In this article, we will examine each of the screening situations and provide information on how to reduce the amount of false-positive results in a screening.
How and where can screenings be run?
There are three ways to run PEP, sanction and adverse media screenings on the Meo platform:
- Automatic screening when onboarding a client via a onboarding process/request
- Automatic screening when importing a company and the associated entities
- Manual screening on an entity
The first method of automated screenings depends on your process setup. Please contact care@meo.io if you have any questions for your specific setup. Most onboarding processes are set up to run an automated PEP, sanction lists and adverse media screening when the client completes the process.
Note that a screening will only be run, if the client does not already have an active screening applied.
The second method of automated screenings can be run when importing a company.
All automated screenings are using your account’s default screening settings.
The manual screening can be created on the specific entity profile, company or person.
The standard screening will follow the setup of the workspace. You can choose to override the default screening settings but toggling the ‘Custom’ search settings. Here you can change all of the settings for the specific screening.
Please also note that you need to screen each entity separately. So if you want to fully screen a company with two beneficial owners, then you need a total of three screenings. This is handled automatically when using the automated screening functionality.
How can I reduce the amount of false-positive matches with a screening?
There are a couple of parameters that you can tweak to limit the amount of false positives while still getting the correct match. There are three parameters that you can adjust:
- Fuzziness
- Match types
- Birth year (if person)
Fuzziness is determining how specific a name match should be. When evaluating a search result, the following parameters are involved:
- Variations in spelling: Names can be spelled differently due to transliterations, typographical errors, or cultural variations. For example, "Mohammad" can also be spelled "Muhammad" or "Mohamed."
- Phonetic similarities: Names that sound alike but are spelled differently, such as "Smith" and "Smyth," require fuzzy matching techniques to be accurately identified.
- Abbreviations and nicknames: People often use shortened versions of their names. For example, "Robert" might appear as "Bob," and "Alexander" might be "Alex."
Fuzziness is a value between 0 and 1. The higher the fuzziness, the broader the search. If a search is giving too many false-positives, then you can consider reducing the fuzziness and thus narrowing the search.
Be careful with setting a default fuzziness value that is too low. It is a balancing act between consistently reducing the amount of false-positives and not missing a potential true-positive match.
Match types are simpler, and is essentially a filter on which match types you are looking for. With match types you can define if you are only screening for PEP + sanction lists or if you are also checking for adverse media matches. You can also limit the amount of adverse media matches to only be the areas that you deem necessary to screen for.
Birth year is probably the most effective way to reduce the amount of false-positives when doing a PEP, sanction lists and adverse media screening. Using a person’s birth year will remove all hits where the birth year has a difference of more than one year. Note that this means that a birth year filtering for e.g. 1967 will include results born in 1966 and 1968.
Where can I set the default screening settings for my workspace account?
You can set up your workspaces screening settings if you are the Admin or Owner of the workspace. To do so, simply follow this link or navigate to Administration → Screenings.
