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

KYC for Software Vendors

Is Your KYC Platform Ready for New Compliance 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 for your customers.

The pressure on you to meet their higher standards requires ever more complex financial compliance solutions if you want to remain competitive.

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

Ten Questions to Ask About Your Name Matching Capabilities

  1. How reliable is our product’s identity verification?
    Your customers require 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 our product track domestic PEPs in internet news articles and social media?
    To meet the future demands of enhanced KYC regulations, your customers will need text analytics to monitor all domestic Politically Exposed Persons (PEPs) they transact business with.
  3. Do we support transaction screening in Russian, Arabic, and Chinese?
    To meet the future demands of enhanced KYC regulations, your customers will need text analytics to monitor all domestic Politically Exposed Persons (PEPs) they transact business with.
  4. Why can’t we rely on our current approach of generating variations 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 customer, it is too risky to rely on outdated methods that do not accommodate all world languages and linguistic mastery.
  5. Can our product adhere to watch list requirements originating from foreign countries?
    With watch lists being created by countries using non-Latin scripts, your product needs to reliably screen names against each and every list.
  6. Can our 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 can handle names in different scripts, names encountered for the first time, and spacing irregularities as well as misspellings.
  7. Will our product scale affordably as name matching demands 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. Your customers need a solution that absorbs change, with minimal additional hardware or cost.
  8. Can our product match names even when components are entered into the wrong fields?
    When your customers are 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 may be mistakenly entered as a middle name.
  9. Is there a way to increase accuracy and cross-lingual matching functionality in the product we 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 our core competence name matching?
    When name matching is a core focus of a company, it means their products are continually developing, improving, and expanding their capabilities

The best-of-breed solution must deliver not only faster, more accurate checking,with fewer errors, but also possess the inherent scalability to meet ever-increasing complexity and volume of names on the various watchlists (external and internal).

Any error can be costly:

  • A false negative means your customer says YES to someone they do not really want to do business with.
  • A false positive means your customer says NO to potentially valuable business.

Either way your customer’s reputation is damaged and that organization is at increased risk of legal liability.