Rules are designed to examine customer activity on a profile basis. These designs should differ according to customer profiles. In financial institutions, the profiles of the customers can be determined according to their income level. Along with the income level, other segments should be considered when building the rule.
Before You Build Rules
There are some factors to look at before building the rules.
- False Positives: If the rules are not set correctly, many false positives will occur. Among these alerts, compliance officers might overlook some things, and the organization could host a financial crime. For this reason, the rules you set should be created as fewer false-positive warnings as possible.
- Compliance Officers: It is essential to obtain the expertise of the compliance team before setting the rules. The better the compliance team knows about customer profiles, the better it will be at building rules. However, the whole team must know the rules very well. The department should work in teams to build and implement rules.
- Technological Support: Before building the rules, the software used must be well known. With Sanction Scanner Transaction Monitoring Software, companies can set their own rules and integrate ready-made rules into their systems.
Creating Better Rules
There are some issues to be considered when determining the rule. Regulated firms need to know them to improve their rule use.
Build your own rules: Customer groups may differ in financial companies. The same rules cannot be applied to customers in different segments. For this reason, companies may need to create their own rules. Compliance departments in companies divide customers according to some segments. As a result of these segments, customers are grouped. It is crucial to create rule sets for grouped customers. For example, a student's account statement is not the same as a businessman's. The same rule sets cannot be set for these two customers.
Use Sandbox: Sandbox allows organizations to create new rules in the system or to change existing rules. Within the Sandbox, compliance officers can test the new rules. Also, if they want to make changes to an old rule, they should test it on Sandbox. This environment is the environment for monitoring the scenario of the rules. You can try the rules in the Sandbox and check if it works the way you want.
Update the rules: Compliance departments must keep the rules up to date. The rules may need to be updated as there is a constant flow of new customers in financial institutions. Compliance officers need to check if the rules are working and add new ones where necessary. These new additions must first be tested in the Sandbox. The entire compliance department should be aware of the newly added rules.
Use Machine Learning and AI: Building rules are very effective in controlling financial crime. But criminals will seek new ways to launder money without breaking the rules. Artificial intelligence should be used to prevent this. With machine learning, you can identify out-of-the-norm anomalies and behavior patterns.
Sample AML Compliance Rules
Profile change before huge amount transaction: With this rule, an alarm is generated when a customer changes their personal information shortly before a significant transaction is made. This could indicate taking over of account or possible "layering" activity to hide the path of funds.
Abnormally high transaction: This rule identifies parties with abnormally high payment transaction volume. This rule is suitable for a peer-to-peer payment network where funds can be withdrawn to an external account.
High increase in overall transaction volume: This rule describes a significant increase in outgoing transactions' value compared to a party's last average. It looks for recently operating parties where the party's transaction value is significantly higher than the 7-day moving average. The rule filters out short-standing parties, low-balance sides, and low outgoing transaction value over the respective time period.
Suspicious transaction: This rule defines actions that differ from the person's standard behavior. This one could indicate an account takeover or an externally affected transaction.
High transaction from a new user: This rule covers high volume transactions from new users. Traders detect that a high percentage of their activities come from new accounts, a potential red flag for money laundering or traditional scams.
Rule-Based Transaction Monitoring Software
Financial institutions make millions of transactions every day. It is not possible to control each of them. But they also have to protect themselves from financial crimes. With the Transaction Monitoring Software, institutions control the transactions of their customers on the basis of rules. The software generates an alarm in case of the rule violation and comes to the screen of the compliance team. The compliance officer checks the alarm and decides whether the transaction is suspicious or not.
Compliance units of financial institutions often cannot do all these rule creation and processing manually and prefer to purchase third-party software. At this point, the Sanction Scanner produces software that will facilitate the work of compliance experts. With the Transaction Monitoring Software, you can apply all the rules we have mentioned above, create your own rules, choose from ready-made rules and integrate them into your system.