Improved Graphyte Solution Will Intelligently Link Open Source Data into a Knowledge Graph for Risk and Threat Management
Quantifind, a provider of a SaaS platform used to automate financial crimes investigations and screening, announced that it received a contract from the Defense Innovation Unit (DIU), an organization within the U.S. Department of Defense. The contract will accelerate development of Quantifind’s risk assessment capabilities beyond financial crimes, while also funding development of its knowledge graph technology to intelligently link vast amounts of complex structured and unstructured data into a single integrated framework.
Organizations throughout government and industry are regularly exposed to risks associated with particular individuals, companies, and their networks, but the information connecting these entities is often scattered across a large array of data sources. Quantifind’s platform integrates a rich trove of open source and proprietary data and leverages AI to perform entity linking and risk detection at scale. It can efficiently identify those data records most likely to refer to an entity of interest and discover signals indicating a variety of risk factors.
“Having established Quantifind’s technology in the banking world, we’re excited to partner with DIU to address the government vertical,” said John Stockton, Quantifind Co-Founder and public sector projects lead. “Fighting malign activity has always been a joint public and private effort, so we think of this initiative as a natural extension of our prior work, and we anticipate significant development alignment between the verticals. Our platform can be quickly configured for defense and law enforcement use cases with customized data sets and risks, and the graph technology that we are building will unlock much more powerful versions of what we do today, resulting in ‘forest versus trees’ types of insights.”
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Quantifind’s GraphyteSearch™ product responds to name queries in real-time with identity match confidence levels and signals of risk, including money laundering and fraud. The new knowledge graph, developed in partnership with DIU, will pre-compute entity links, relationships, metadata, and risks into a single schema, unifying data sets as distinct as structured corporate registrations and unstructured text from news articles. The integrated graph and underlying machine learning models will automate the production of insights to populate the intelligence collection funnel, with alerts based on graph algorithms including pathfinding, network identification, and anomaly detection. For more information, email Quantifind at public@quantifind.com.
