Name Matching Helps Prevent Financial Crime in International Funds Transfers

Payment service providers (PSPs) offers merchants and other clients online services for processing electronic payments via credit card, direct debit, bank transfers, etc.  It typically uses a SaaS model which provides a single payment gateway for multiple payment methods.  PSPs also frequently focus on international money transfers, thus serving immigrant communities with an easy and secure means of transferring funds across borders.

American online PSPs are supervised by the Financial Crimes Enforcement Network (or FinCEN), a bureau of the United States Department of the Treasury which monitors financial transactions in order to combat criminal activities such as money laundering, terrorism financing, and other financial crimes.  PSPs are obliged to comply with Know Your Customer (KYC) and Anti Money Laundering (AML) regulations.  Internationally, a particular focus is on uncovering drug money transfers and other frequent cross-border criminal activities.

To take the case of KYC:  In order to be compliant, PSPs need to screen prospective and current customers against sanctions lists such as those maintained by the European Union, the UN Security Council, or the US Treasury Department’s Office of Foreign Assets Control (OFAC).  Individuals and companies on those lists are typically associated with target countries and regimes, terrorists, international drug traffickers, or are engaged in the proliferation of weapons of mass destruction.  Failing to meet KYC requirements could subject a PSP to substantial fines.

The Challenges of Name Matching

Screening prospective and current clients against sanction lists is not an easy task.  Records may differ due to:

• Misspellings
• Word order variations (Park Sol Mi – Sol Mi Park)
• Initials (John Benjamin Robinson – B. Robinson)
• Abbreviations (Avenue – Ave.)
• Nicknames (Edward – Ted/Teddy)

All of these may, of course, be accidental or intentional.

The records can also be in English or other languages and language scripts, resulting in differences in records due to transliteration variations (Abdel Fattah el-Sisi – Abdul Fatah al-Sisi).  The record fields may also contain data other than names: dates, addresses, and a variety of numeric values, all of which need to be accurately matched.

Modern matching techniques have to be robust in the face of all these potential record discrepancies, not only individually, but in combination. They must also scale to meet today’s Big Data-sized challenges in order to support real-time screening of very large record sets.

How Name Matching Meets the Challenge

Name matching is a critical technology to support PSPs compliance obligations.  Here are some crucial features of an effective and accurate name matching tool:

1. High accuracy.  Effective name matching requires that it be highly accurate, minimizing false positives and false negatives.  Critical to this is the incorporation of techniques for handling the differing characteristics of names from all over the world.
2. Scalable and real-time.  Name matching must be engineered to support scalable, real-time matching of prospective customer records against sanctions lists.
3. Tunable. A name matching product must allow the application of specific business rules to determine what combination of record attributes should be matched and how important each attribute is to the overall matching score.

NetOwl is the kind of product that can provide PSPs with the advanced name matching capabilities required to ensure compliance with Government regulations.