Abstract: An embodiment of the present invention is directed to developing Autonomous Fraud Risk Management to identify emerging fraud trends in near real-time and mitigate risk by executing strategies to address fraud in a timely manner.

Abstract: Systems and methods for risk diagnosis of cryptocurrency addresses on blockchains using anonymous and public information are disclosed. In one embodiment, a method may include a risk diagnosis computer program executed by a server: receiving data with labels and data without labels from public data databases and/or anonymous data databases; fitting the data without labels into a plurality of clusters using unsupervised learning; assigning a risk level to each of the plurality of clusters; verifying the risk level for each of the plurality of clusters using the data with labels; receiving unseen data; and predicting a risk level associated with the unseen data by constructing features and text embeddings from the unseen data, clustering the unseen data based on a distance measurement to one of the plurality of clusters, and returning a risk level associated with the cluster.

Abstract: A method for performing fact verification includes receiving a document for verification; identifying and extracting, on the computer network, at least two named entities from the document for verification and associated information as metadata; identifying, off-chain, identifiers of relevant documents corresponding to each of the at least two named entities, the relevant documents being authenticated documents including one or more of the at least two named entities; identifying a predetermined number of relevant documents among the identified relevant documents based on a number of the at least two named entities present and a number of occurrences for each of the named entities; and determining whether the document to be verified is supported by the predetermined number of relevant documents.

Abstract: Embodiments disclosed herein provide for systems and methods for secure logins using facial recognition with a blockchain-based verification system. The systems and methods provide for authentication, authorization, and secure storage of biometrics data. Authentication is performed with a machine learning system implementing the facial recognition. The biometrics data can be securely stored on a blockchain and used to perform the facial recognition during login. Authorization is provided with an active directory system.

Abstract: An embodiment of the present invention is directed to developing Autonomous Fraud Risk Management to identify emerging fraud trends in near real-time and mitigate risk by executing strategies to address fraud in a timely manner.

Abstract: Embodiments disclosed herein provide for systems and methods for secure logins using facial recognition with a blockchain-based verification system. The systems and methods provide for authentication, authorization, and secure storage of biometrics data. Authentication is performed with a machine learning system implementing the facial recognition. The biometrics data can be securely stored on a blockchain and used to perform the facial recognition during login. Authorization is provided with an active directory system.