Grid filters
Grid offers powerful filtering capabilities that can fine-tune screening results to match your firm’s unique business requirements.
A firm filter is composed of multiple filter expressions, which together serve to define the screening scope and exclusion rules for potential matches.
Grid filters and descriptions
The following table shows the filter name and its associated description.
Filter | Description |
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Alias score filter | Parameters: Numeric: a comparison operator and a numeric threshold to be compared with the alias score. The alias score filter can reduce false positives resulting from matches against partial aliases by considering the full set of names for a profile. This filter is feature-specific to person name matching and can only be applied to person inquiries. When used, in the search process a separate alias score, from 0 to 100, is produced for profiles that meet the primary match criteria but have multiple names/aliases that could potentially rule out the match. If the alias score falls below the threshold specified in the firm filter, that profile is filtered out of the results. The algorithm only considers profile names similar to the matched name so as to not rule out a match based on unique aliases. As an example, consider an inquiry for the name “James P. Smith” matched to a Grid profile containing the name “James Smith” and an alias “James R. Smith”. The inquiry matches the profile based on the name “James Smith.” However, the alias contains conflicting information because a different middle initial results in an alias score of zero, which allows the match to be filtered out. |
Bordering country filter | Parameters: None. The bordering country filter considers if the country or state in the inquiry matches any of the entity’s bordering countries. The filter only applies when there is a country available on both the inquiry and the matched entity. A bordering country is defined as two countries whose borders touch.
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Bordering state or province filter | Parameters: None. The bordering state or province filter considers if the inquiry name's state or province matches the entity’s bordering state or province. The filter only applies when there is a country and state or province available on both the inquiry and the matched entity. |
CVIP filter | Parameters: String: one or more CVIP codes. The CVIP (Critical, Valuable, Investigate, Probative) filter considers a firm's CVIP code for the entity match. The CVIP code is calculated at the entity level based on a firm's configured CVIP rule matrix, which is based on:
This filter is typically used to exclude entities whose CVIP code is unclassified (U), as that type of entity’s events are outside the screening scope defined by the CVIP rule matrix. |
Country match filter | Parameters: String: input in the Country field. The country match filter considers if the inquiry's country matches an entity’s country. This filter is typically used by Grid in tandem with the global search filter to ensure only non-global searches are filtered out when there is a country mismatch. The filter only applies when there is a country available on both the inquiry and the matched entity. Note Grid normalizes countries to the ISO standard. As part of the ISO standard, some countries are also considered provinces, and this is taken into account in this filter. |
Deceased filter | Parameters: None. The deceased filter considers if a matched person entity type is deceased, or has a date of death attribute. This filter can be used to exclude matches for deceased entities. |
DOB filter | Parameters: Numeric: the difference threshold between the two dates of birth, in years. The date of birth (DOB) filter computes the difference in years between the date of birth from the submitted inquiry and the date, or dates, of birth from the entity. This filter only applies to person entity type inquiries and is only applied if both the inquiry and entity names have dates of birth available. This filter can be used to exclude matches where the entity DOB is too different from the inquiry DOB. Commonly used are one year or two-year ranges. |
DOB year match filter | Parameters: None. The date of birth (DOB) year match filter considers if the year from the inquiry DOB exactly matches a year from the entity DOBs. This filter is only applied if both the inquiry and entity have dates of birth available. |
DOD filter | Parameters: Numeric: the difference threshold between the entity DOD and the current date, in years. The date of death (DOD) filter computes the difference in years between the date of death from the entity and the current date. This filter only applies to person entity type inquiries. This filter is only applied if the entity has a date of death available. |
Entity date filter | Parameters: Numeric: the difference threshold between the entity date and the current date, in years. The entity date is the most recent event date for all events associated with the entity. This filter is typically used to exclude older events from consideration, often in tandem with the event filter. Only recommended for use with firms not leveraging CVIP. |
Entity type filter | Parameters: String: P, O, or U. This filter considers the type of entity matched. The entity type can be a person (P), organization (O), or unclassified (U). This filter is typically used in tandem with other filters to impose different rules for entity type matching. |
Event filter | Parameters: String: a list of event category codes, also known as risk codes, and, optionally, subcategory codes, such as stages. This filter is based on event categories and sub-categories. |
Event date filter | Parameters: Numeric: the difference threshold between each event date and the current date, in years. The event date filter is based on an event date. Typically, the entity date filter is more useful. However, for special cases, the individual event dates may be considered. Only recommended for use with firms not leveraging CVIP |
Exact DOB filter | Parameters: None. The exact date of birth (DOB) filter considers whether the inquiry’s date of birth exactly matches one of the matched entity’s DOBs, if available. This filter is only applied if a date of birth is available on both the inquiry and entity. |
Geographic distance filter | Parameters: Numeric: A geographic distance radius, in miles. The geographic distance filter considers the distance between the address of the inquiry and the closest address of the matched entity. The distance is calculated based on latitude and longitude and not driving distance. The filter only applies if there are two geographical data points on both sides, and they can successfully be geocoded. This filter is typically used to exclude matches outside of a certain geographic radius, optionally in tandem with other filters. |
Global search filter | Parameters: None. The global search filter considers the optional inquiry setting, on or off, within an inquiry. This filter is always used in combination with other filters, such as the country match filter. |
iList filtering | Parameters: Configured with an alertable iList or a non-alertable, safe iList. When configured with an alertable iList or a non-alertable, safe iList, several iList match filters can be configured to impose special handling or to exclude matches when for the submitted name matches an iList entry, either in tandem with other filters. This includes filters on the matched iList name, and the iList match score. |
Inquiry name only filter | Parameters: None. This filter considers if the inquiry was a "name only" inquiry, where it did not specify an address or a date of birth. This would typically be used in tandem with other filters to impose different rules for inquiry-only names. |
Item source filter | Parameters: String: a list of item source keys. The item source filter considers the source for each matched entity/event. This is typically used to restrict the screening scope for monitored lists, or to exclude specific sources. |
Item type filter | Parameters: String: a list of item types. The item type filter considers the Item Type designation for each matched entity or event. The Item Type can be WEB, for monitored lists, or MEDIA, for news articles. This filter is typically used to include or exclude a type, or in tandem with other filters to impose different filtering rules based on the type. |
Knowledge tag filter | Parameters: String: one or more knowledge tags. The knowledge tag filter considers if the matched entity’s events contain knowledge tags that match a specified value or values. This filter can be used to include/exclude events that are in specially designated categories, such as #ElderFraud, #NonFinancialCrime, or #Ransomware. |
Match score filter | Parameters: Operator + Numeric: a comparison operator and a numeric threshold to be compared with the match score. The match score filter considers the match score for the entity match. The match score is an integer from 0 to 100 that the system assigns based on the quality of the match. This filter takes an argument of a comparison operator followed by a match score threshold. This filter is used frequently to exclude matches with scores below a certain threshold. This filter can also be used in tandem with other filters, such as event, to impose different thresholds for different types of matches. |
Name common in country filter | Parameters: None. The name common in country filter considers if the surname is common in the associated country. There are separate filters for the name common in country filter, which considers the inquiry surname and country, and the match name common in country filter, which considers the matched entity’s surname and countries. This filter is typically used in tandem with other filters, to impose stricter filters for common names. |
Name gender match probability filter | Parameters: Operator + Numeric: a comparison operator and a numeric threshold to be compared with the name gender match probability. The name gender match probability filter considers the likelihood that the inquiry's name and entity match name are the same gender. The logic considers only the given name for the inquiry and matched entity. The filter uses the probability of a gender match between the inquiry name and the entity name and filters out matches where the probability of a match is beneath the specified threshold. A threshold of 0.05 is the recommended setting and would indicate that the probability of a gender match, based on the name, is below 5%. |
PEP level filter | Parameters: String: one or more PEP Level codes. The politically exposed person (PEP) filter considers the PEP level for entities that have a PEP event. A PEP level depends on designation/position, as per the governmental hierarchy and the political master structure of the country. The level primarily ranges from 1 - 5, depending on the administrative division and government structure of the country, with level 1 denoting the highest seniority. Filtering by PEP level allows for optimization based on the seniority of the PEP. This filter is typically used to restrict the screening scope to only certain PEP Levels. This filter is frequently used in tandem with the PEP type filter. |
PEP level change | Parameters: PEP data is curated using information from multiple government, biographical, and reputable publicly available sources to create a comprehensive risk profile. Due to the large volume of PEP updates, portfolio monitoring alerts are only sent for newly added PEPs. Any new PEP profiles, or ADD/ADDs, are included in portfolio monitoring. Data is constantly being added to profiles to bolster existing PEP data, such as date of birth, address information, other prominent political positions, etc. Those minor changes are considered EDIT/EDITs and are not sent to portfolio monitoring. For example, if a new cabinet minister is appointed and has never held any other political position in their lifetime, that individual is considered a new PEP profile and added to Grid. If this cabinet minister previously held the position of supreme court judge, that individual is considered a modification to an existing PEP profile as the cabinet minister would have already had an active PEP profile in Grid for the supreme court position. There are occasions where an EDIT to a profile may be considered risk relevant, meaning, if a PEP were to move into a new political position with a new PEP type and level then the overall risk of that PEP may have changed, such as in the above example. To account for any changes to a PEP Type or level, Grid uses a configurable filter called portfolio monitoring PEP changes. This configurability allows our customers to opt in for alerts if a PEP changes a PEP Type or moves to a higher level. The filter only accounts for an increase in risk, so if a PEP were to move from a level 1 to a level 2 it would not be included in portfolio monitoring. |
PEP rating filter | Parameters: String: one or more PEP rating codes. The PEP rating filter considers the PEP score for entities that have a PEP event. PEP ratings can be:
This score is assigned to a PEP based on a proprietary scoring mechanism that accounts for position risk, country sovereign ratings, country corruption ratings, and relevant event risk. PEP rating filters are only available for batch inquiry screening, not portfolio monitoring. PEP ratings filters are not available for portfolio monitoring due to the additional risk information that could change the rating after entity consolidation. |
PEP to date filter and PEP from date filter | Parameters: Numeric: date difference threshold between the PEP to/from date and the current date, in years. The PEP to date filter considers the end date for a PEP event, and the PEP from date filter considers the start date for a PEP event. Many PEP events have from and to dates, where this filter can be used to restrict the screening scope based on these dates. Typically, the PEP to date filter is used to exclude older PEP events. |
PEP type filter | Parameters: String: one or more PEP Type codes. The PEP type filter considers PEP Type for entities that have a PEP event. This filter is typically used to restrict the screening scope to only certain types of PEPs. A PEP Type is a classification of PEPs at different levels, such as national, state, district, regional, and municipal, and within the country as per a governmental hierarchy. There are 17 PEP Types: HOS - Heads of state CAB - Cabinet officials INF - Senior officials overseeing key infrastructure sectors. NIO - Senior officials overseeing non-infrastructure sectors MUN - Municipal level officials. REG - Regional officials LEG - Senior legislative branch officials AMB - Ambassadors and top diplomatic officials MIL - Senior military officials JUD - Senior judicial officials POL - Political party officials GOE - Government Owned Enterprises (Organizations) GCO - Top executives/officers in state-controlled enterprises IGO - International Government Officials ISO - International Sporting Officials FAM - Family members ASC - Close associates and advisors Filtering by PEP Type allows specific categories of government bodies to be included in screening results. |
Related PEP attributes filtering | Parameters: The related PEP attributes filter considers the PEP attributes for any PEP entities related to the matched entity. An entity is related to a PEP entity if there is an association link of type family (FAM) or associated (ASC). All the same PEP attributes are available for all filters related to PEPs: PEP type, PEP Level, PEP rating, and to/from dates. |
Risk score filter | Parameters: Operator + Numeric: a comparison operator and a numeric threshold to be compared with the risk score. The risk score filter considers the risk score for the entity match. The risk score is an integer from 0 to 100 that the system assigns based on a formula involving the event category, item priority, and other fields. This filter takes an argument of a comparison operator followed by a risk score threshold. |
Search type filter | Parameters: String: LF for initial screening or LB for portfolio monitoring. The search type filter considers if the entity match resulted from onboarding/initial screening or from portfolio monitoring. This filter can be used to impose a different set of filtering rules for ongoing monitoring than was originally used for onboarding/initial screening. |
Sex match filter | Parameters: None. The sex match filter considers the sex attributes from the inquiry and the matched entity. Both API and Review Inquiry Batch (RIB) inquiry submissions allow a sex attribute to be provided for person inquiries. At present, either male (M) or female (F) are accepted for person name types. If provided, the inquiry is matched to an entity that also has a sex attribute value. This filter can be used to exclude matches where the values do not match. It can only be applied to person name inquiries where there is a sex attribute value available on both the inquiry and matched entity. |
State/province match filter | Parameters: None. The state/province match filter considers matches based on the inquiry's state/province. For a state/province to be considered a match, the country must also match. The filter only applies when there is a country and state/province available on both the inquiry and the matched entity. |
Variant match filters | Parameters: None. Variant match filters are available for person inquiries and consider matches based on a name variants. Those include:
These types of filters can be used in tandem with other filters to impose different rules for variant-based matches. |
Weak alias filtering | Parameters: Firm-level configuration setting. If configured for a firm, weak alias filtering excludes matches from sanctions watchlist screening results. The weak alias filtering process utilizes back-end Moody's technology and processes to capture weak or strong alias quality from the source. Inquiry names are then matched against profile data in the Grid database and a determination is made if the match in question should be included or excluded from results. Weak aliases can be identified as:
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