Customer Information Data Management Systems
Large global bank
Solving serious data-quality problems is key to AML compliance for global bank.
One of the world's largest banks
Millions of customers globally
Trillions of dollars in assets
Ensure AML compliance by improving quality of data in transaction monitoring system
Improve efficiency of investigations
Have entity resolution technology fully functional within six months
More precise definition of risk posed by each customer
More accurate alerts than in legacy system
Reduction in false positives and noise in transaction monitoring, for more efficient AML operations
One of the world’s biggest banks was in serious trouble. It was facing regulatory action because of deficiencies in its anti-money laundering (AML) compliance activities. The bank needed to improve its transaction monitoring, and it didn’t have much time.
One specific area it needed to improve was counterparty identification capabilities, to ensure that information flowing into the transaction monitoring system was accurate and complete. The financial institution’s counterparty data was in disarray, with crucial identifiers missing from some transactions. Because of these data management problems, trillions of dollars in transactions were flying below the bank’s compliance radar every year.
The bank prepared to roll out a new transaction monitoring system on a six-month timeline, and improving the quality of the information being pulled into the system was a top priority. The adage “poor data kills compliance” rang true with the management team. It was a time-sensitive initiative, as the data-quality problems needed to be resolved before the transaction monitoring system went into production.
The financial institution already worked closely with two large business intelligence vendors, both of which would have been willing to build systems, free of charge, for validating and supplementing the bank’s counterparty information. However, the bank lacked confidence that either of the other vendors could provide the breadth and depth of entity resolution functionality it needed, and it knew they couldn’t do so within its six-month window for deployment.
Instead, the financial institution selected Pitney Bowes Spectrum® Entity Resolution. Its decision was largely based on the fact that Entity Resolution is able to offer industry-leading data quality, alongside an innovative “graph”-based data hub that enables investigators to identify non-obvious relationships, helping to drive down the time and cost of AML investigations.
Pitney Bowes Spectrum® Entity Resolution assigns each of the bank’s counterparties a Global Unique ID, then creates a single version of the truth around that counterparty’s relationship with the bank. It then adds context by drawing on the bank’s internal systems, as well as the Pitney Bowes World Points of Interest Data Set, which includes more than 100 million businesses and addresses. And because all the entity resolution processes are contained within the system, rather than targeting erroneous data in source systems, the deployment met the bank’s tight timeline and delivers a high-performing solution.
At the same time, the analytics capabilities of Entity Resolution enable the financial institution to monitor transactions more precisely. The solution segments counterparties at a granular level and establishes expected behaviors for each group. Then it compares all transactions against expectations for the counterparties, generating alerts when activities fall outside standard deviations.
Results and benefits
Because the bank integrated the Entity Resolution solution into its transaction monitoring system, alerts are now more accurate across multiple jurisdictions. The bank clears high volumes of cross-border transactions on a daily basis, and in the past it struggled to separate its foreign customers from unknown foreign counterparties. By providing this capability, Entity Resolution is contributing to reducing false positives and “noise” in transaction monitoring, enabling the bank to better target its investigative resources.
The Global Unique ID and relationship visualization capabilities further improve investigator efficiency by linking alerts for the same counterparty into a single case for investigation. Entity Resolution is able to process up to 3 million transactions per hour, consolidating more than 80 percent of the identified third parties.