• Use Case: Financial Compliance
  • Segment: Risk Management
  • Product: Rosette
  • Function: Name Analytics
  • Availability: API or SDK

KYC for Financial Institutions

Are You Prepared for New KYC Requirements?

  • Regulators around the world require you to screen customers against a growing number of watch lists that are continually revised.
  • The EU’s 2015 anti-money laundering laws give you just two years to meet more rigorous Know Your Customer requirements.
  • Penalties and fines against executives for non-compliance, at both small and large organizations, are setting records.
  • Globally you are increasingly required to adhere to diverse regulations enacted by all the countries you do business with.
  • Your ability to accurately match customer names written in all global languages and scripts has become essential.

Traditional name matching software looks at names as a simple sequence of letters. It generates an exhaustive list of potentially hundreds of variations of each name on each watch list and then checks each new name encountered against that list. The process requires continual generation and storage of an increasing number of name variations and, as the volume of names increases, the matching process becomes increasingly time-consuming. This approach only accommodates names written in Latin-based alphabets.

Next-generation, knowledge-based name matching software is built upon established patterns of language and cultural use, including the ability to identify the different ways words are used to represent similar names. It accommodates names in non-Latin scripts by applying knowledge of how names are spelled and how each letter or group of letters sounds in each language.

Invaluable Name Matching

Accuracy in name matching, across global languages and scripts, has never been more critical.

The pressure on you to meet higher standards under closer scrutiny requires ever more stringent financial compliance solutions if you want to remain competitive.

Eliminating terrorism, money laundering, and fraud now depend on your organization’s ability to Know Your Customer (KYC):

  • Is the person asking to wire money truly who he says he is?
  • Does the payee printed on this check appear on any of the numerous worldwide watch lists?

Ten Questions to Ask About Name Matching

  1. How reliable is your current solution’s identity verification?
    You need a product that can identify individuals through their legal name, nickname(s), initials, and all possible misspellings and iterations, regardless of language. Comprehensive name matching must now accommodate documents, web pages, customer information, wire transfers, teller systems, brokerage and trust databases, invoices, and contracts.
  2. Can your solution track domestic PEPs in Internet news articles and social media?
    To meet the demands of enhanced KYC regulations, you will need text analytics to monitor all domestic Politically Exposed Persons (PEPs) you transact business with.
  3. Does your solution support transaction screening in Russian, Arabic, and Chinese?
    Global identity and financial investigations now depend on cross-lingual matching and linguistic expertise across non-Latin script language, including difficult languages (i.e. Russian, Arabic, Japanese, Chinese, Korean).
  4. Why isn’t the traditional approach of generating variations adequate to match misspelled names?
    A three-component name translated into English can have hundreds of variations. In a climate of escalating international regulation and penalties and when even a single failure to match a single name could jeopardize your institution, it is simply too risky to rely on outdated methods that do not encompass all world languages and linguistic mastery.
  5. Can your solution accommodate watch list requirements originating from all countries?
    With watch lists now being created by countries using non-Latin scripts, your product needs to reliably screen names against each and every list.
  6. Can your solution identify Mohammad Al Baradei, Mohamed ElBaradei, 穆罕默德·巴拉迪, ухаммед аль-Барадаї and مصطفى البرادعى as the same person?
    When name matching, your software must be both culturally sensitive and knowledgeable about linguistics. Knowledge-based name matching is stronger than name variation generation systems when it comes to names in different scripts, names encountered for the first time, spacing irregularities, and misspellings.
  7. Can your solution scale affordably as name matching demands continue to grow?
    All watch lists are works in progress. As each grows, the number of name matches grows exponentially for name-generation solutions, but not for knowledge-based solutions. You want a solution that absorbs change, with minimal additional hardware or cost.
  8. Can your solution match names even when components are entered into the wrong fields?
    When your organization is held accountable for accurately matching names against a growing number of watch lists, it is risky to rely, for example, on a bank employee in Chicago knowing that a Mexican customer’s surname is often two words, where one name may be mistakenly entered as a middle name.
  9. Is there a way to increase accuracy and cross-lingual matching functionality in the solution you have now?
    There are name matching products designed to seamlessly layer on top of existing functionality without adding a lot of additional hardware.
  10. Is your solution vendor focused on name matching?
    When name matching is a core focus of a company, it means its products are continually developing, improving, and expanding their capabilities.

Take the time NOW to assess if your current name matching solution is as reliable as it needs to be. Make sure it delivers the fastest and most accurate results possible, while minimizing errors. Consider whether your solution offers the inherent scalability you need as compliance requirements continue to expand.

Are you confident that your current software solution is reliable enough, when the stakes are so high?

  • A false negative means you say YES to someone you don’t really want to do business with.
  • A false positive requires expensive investigation and the possibility you say NO to potentially valuable business.

Either way, your institutional reputation is damaged and you face increased risk of legal liability.