Configure classification model

Classification model rules, thresholds, and stopwords define how a model processes a hit. When a name is run against hit providers, they return hit data. Based on the configured rules and thresholds, each hit is given a hit score that determines whether it should be treated as False Positive or escalated.

Rules

The NSS classification model applies rules to determine if a hit should be defined as False Positive. You can set the rules when configuring the NSS skill. For instructions, see Install and configure | Configure model.

You can set the model to apply the rules based on the following factors:

• Name: name of an individual or organization

• Location: country of present and past affiliation, ownership, or citizenship

• Date: date and year of birth for an individual or founding date and year for organizations

• Type: hit type; individual (PERSON) or organization (ENTITY)

• Gender: gender of an individual

Based on matching the hit data from providers against the input data, the NSS classification model can give the following outcomes:

• Strong match

• Weak mismatch

• Strong mismatch

• Not available, if no data is provided on either side

Thresholds

For each hit, the model provides a hit score. You can define thresholds on the minimum hit score needed for escalation when configuring the NSS skill. For instructions, see Install and configure | Configure model.

The following thresholds are available:

• Strong name match threshold: NSS considers a name to be a strong match if it is similar to a screened entity, at least, to the defined value.

• Strong name mismatch threshold: NSS considers a name to be a strong mismatch if it is different from a screened entity, at least, to the defined value.

• Strong date match threshold. NSS considers a date to be a strong match if the date is different from the screened one by not more than the specified amount of days.

• Strong date mismatch threshold. NSS considers a date to be a strong mismatch if the date is different from the screened one by at least the specified amount of days.

  • If both dates are provided in the MM/dd/YYYY format and the number of days between them is less than or equal to the configured threshold, the dates are considered a match or a mismatch based on the strong match or mismatch settings.
  • If at least one of the dates is not in the MM/dd/YYYY format, the dates are considered a match regardless of the day difference.

• Enable dates comparison by date type

• Enable locations comparison by location type

• Enable proximity matching

Stopwords

Stopwords are common words like "the," "and," or "is" that are typically excluded from the text analysis as they do not carry a significant meaning.

By default, the following categories of stopwords are filled in:

• Geographical: stopwords related to geographic terms
• Financial: stopwords related to financial terms
• Company: stopwords related to company-specific terms
• Miscellaneous: general stopwords that are not domain-specific

Consider the specific domain and context of your classification task when selecting stopwords. Mind that adding or removing stopwords can significantly affect the performance of the NSS Classification Model.

Default configuration

Rules

The decision matrix below describes the default rule configuration of the NSS classification model for Name, Location, and Date when a hit is marked as False Positive. In all other cases, the hit is escalated for further review.

Name	Location	Date	Type	Resolution
Strong mismatch				False Positive
		Strong mismatch		False Positive
			Strong mismatch	False Positive
Weak mismatch	Weak mismatch			False Positive
Weak mismatch		Weak mismatch		False Positive
	Weak mismatch	Weak mismatch		False Positive

note

If the comparison results are between the weak and strong factors, the model produces a Weak Mismatch outcome.

Thresholds

See the default threshold values in the table below:

Threshold	Default value
Strong name match threshold	0.8
Strong name mismatch threshold	0.75
Strong date match threshold	30
Strong date mismatch threshold	365

Model narrative

If the model's final decision is False Positive, the narrative can include:

• Only those rule factors that actually trigger the model to take a specific decision.
• All factors for strong match and weak mismatch.

If you want the model's decision narrative to include all factors for strong match and weak mismatch, select the Include all criteria in the decision narrative checkbox during configuration.

For instance, let's assume that the rule setup on the configuration screen is as follows:

• If the model's False Positive decision is triggered based on the value in the first row, the following lines appear in the model narrative:

  False Positive.
  Strong name mismatch (“{input_name}“, “{wle_name}“).

• If the model's final decision is Need more information, the narrative contains one Strong match and Week mismatch factors (if any):

  Please review manually. Not enough information to disposition.
  Strong name match (“{input_name}“, “{wle_name}“).