3 min read
Detecting Counterparty Behavior with QuantaVerse’s Advanced Technology
Sophie Proctor : July 01, 2022
AML case investigations traditionally center on the focal entity and their most active counterparties. However, limiting the circle of inquiry investigators may miss suspicious counterparty clues and any related risks, leaving financial institutions vulnerable.
But how can counterparties undergo effective examination? Even the best human investigative teams can encounter these complications, including:
- Mis-matched skill sets – the diverse set of skills investigators have may not match the case at hand
- Language barriers – researching in foreign languages can prove difficult and time consuming
- Time limitations -- investigators are under pressure to get cases reviewed and high manual effort with time constraints can cause human error or missed suspicious activity
- Global variations -- conducting global research brings with it differences in legal structures and registrations in jurisdictions which can slow down the investigative process.
Investigative teams must therefore identify which part of the process is sacrificed; the number of counterparties being examined, the depth of their research, or how much time they can allot to the case.
Book a demo today to find out how our QuantaVerse platform can help your financial institution detect and prevent money laundering.
Determining the depth of the research
For investigative teams to decide upon the counterparty research, they are given either guidelines from the bank, or expectations of the regulators. The bank may offer guidelines such as: research the top number of counterparties based on transaction volume, only research counterparties related to alerted transactions, or 50% of the dollar value of the transactions.
Financial institutions must take some of the decision making into their own hands and establish their own standards for staying aligned with their regulators’ expectations as well as their own risk appetite. This may mean discrepancies between institutions, but also between cases within the institution as they consider the nature of the case for their investigative process.
Customer-based TMS Alerts, or HRER Investigations
- Existing customers are easier for investigators as they already have access to their information (investigators generally spend 50% of their time looking for data internally and 50% looking externally)
- Internal data helps counterparty investigations as it can provide information on any prior investigations, RFIs, legal papers, previous sanctions or mentions in prior SARs
- External data requires deeper research as well as more time and skills (such as foreign languages) which can cause complications
Correspondent Banking Investigations
- There is no relationship with either party and no internal information available, making these cases more challenging
- The trigger for the alerts forms the investigative guidelines and how far an investigator can dig into counterparties
Complicating Factors for Investigators
- The Multinational Conundrum
If a party in a transaction is a multinational company, they will have legal entities of a larger corporation conducting business across multiple jurisdictions. The default for investigators may be to examine the larger parent company which is easier to research and has online content in their local language. But if one entity for this multinational company from a smaller and more obscure region is the counterparty which is being paid a large portion of the relationship transactions, then that unit must be investigated. The issue lies that an obscure business unit of a large international company will have little online presence and causes challenges for investigators.
- Double Duty
The investigator’s experience can greatly influence how cases are reviewed. For example, in China, a company’s English name will differ significantly from the Chinese name and the Chinese government will allow companies to incorporate with a different name. A highly skilled investigator may know to research both companies, under the two differing names, and investigate counterparty relationships on both sides. Investigators are then faced with less time to investigate, as they have both company names to research, or some junior investigators may be unaware they have to research both and miss any potential risk.
How QuantaVerse can help
An invaluable capability of an AI-powered technology solution like QuantaVerse is its ability to monitor customers’ relationships to other customers and entities and learn from their associated behavior. With this capability, the transactional analysis of these intermediary relationships can be automated to detect any anomalous behaviors and identify which client is causing these anomalies. Find out more about applying AI to reduce AML risk here.
The solution can also account for seasonality, mergers and acquisitions, randomness, and other legitimate variabilities which can separate the illegitimate anomalies which present significant risks to financial institutions. To complete the process, QuantaVerse’s intelligent technology can provide predictive insights into these transactional behaviors and automate the necessary regulatory analysis and reporting.
QuantaVerse provides a deeper investigative process than often conducted by investigators, with a more complete network of due diligence and provides a high accuracy rate in less time than a manual web search. Investigators can be put to greater ease when conducting their due diligence with this platform as it brings with it a greater assurance rate with thoroughly researched findings and a 98-99% accuracy.
The QuantaVerse platform can also be counted on by the more junior investigators due to its record of their respective institution’s best practices, proving consistent findings are created regardless of years of experience. It will also save time for the more seasoned investigators as they reserve their time for more serious cases of financial crime.
Book a demo today to find out how our QuantaVerse platform can help your financial institution detect and prevent money laundering.