Why it is just as hard as AML monitoring
AML and sanctions are usually mentioned in the same breath. But while they are closely associated, they’re not the same. Admittedly, sanctioned entities could very well also be involved with money laundering, but this isn’t always necessarily the reason such entities appear on a sanctions list. Sanctions are commonly known as a means of putting political pressure on foreign regimes. But it’s not the only reason for sanctions.
Sanctioning becomes more complex every time the regulations change. By no means do they apply to foreign regimes only. It also applies to activities, for example. Sanctions are used for:
- Specific people
- Blocking financing of specific activities
- Monitoring for licenses that are required for specific goods when exporting them to sanctioned countries.
This article explains why monitoring for sanctions isn’t as easy and straightforward as one might assume. It also discusses the role technology can have in sanction monitoring.
Misconception 1: Working of a list makes sanction monitoring easy
AML monitoring can sometimes seem like a scavenger hunt. You’re searching for clues to find a haystack. When you’re finally there, you find out that you still have to find a needle in that haystack.
Still, don’t underestimate the effort going into sanctions monitoring. Matching transactions against a sanctions list might sound easy, but it isn’t. There are many reasons why banks could fail to comply with sanction monitoring regulations. Political tensions can complicate this type of monitoring. An example would be the current divide between the United States of America and Europe on how to approach Iran after the USA canceled the nuclear deal that was negotiated under the Obama administration.
Political ambiguity makes it hard for global banks to decide on processing transactions. It forces banks to revisit their risk appetite and possibly change their policies urgently. These types of situations ask for sophisticated and adaptable software that can instantly install redefined policies. But this example is extraordinarily complicated. Most issues leading to compliance failures in sanction monitoring are more mundane. This brings us to misconception number two.
Misconception 2: Sanction monitoring is a simple name matching process
As mentioned, sanctions monitoring has the benefit of working against a data list. That doesn’t make it much easier than monitoring for money laundering. It’s important to emphasize that screening isn’t a simple name matching process. It requires analyzing data from diverse and sometimes conflicting tools and sanctions lists. For successful analyses, monitoring technology asks for a specific level of sophistication. The application needs to be smart enough to recognize sanctioned entities. Even if there isn’t an exact match on a list. This is especially hard for those financial institutions where data sources aren’t connected. Unconnected data sources can lead to issues like inaccurate or incomplete data. Unfortunately, most traditional banks deal with this problem.
Machine learning technology generates and combines signals for banks with scattered data sources to separate the false positives from actual positive alerts. Machine learning technology enables the application to learn from a compliance officer’s input when he assesses and handles an alert. The next time a similar signal comes up, the system recognizes that there was a similar signal before and knows what to do with it. It will either automatically process a false positive transaction, or it will send the alert to a compliance officer for further investigation.
Connecting the sanctions monitoring application to an automatically updated database of sanctions lists mitigates the risk of missing newly sanctioned entities. Also, when new sanctions are imposed, the system won’t need to be manually updated with sanction rules.
Misconception 3: Every transaction is a possible hit on the sanctions list
Compliance takes a lot of effort and human resources. That’s why it’s important to be smart about monitoring priorities. Every payment doesn’t need the same level of monitoring. Neither does every client need as much monitoring scrutiny. For example, as domestic payments fall under the same jurisdiction, they are less likely to be subjected to sanctioning than cross-border payments.
If the monitoring application doesn’t take that into account, it means that it could provide more work for compliance officers by causing false positive alerts. Sanction monitoring asks for technology that can intensify monitoring routines for certain payments over others.
To safely configure monitoring priorities, the monitoring application should be able to take a client’s network into account to identify suspicious behavior. If a client constantly makes cross-border payments to recipients with aliases like Ahmed the Wise or Igor the Great, that should be a cause for suspicion. Even in less obvious situations, the system needs to be able to find patterns in the behavioral and network data of a client. Just because you cleared a client in the KYC-process, doesn’t mean he won’t be in contact with sanctioned entities. With continuous monitoring, a client’s risk rate can be lowered or increased. That will help the system to determine how to rank individual alerts.
A lack of guidelines makes AML monitoring elusive. But sanction monitoring has its own set of challenges. Technology helps to make sanction monitoring much easier and more effective. At the same time, it lowers the number of false positives and, thus, the overall alerts.