The financial services sector is one of the heavily regulated sectors around the world. Entities offering financial services are required to prevent criminals from abusing their services and protect themselves from relevant regulatory breaches and reputational damages.
The technological advances and developments have changed the way customers transact. More and more businesses are building their models on face-to-face customer relationships and transactions while at the same time they take measures to mitigate the associated risks, such as fraud and money laundering.
However, the rapid developments in technology have also changed the way money laundering is conducted. Regulators and supervised entities around the world need to adapt to these developments and use tools that will enable them to identify potential money laundering with the use of the latest technology.
KYC/CDD assists regulated entities to identify and mitigate potential money laundering and terrorist financing risks associated with a customer before onboarding. However, some risks become evident once the customer transacts or during the business relationship.
How transaction monitoring works
Transaction monitoring is a process that analyses transactions conducted by customers and identifies patterns that may be potentially linked to money laundering or terrorist financing.
An automated transaction monitoring tool allows regulated entities to build rules that will trigger alerts to the compliance department when one or more criteria are met. Scenarios are built taking into consideration:
- Date
- Country
- Amount
- Name of the recipient
- IP address involved
- Reference (if applicable)
Once the specified criteria are met and a transaction is triggered, the compliance department should take measures to investigate the transaction further and decide whether the transaction was indeed a red flag or a false positive. From there on, red flags must be further investigated and, if necessary, a Suspicious Transaction/Activity Report (STR/SAR) may be submitted to the Financial Intelligence Unit (FIU) of the specific jurisdiction.
Manual vs automated transaction monitoring
Manual transaction monitoring is when a company uses employees to analyse its customers transactions and identify potential suspicious activity without the use of an automated system. Criminals, however, are exploiting the latest developments in technology. Additionally, digital transactions are increasing, become more complex and it’s becoming more challenging to manually spot potential suspicious activity. Considering the above, it is impossible for regulated entities to protect themselves from money laundering with manual transaction monitoring tools.
Automated transaction monitoring tools enable regulated entities to monitor a larger number of transactions quickly, saving companies’ time and money. As a result, the compliance department is not required to spend time on each and every customer transaction and can only focus on triggered transactions.
The main elements of an effective transaction monitoring tool
The transaction monitoring tool must enable an entity to:
- Receive alerts when identifying suspicious transactions
- Customize and configure multiple rules, actions and threshold
- Provide a risk rating for monitored transactions
- Allow real-time monitoring if required by the regulated entity
- Stop transactions that may be connected to ML/TF
- Forward alerts to the compliance departments
- Provides detailed analysis about the alert
- Eliminate false positives with the use of Artificial Intelligence (AI) or Machine Learning.
The challenges
Despite all the benefits, there are several challenges associated with automated transaction monitoring.
- False positives: This is when the system is triggering alerts for transactions that do not require further investigation. If too many false positives are generated, more people are required to review these transactions, increasing unnecessarily the operational costs of a company.
- Different perspective from regulators: Entities offering their services in other countries need to consider the regulators’ approach to anti-money laundering and take it into consideration when designing the transaction monitoring rules.
- Ensure continuous compliance with regulations: The AML requirements are constantly changing. The transaction monitoring tool must ensure that transactions remain compliant with the FATF and all EU AML directives.
- Scenario rules: The rules created as part of the transaction monitoring of an entity must be in accordance with the specific risks faced by the entity. One-size-fits-all approach is not appropriate. Even in the same organization, different departments may need to set different rules. Scenarios and rules must be flexible and adaptable to any regulatory changes.
- Machine learning: Machine learning collects behavioural data to build sophisticated algorithms which identify more accurately potential suspicious activity. The algorithms adjust to new trends and are continuously improved over time. Regulated entities with large amount of data need to consider the use of machine learning in transaction monitoring.
