From BSA Officers to Complex Investigations teams, efficiency in AML investigations is a challenge.
The consumer banking market is changing. FinTechs are quickly on the rise. Financial institutions are being pushed to adapt to consumer demands for frictionless banking at a faster pace than ever before. And with each new product or service offered, more and more financial data systems are required — adding more and more systems to an already complex technical environment. As a result, investigators must often manually piece together data from dozens of siloed data sources. With an incomplete and fragmented view of customer activity, investigators spend valuable time and resources managing data instead of performing the meaningful investigative work they are trained to do.
Data is key when it comes to improving AML investigations. Conventional approaches provide limited access to rich, resolved data from financial data systems. Investigators may not have unfettered access to all their required data sources and may have to request and wait for data from separate teams. With a massive amount of data from multiple locations, investigators are often left to manually piece together a complete view of their customers’ activity. Compiling, managing, and manipulating data to prepare to start an investigation can often take a significant amount of time, slowing down investigations and preventing investigators from quickly making decisions and providing actionable intelligence to law enforcement.
Data challenges for AML investigators can include:
1. Unresolved Entities
Today’s financial institutions offer individual and business customers multiple products, requiring multiple financial data systems and multiple data models. Complex data pipelines create large amounts of data to compile and analyze for money laundering and fraud investigations, and variations in individual and business customer names may result in a single entity appearing as multiple entities within your demographic information. Without an automated process to resolve entities and transactions together from different data sources, investigators are often left to manually piece together a complete view of their customers activity.
2. Fragmented View of Customer Activity and Relationships
AML investigators must fully understand their customers’ activity to make confident decisions quickly. Data is received from many different data sources and manipulated in many different programs and forms, such as spreadsheets, graphic design programs, word processors, and shared drives. Without the appropriate tools to visualize data, investigations are tedious, time consuming, and suspicious activity may go unnoticed.
3. Unknown Counterparties
Investigators have been encouraged to take a risk-based approach to AML investigations and should understand the relationships between their customers and the entities they transact with. This investigative process into counterparties can be extremely time consuming, and it often requires accessing data from many different systems ranging from financial systems, third-party data sources, and open-source data. Up to 60% of alert triage time is spent on tasks related to counterparty research. Without a consolidated view of each counterparty’s historical activity and relationships, investigators are left to manually search for information on counterparties related to their investigations — this process can be incredibly time consuming and error-prone.
4. No Single System of Record
AML investigation teams quite often lack a single, consolidated source of data that provides all the information needed to accurately assess risk, and often lack a system of record for counterparties. Investigations rely on transactional data, demographic data, past cases, alerts, and SAR filings, as well as related entities such as co-signers, beneficial owners or counterparties. Without a single platform to provide a consolidated view of all this data, investigators are often left to piece this information together manually — resulting in duplication of effort and more time spent collecting and manipulating data, rather than investigating activity.
Institutions should consider how a holistic AML Investigation Platform can improve the efficiency and effectiveness of anti-financial crime investigations. Verafin’s unique approach to AML investigations offers a complete view of your transactional and demographic data for a complete picture of customer activity. With a data-driven anti-financial crime management platform including entity resolution, counterparty risk analysis and visual storytelling in a single system of record, Verafin improves the efficiency and effectiveness of AML investigations.