Understanding Filters
Filters help you generate the most relevant alerts. They allow you to limit alerts to only specific sets of objects, like entities (users or businesses), transactions, account numbers, addresses, countries, etc.
Filters are available in the Scenario Model Builder. A funnel icon will appear that allows agents granular control of the model logic:
Filters offer granular control over fields
The following list outlines some of the configurable filters:
| Filter name | Description |
|---|---|
business | Business entity information such as tax ID, name or registered location |
entity | High level entity information such as status, tags, or type |
user | User entity information such as ssn, gender, name, or DOB |
ip address | IP address first or last seen by entity |
client fingerprint | Fingerprint first or last seen by entity |
address | Full address of an entity/event |
geolocation | Last known IP address of an entity/event |
Filters match for text and compare numbers
Put simply, filter expressions just check whether a value matches or doesn't match a different value.
In formal terms, these are called [boolean expressions (https://en.wikipedia.org/wiki/Boolean_expression).
| Expression | Filter in practice |
|---|---|
business/name == Acme | Only business named Acme |
business/name != Acme | Only business NOT named Acme |
txn_amount > 10000 | Only transactions greater than ten thousand |
txn_amount < 10000 | Only transactions less than ten thousand |
entity/registered_at BETWEEN 01.01.2020 and 01.02.2020 | Only entities that registered between these days |
entity/address is empty | Only entities without addresses |
entity/address is not empty | Only entities with addresses |
last_name like %Smith% | Only entities with names similar to Smith |
Use % when using the "Like" filter
When using
LikeorNot Like, be sure enclose%around the value. E.g, search for similarity with "ABC" using this%ABC%(see the following section for an example of a search)
Filters can be combined
You can also combine filters by using logical operators, like AND and NOT.
In this example we filters for entities:
- who have a
region:floridatag; - have a last name like Johnson AND have risk scores greater than 50 3) who DO NOT have empty SSNs.
Updated 7 months ago