Financial Crimes Risk Assessment

Quantifind enables financial crimes investigators and analysts to make better decisions, faster, with intelligent automation.

Quantifind’s bulk processing technology uses a unique combination of external data sources and predictive risk typology models to inform the risk level of a person or an organization. Our entity searches employ a wide variety of data sources including sanctions and blacklists, negative news, social media, and real-time search engine results. Findings are then further refined using entity resolution and predictive models, highlighting high-risk entities while eliminating any false positives.

Through our partnership with Snowflake, you’ll be able to run risk assessments on any entities data stored in Snowflake in a private and secure manner.

How this works:

Gather entity (person or organization) information (supported fields are listed below):

external_id //an id used to identify the entity, mandatory
entityType //can be either "organization" or "person", mandatory
firstName //first name of a "person" entity, mandatory
middleName //middle name of a "person" entity, optional
lastName //first name of a "person" entity, mandatory
orgName //name of an "organization" entity, mandatory
city //address information: city, optional
state //address information: state, optional
country //address information: country, optional
birthDate //birth date of a "person" entity, optional
employer //employer of a "person" entity, optional

Follow the steps in the documentation to:
1. Create a table with the above entity information
2. Share the table with Quantifind to start the risk assessment
3. Prepare a table to store the Quantifind results
4. When the processing is done, execute query to view results