Senzing’s non-obvious relationship linking now available as a service on RegTech One platform
AML Partners is pleased to announce a new strategic partnership with Senzing, the first real-time, purpose-built AI for entity resolution, which is crucial to AML and fighting financial crimes. The Senzing® softare for non-obvious relationship linking, and entity resolution, is now available as a platform service on AML Partners’ RegTech OneTM platform for RegTech applications.
Senzing describes itself as a technology to discover “who is who in your big data.” In addition to its relationship-awareness capabilities and entity-centric learning, the AI in Senzing is both self-correcting and dirty-data tolerant.
AML Partners CEO Frank Cummings praises the capabilities of Senzing, its ease of use, and its tremendous utility in the fight against money laundering and other financial crime. With Senzing now available as a platform service on RegTech One, institutions using RegTech One to create their own Networks of Applications and Ecosystems of Data can now point the Senzing AI at their various datasets. With Senzing as a service on RegTech One, institutions can now automate the revealing and flagging of non-obvious relationships and other entity-resolution concerns that exist in their Ecosystems of Data.
“There are a couple of big competitive advantages gained by having Senzing as a platform service on RegTech One,” Cummings said. “Senzing searches your data sets—both structured and semi-structured—for non-obvious relationships. For example, you can see in all of your payments if an intermediary is tied to someone on a sanctions list—even if that ‘someone’ is listed way down below not as an individual but as an owner of a sanctioned company.”
Cummings notes that “the discovered/hidden linking happens automatically through Senzing, and the beautiful thing about it is that it discovers unseen graphs.”
With Senzing on RegTech One, institutions can pull down ownership from semi-structured documents. Identifying Politically Exposed Persons (PEPs) is a prime example of the value of this feature. A PEP might appear in one database but not in another, Cummings said.
“Senzing picks that up and you see the link,” he said. “This could not be done before—Senzing has created the solution for this problem. This non-obvious relationship linking is a technology that is a killer to money laundering.”
“We’re thrilled to team up with AML Partners and join forces in catching bad guys together,” said Jeff Jonas, Founder and CEO, Senzing.
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