Customer Information Management
Large Global Financial Services Firm
Global financial services firm boosts AML compliance with more flexible transaction monitoring.
Large global financial services firm
Thousands of financial advisors serving clients across thousands of locations globally
Millions of client accounts, holding billions of dollars in client assets
Expand transaction monitoring of external counterparties to identify internal parties’ problematic behaviors as well
Institute routine, automated processes that compare brokers’ activities against the behavioral norms for their peers
Knowledge graph shows complete view of all an individual’s relationships with other customers or financial advisors within the firm’s records.
Investigations of alerts take much less time.
Algorithm-based analysis establishes range of accepted behaviors for each group.
Alerts generated whenever an individual’s behavior deviates from the standards for his/her group.
When a Large Global Financial Services Firm learned that it would be under investigation by the US Treasury’s Financial Crimes Enforcement Network (FinCEN), it discovered a significant gap in its transaction monitoring processes. Highly suspicious activities undertaken by an employee in an offshore location had come to light when another financial institution filed a Suspicious Activities Report (SAR). The broker/dealer’s external-facing transaction monitoring system had no way of identifying such situations.
As FinCEN launched an 18-month independent review of the organization’s anti-money laundering (AML) practices, the broker/dealer began looking for a solution that would augment data management and help investigators identify potentially problematic internal transactions.
The firm’s transaction monitoring system, which focused on external AML threats, was doing a good job of alerting compliance staff to transactions that violated specific predetermined rules. The firm needed to supplement this system with a more flexible transaction monitoring capability, which would generate alerts whenever a financial advisor or other insider acted in a way that was not consistent with the behavior of his or her peers.
The broker/dealer deployed Pitney Bowes Spectrum® Entity Resolution, built on the Spectrum® Technology Platform, to achieve next-generation data management capabilities.
First, Pitney Bowes worked with the broker/dealer to resolve data-quality issues so that information pulled in from an assortment of source systems would be consistent. Then Pitney Bowes helped the firm configure Entity Resolution to serve as a name and address data-matching engine. The solution accesses a referential database that includes millions of name variations to support entity resolution across all the broker/dealer’s transactions. The goal is to provide a holistic view of every activity, in every account, that is associated with an individual.
Results and benefits
Spectrum generates a web-like visual representation, known as a knowledge graph, that shows all an individual’s relationships which appear in the broker/dealer’s records. The relationships may include customers and financial advisors with whom the individual has worked, any accounts in which the individual has had transactions, and destinations with which the individual’s various accounts have been associated. This saves a tremendous amount of investigation time whenever an alert is generated.
Finally, the firm harnesses the analytical power of the Spectrum Data Hub graph database to identify behavioral outliers as they occur. Rather than running transactions through a specific set of rules, the database uses an algorithm to establish a range of accepted behaviors for a particular group of individuals. Whenever Spectrum detects an abnormality or deviation from these standards, it generates an alert to investigators.