Quantifind: Financial Crimes Risk Assessment
Automated entity risk assessment for financial crimes investigation
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
3. When the processing is done, execute query to view results
Processing time varies based on the number of entities. The processing rate is 1000-2500 entity searches per hour.