
AI-Enabled Machine Translation from SYSTRAN Can Help
- Understand every email, PDF, SMS, and document
- Keep private information away from the bad actors lurking just outside your firewalls. You own and control the information on your SYSTRAN servers—no outsiders are allowed in.
- Enable fully compliant communications at all levels of your organization. Employees don’t have to go elsewhere for translation when SYSTRAN is accessible in the programs they use daily.
- Create an accurate picture of where you stand on compliance. SYSTRAN gives your compliance-monitoring teams the visibility they need to identify risks before they become fines.
SYSTRAN’s MT busts open global visibility so nothing can hide, allowing you to ensure every document and communication channel is in compliance with all laws and security regulations.
Translate the unknown into known so you don’t miss a thing! Schedule your free demo today to see how SYSTRAN keeps information secure and gives deep visibility of your potential risks.