AML screening

Ensure that your applicants do not pose a money laundering threat to your organization.

AML screening is intended to ensure that none of the applicants—both physical and legal—verified by Sumsub pose a money laundering threat to your organization.

If AML screening is enabled, Sumsub will screen through a variety of public and proprietary sources (watchlists, sanctions lists, adverse media, etc.) to find an entity with a fully or partly matching applicant’s full name and date of birth.

How it works

AML screening consists of 3 steps:

Data extraction

There are two types of watchlist screening:

  • Information-based. Textual data, such as the applicant name and date of birth received from the applicant is matched against a comprehensive set of watchlists in order to find/exclude a match.
  • Document-based. The name and date of birth are extracted from the identity document that was uploaded by the applicant.

In both cases, fuzzy logic is involved to ensure that no spelling variations of the applicant’s name are overlooked.

Watchlist screening

The watchlist screening helps find applicants that are:

  • Known or suspected terrorists
  • Sanctioned persons
  • Politically exposed persons (PEPs)
  • Persons with criminal background
  • Persons mentioned in adverse media

The potentially matching data from various sanctions and watchlists is compared against the applicant profile to establish a match. Below you will find a list of matches available in Sumsub.

Match typeDescription
True positiveApplicant data exactly matches one or several watchlist records. Full DOB of the applicant along with their name matches one or several watchlist records, but middle name omitted/abbreviated.
Potential matchName of the applicant matches one or several watchlist records, but the age/year of birth data is missing or the applicant is suspected of committing a crime. When two of three words in the applicant name match one or several watchlist records, along with their year of birth or age.
False positiveApplicant data doesn't match the source, or it matches, but the context clearly shows the person doesn't pose any threat.
UnknownApplicant name in the document contains only one word. There can also be cases with the matching applicant common name and abundance of matches. In such tricky cases the Sumsub client makes the final decision regarding the applicant.

Match processing

Applicants with False positive statuses are automatically approved; all the rest are either declined or assigned the Requires action status and then delegated to the client compliance officers for further processing.

Here are some examples:

CaseStatusNext action
The applicant name is not found in any of the sources.N/AThe applicant is automatically approved.
Applicant data exactly matches in one or several watchlist records.True positiveThe applicant is either declined or assigned the Requires action status and then delegated to the client compliance officers for further processing. The action depends on the customer settings.
Applicant data matches the watchlist record, but the record does not include criminal or suspicious information about the person. For example, if the applicant is a crime journalist, and their name features on the article as an author.False positiveThe applicant is assigned the Approved status.
Applicant data matches the watchlist record exactly, but additional information clearly shows that the applicant and the person on the record are different people.False positiveThe applicant is assigned the Approved status.
Name of the applicant matches one or several watchlist records, but the age/year of birth data is missing, or the applicant is suspected of committing a crime.Potential matchThe applicant is assigned the Declined status or Requires action status and then delegated to the client compliance officers for further processing.
The applicant name contains just one word.
There can also be cases with the matching applicant common name and abundance of matches.
UnknownThe applicant is assigned the Declined status or Requires action status and then delegated to the client compliance officers for further processing.

Examples

  • False positive. The applicant name match one or several watchlist records, but their DOB/age is different.
  • True positive. The applicant name partially matches one or several watchlist records and DOB/age matches these too, but the middle name is abbreviated.
  • Potential match. Two of three words in the applicant full name match one or several watchlist records, and their DOB/age matches these too.

If applicants are declined based on a watchlist match, they are assigned a respective rejection tag depending on the source where the match was found:

  • Sanctions
  • PEP
  • Criminal records
  • Adverse Media
  • On demand, the system can be set to delegate borderline cases to the client compliance officers for manual processing.

Ongoing AML monitoring

Ongoing AML monitoring is a process introduced by organizations to ensure that their business relationships are consistent. This keeps information about applicants up-to-date with the changes to sanction lists and watchlists across the globe.

We update our data as soon as the changes are made to the sanctions lists and watchlists. This lets you get reliable data from trustworthy sources, reducing manual labor and protecting your business from crime.

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Attention

Changes in your regulation settings affect ongoing AML monitoring results. For example, if you change the types of PEPs that should be declined by the system, some of the approved applicants might be declined as well.

Fuzzy matching

An effective screening system relies on both exact and inexact name matching for accurate identification as fraudsters often transpose names and other data trying to conceal their true identity.

Fuzzy matching is a technology that identifies spelling variations of the names and other search terms in case a character was omitted, inserted, or replaced either occasionally or on purpose.

Fuzzy logic capabilities

Apart from catching spelling errors, fuzzy logic is extremely helpful for screening names that have been transliterated from the non-Latin scripts. This lets you avoid missing true positives due to geographic, cultural differences, or other differences, such as:

  • Transcription variations, e.g. Husain, Hussein.
  • Homophones (equivalent pronunciation), e.g. Jaqueline, Jacklyn.
  • Phonetic matching, e.g. Irbah, Ibra.
  • Hypocorisms (shortenings), e.g. James / Jimmy / Jim.
  • Common abbreviations (for entities), e.g. ‘Ltd’ instead of ‘Limited’.

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Note

Fuzziness is not performed on non-Latin characters.

How do we cope with false positives

A false positive is a screening result that the system considers a match but in reality, it is not. To cut false positives to a minimum, we capped the maximum edit distance change at one character.

Manage fuzzy matching results

The fuzzy matching results are located in the Watchlists section of the applicant profile and are marked as Fuzzy match. The Name column lists all potential applicant name matches found in various watchlists and adverse media.

If you disagree with the fuzzy matching results, you can change the status of the match in the corresponding column to False positive.

AML data sources and refreshment times

Watchlist screening is an integral part of an AML check. The potentially matching data from various sanctions and watchlists is compared against the applicant profile to establish a match.

Watchlists are databases containing lists that businesses use for regular identity checks against known or suspected terrorists, money launderers, fraudsters, sanctioned persons, or PEPs.

Currently, Sumsub uses data from 10,000 independent and reliable data sources from 200+ countries and territories to ensure compliance with all local and global standards. These sources include:

  • The Office of Foreign Assets Control (OFAC) Sanctions
  • The United Nations Security Council’s Sanctions list
  • Her Majesty’s (HM) Treasury List
  • The EU Consolidated Sanctions List
  • The EU Most Wanted Warnings
  • The Bureau of Industry and Security
  • The State Department Foreign Terrorist Organizations List and Non-Proliferation List
  • US DOJ (FBI, DEA, US Marshals, and others)
  • Interpol’s Most Wanted
  • CBI List (The Central Bureau of Investigation)

We also offer an ongoing monitoring option that notifies the client each time their applicant status regarding AML screening changes.

We update our data as soon as the changes are made to the sanctions lists and watchlists, and we use Fuzzy matching to reduce false positives, at the same time making sure no name variations are omitted upon screening.

This lets you get reliable data from trustworthy sources, reduce manual labor and protect your business from potential fraudsters and risky users.

The following table explains refreshment time per data type.

Type of data (source)When the data gets to Sumsub
Adverse media (negative news)Within 48 hours after publication on the referral website.
Sanctions and watchlistsWithin 15 minutes after publication on the source website.
Politically exposed persons (PEPs)Within 1 day after the source database update.
National warning lists (For example, EU Most Wanted warnings)Within 1 day after the source database update.
Fitness and probity (senior employees competence) watchlistsWithin 1 day after the source database update.

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Applicable to Politically exposed persons (PEPs), National warning lists, and Fitness and probity

All data sources run on monthly intervals which means that the maximum time it takes from the moment a source updates to the moment it is in our database is one month, however it exceeds two weeks rather seldom.

Configure AML screening

To set up the AML screening process:

  1. Open the AML Screening settings and choose a provider that you want to use for AML screening. If the provider is locked, enter your credentials, as described in Comply advantage and World-check one
  2. Define whether to monitor applicants against sanction lists, watchlists, and/or if they are not compliant with the Standards of the Fitness and Probity Regime.
  3. Specify categories of PEPs for which you want to screen your applicants.
  4. Add types of adverse media associated with your applicants.
  5. Select how strictly the name matching should be performed.
  6. Enable Ongoing AML Monitoring to be informed on any changes in sanctions and watchlists concerning your applicants.
  7. Enable auto-screening for AML to monitor applicant profiles for one year after the initial check has been completed. If an issue is detected, the applicant will be rejected. You can also instruct the system to automatically assign applicants to compliance officers for a manual review and monitor applicants for an unlimited period of time.
  8. Save your changes.

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Note

To enable Ongoing AML Monitoring, contact your Customer Success Manager.

Interpret AML screening results

The results of the AML check are located In the Watchlists section of the applicant profile, where you can see various metrics, such as the date and time when the screening was performed, the applicant name along with their date of birth, search reference that was used during the screening, fuzziness interval, and whether the ongoing monitoring was enabled. You can also leave a note to preserve some useful information about the screening results.

Depending on the screening results, the status timestamp is highlighted in different colors:

  • Green — no matches were found in the watchlists; the applicant can be approved (or is already approved).
  • Yellow — matches in the watchlists are found, and require investigation.
  • Red — matches in the watchlists are found. Thoroughly investigate check results if you want to approve the applicant despite the found matches.

You may have several timestamps—each showing its own results—in case of several WL checks performed at different times.

Screening parameters

The following screening parameters are available, depending on the check result. Usually, less parameters are shown if the result is green.

ParameterDescription
Search termName of the screened person.
Created atDate and time when the screening was performed.
Search refSearch ID on the Comply Advantage (our AML screening provider) side.
Fuzziness IntervalA customizable value which defines how many inexact matches can be found during the WL screening.
Year of birthBirth date of the screened person.
Ongoing monitoringIndicates if the ongoing AML monitoring is on/off.
Last screening dateDate when the screening was last performed.
Warning typesTypes of matches configured in the settings. Hover the mouse cursor over the question mark to view, or click the link to open the settings in a new tab.

Watchlist (AML) screening report

To view the full report or download it as a PDF file click View Report.

Field

Description

Name

Names and birth dates of people with the same or similar name mentioned in any public sources in a negative context for the Watchlist check and their statuses as individuals or legal entities.

Matches

One or more labels indicating the reasons why the user with the same data is mentioned in the source. For example, Adverse Media, Sanction, PEP, Fitness probity, Warning and others.

Click a label to view the list of sources — the links you can follow to investigate additional information. A label does not always strictly correspond to a WL category, the context should be considered as well.

Relevance

Indicates the name relevance degree in the found source with the name of your applicant. For example, it can be Exact name match, Aka exact match, Equivalent name, Fuzzy match, Date/year of birth match, Unknown, Name variations removal and so on.

Countries

Countries the found matches are related to.

Whitelisted

Indicates if the found match is whitelisted or not. Possible options:

  • On — whitelisted.
  • Off — not whitelisted.
  • Empty — no data.

Match status

Indicates the found match status that correlates with the screening parameters.

Risk level

Risk degree that a found match represents. Possible options are:

  • Unknown — When it is not obvious which risk level to choose.
  • Low
  • Medium
  • High

If the Risk level field is empty, you can manually assign the risk level to the match.

Additional Info

Auxiliary information that can be used as an addition:

  • ID — the match ID on the Comply Advantage side; internal parameter for communication with the provider.
  • Status — the status of the WL check results review.
  • Review date and time
  • Reviewer login
  • View/Edit note — click to view and/or edit (create) a note. For example, you approved the earlier rejected applicant and you want your team to know why.

Manage AML screening results

If an applicant was delegated to you after the AML screening in accordance with your settings or you disagree with the system decision, you may need to investigate their profile and make a final decision according to your business requirements.

Approve applicants rejected after WL check

To approve applicants rejected during the screening:

  1. Go to the Applicants page.
  2. In the table, find and open the applicant profile you need.
  3. Click Check manually.
  4. Review the profile and navigate to the Watchlists section.
  5. In case of several WL checks performed at different times, go through each timestamp to see and study its results.
  6. Click the applicant record in the table to investigate the sources where the matches were found as per selected timestamp.
  7. Change parameters to those in which you are sure they must be in the following fields: is whitelisted, Match status, Risk level.
  8. Deselect the assigned rejection tags and click Approve.

Remove watchlist check results

You can remove the screening results for each of the timestamps:

  1. Select the timestamp the results of which you want to remove.
  2. Click the trash icon on the right.