Quantifind Joins the Snowflake Data Marketplace

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Jun 24, 2020, 15:45 ET

MENLO PARK, Calif., June 24, 2020 /PRNewswire/ -- Quantifind announced today that it is joining the Snowflake Data Marketplace, enabling financial services customers of Snowflake's cloud data platform to seamlessly run customer and counterparty risk assessments in a private, secure, and efficient manner.

Quantifind's proprietary cloud-enabled technology uses a combination of public-domain data sources, best-in-class entity resolution, and predictive risk typology models to build accurate risk profiles on the fly for individuals and organizations alike. In this integration, mutual customers will have direct access to Quantifind's Batch Search API from within the Snowflake platform, allowing them to build new secure and automated Customer Due Diligence (CDD) workflows.

"We're thrilled to be partnering with Quantifind to help our financial services customers mitigate risks in their operations," says Justin Langseth, Vice President of Snowflake Data Marketplace. "The combination of Snowflake's world-class data platform capabilities with Quantifind's innovative technology in the anti-financial crimes space can provide a valuable service to our joint customers."

"As financial services firms continue their migration of data storage and back-office services to the cloud, we believe there is a great opportunity to meet them where they are and help them reap the benefits of this transformative change," says Ari Tuchman, CEO and Co-Founder of Quantifind. "With this integration, Snowflake and Quantifind mutual customers will be able to stand up new, more efficient and secure anti-money laundering and fraud risk mitigation processes without ever transferring any data or executing a costly implementation program."

About Quantifind:

Quantifind is a technology company whose AI platform uncovers risk signals across disparate and unstructured text sources. In financial crimes risk management, Quantifind provides an AI solution for anti-money laundering and fraud detection that uniquely discovers risk by combining internal financial institution data with public domain data. At a time when false positive transaction-based Alerts are pushing compliance costs higher and further straining investigative workforces, a Quantifind implementation can help realize a 30% efficiency gain.

SOURCE Quantifind