The Name Game

Since the terrorist attacks on Sept. 11, 2001, government watch lists of known terrorists and money launderers have proliferated. Despite banks' earnest efforts, some may inadvertently do business with people on the watch lists because it often is difficult to match spelling variations common in translated names, as with Chinese or Arabic monikers.

Dusseldorf, Germany-based WestLB AG ($308.1 billion in assets), which has branches and subsidiaries worldwide, was struggling with the issue as it combated money laundering, according to Hagen Schaumkell, director in the business unit of money laundering prevention at the bank. Even before 9/11, Schaumkell relates, he was searching for a monitoring system to prevent WestLB from being the target of money laundering and ease the burden on the bank's investigators, who conducted intensive daily research to create lists of questionable people and transactions, and compared names to watch lists. After 9/11, however, as the watch lists grew rapidly, the need for an automated solution intensified, Schaumkell adds.

Hands-On Research

In the first quarter of 2004, Schaumkell researched products to streamline and improve the name-matching process. Among the solution providers was Herndon, Va.-based LAS. Schaumkell visited the company and was provided with a demonstration account of LAS' NameVariationGenerator (NVG) software. He also performed online demonstrations of at least 10 other products, he relates.

According to Schaumkell, he was sold on LAS' solution because it uses actual spelling variations of names - including nickname recognition - based on culturally sensitive rules and an empirical base of nearly 1 billion names collected from more than 200 countries around the world, rather than relying on mathematical formulas or hit ratios. The bank signed a contract with LAS in June 2004. Schaumkell notes that the purchase cost the bank 20 percent of its total IT expenditure for 2004.

Implementation was completed in August 2004, and NVG has become a core part of the bank's investigative tools. "We wanted to integrate LAS' technology into our solution to build a stronger solution," says Schaumkell. Integration was quick and easy, he claims, using a Simple Object Access Protocol (SOAP) server process. WestLB runs the application on a Microsoft (Redmond, Wash.) Windows 32 server. The bank's investigators log onto the system from individual PCs.

Since NVG was added, questionable names are red flagged within 10 minutes rather than hours, relates Schaumkell. Each day, the bank may have as many as 300 hits. "Before NVG, it took our four investigators 12 hours to get the 300 names, and we had poorer quality," Schaumkell says. "Now, we get better-quality hits to check."

Schaumkell adds that the solution has empowered his investigators. "If we know a certain customer has the same name as someone on the list, and we've checked to find out he is not the one we are looking for on the list, we exclude him by his account number or address," he says. "Every day, we are catching somebody who is interesting enough to be further investigated. In the future, we plan to purchase more LAS software [Name Hunter] to check on new customer relationships in reference to the watch list."

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Snapshot

- Institution: WestLB AG (Dusseldorf, Germany).

- Assets: $308.1 billion.

- Business Challenge: Automate name matching with government watch lists for anti-money laundering efforts.

- Solution: LAS' (Herndon, Va.) NameVariationGenerator.