How AMLC analyzes suspicious money deals

(First of two parts)

MANILA, Philippines — As the country’s financial intelligence unit, the Anti-Money Laundering Council (AMLC) plays a vital role in ensuring that the Philippines is not used as a money laundering site for the proceeds of any illicit activity or financial crime.

At the core of its operations are two key types of transaction reports: the Covered Transaction Reports (CTRs) and Suspicious Transaction Reports (STRs). These reports provide the foundation for the AMLC’s intelligence work and are critical to the detection of potential money laundering and terrorism financing activities.

CTRs are filed to monitor large transactions that are possibly linked to money laundering or other illicit activities. CTRs are typically filed when a financial transaction exceeds P500,000.

It also refers to a transaction involving jewelry dealers that is above P1 million or a cash transaction with real estate developers exceeding P7.5 million.

On the other hand, STRs are more complex. These are flagged when financial institutions detect transactions that may seem irregular or unusual. These transactions do not necessarily involve large sums but may be indicative of attempts to obscure unlawful activities.

Both CTRs and STRs are submitted electronically by covered persons—typically banks, financial institutions, or other regulated entities—through the AMLC’s File Transfer and Reporting Facility.

Due to the sensitivity of the information, all involved entities, officers and employees are prohibited by law from communicating any details of a report, ensuring confidentiality throughout the process.

“Upon the receipt of transaction reports, the AMLC assesses the information, prioritizes the risk and performs its own analyses using a variety of information sources and analytical techniques,” the AMLC told The STAR in an email interview.

The AMLC also performs strategic analysis using data gathered from the transaction reports and other information it receives from law enforcement agencies and counterpart financial intelligence units of other countries.

AMLC’s risk-based approach

As the national center for receipt and analysis of CTR and STRs, the AMLC receives millions of transaction reports each year.

To prioritize the processing and analysis of more critical CTRs/STRs, the AMLC has implemented the rules-based and risk-based classification system. This system classifies STRs based on specific rules and corresponding risk levels of unlawful activities and suspicious circumstances.

The AMLC has also implemented the data mining system, which is a tool that generates alerts grounded on rule-based scenarios.

In carrying out its functions, the country’s financial intelligence unit employs several mechanisms to address the issue of false positives in its analysis of financial transactions.

A key approach is conducting thorough analyses of submitted reports, ensuring that only those involved in unlawful activities are flagged in the AMLC’s reports.

To enhance accuracy, the AMLC implements a human review process for flagged transactions, particularly for high-value or high-risk ones. This manual review helps ensure that legitimate transactions are not mistakenly categorized as suspicious.

The AMLC also issues reports and guidelines, such as the AMLC Registration and Reporting Guidelines, which provide a list of alerts and red flags to help covered persons accurately identify suspicious transactions.

Moreover, the AMLC disseminates strategic analysis reports to relevant stakeholders, outlining emerging money laundering typologies and suspicious indicators to guide financial institutions in detecting illicit activities.

To stay ahead of evolving threats, the AMLC said it continuously updates the rules and models of its data mining system to adapt to new patterns. Advanced data analytics and machine learning algorithms are also utilized to better understand transaction patterns and distinguish between legitimate and suspicious activities, minimizing the occurrence of false positives.

However, data quality issues and isolated systems are still significant challenges that the AMLC faces in processing and analyzing high volumes of transaction reports.

“The presence of data inconsistencies and errors (possibly attributable to encoding mistakes by covered persons) requires meticulous cleaning and standardization procedures, which typically take a considerable amount of time to correct and/or reconcile,” the AMLC said.

(To be continued)