Solving Serious Data-Quality Problems is Key to AML Compliance for Global Bank
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 counter-party identification capabilities, to ensure that information flowing into the transaction monitoring system was accurate and complete. The financial institution’s counter-party 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 counter-party 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 Precisely 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 compliance investigations.
Precisely 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 Precisely World Points of Interest dataset, 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.