Abstract: Embodiments provide methods and systems for recommending one or more authorizing components to issuers and/or merchants for enhancing approval rates of payment processing requests. Method performed by server system includes receiving a payment authorization request for a payment transaction between a cardholder and a merchant in real time. The method includes identifying payment transaction features associated with the payment transaction based, at least in part, on the payment authorization request. The method further includes predicting a combination of one or more authorizing components to be applied to the payment transaction to obtain a product recommendation strategy for the payment transaction. The combination of one or more authorizing components is predicted based, at least in part, on a trained machine learning model and the payment transaction features.

Abstract: Embodiments provide electronic methods and systems for facilitating payment authorization for payment transactions initiated from an on-board device of an autonomous vehicle. The method performed by a server system includes receiving payment transaction request initiated from on-board device positioned in autonomous vehicle. The method further includes accessing authentication parameters received from on-board device, wherein authentication parameters include multisensory data captured using sensors positioned in autonomous vehicle, and generating authentication features based on authentication parameters and neural network models. The neural network models are trained based on historical multisensory data of one or more autonomous vehicles.

Abstract: A method for detecting fraudulent transactions includes generation of a graph including a plurality of nodes and a plurality edges between the plurality of nodes based on historical transaction data of a plurality of historical transactions. The plurality of nodes include a set of merchant nodes and a set of consumer nodes. A set of static features and a plurality of dynamic features are determined based on the historical transaction data and the generated graph, respectively. A neural network is trained based on the set of static features and the plurality of dynamic features for detection of transaction fraud. The neural network is used to detect a first transaction as one of a fraudulent transaction or a legitimate transaction based on first transaction data of the first transaction.

Abstract: A method for facilitating entity resolution is provided. A server generates a graph based on a first dataset comprising a first entity and a second dataset comprising a plurality of entities. Each node in the generated graph corresponds to the first entity or one of the plurality of entities. The server generates a plurality of embeddings for the plurality of nodes in the generated graph. Each of the plurality of embeddings represents an entity as a point in a d-dimensional embedding space. The server identifies a set of nearest neighbors for the first entity based on the plurality of embeddings. The server determines a similarity metric for each of the identified nearest neighbor with respect to the first entity. The server associates the first entity with a second entity of the second dataset that corresponds to a nearest neighbor in the set of nearest neighbors.

Abstract: Embodiments provide anti-money laundering methods, and systems for detecting potential money laundering financial transactions using artificial intelligence. The method performed by a server system includes receiving data elements associated with financial activities of users who are associated with at least one issuer. The data elements include transaction data associated with users. The method includes identifying graph features based on data elements, and creating temporal knowledge graph based on the graph features. The temporal knowledge graph represents a computer-based graph representation of the users as nodes and relations among the nodes as edges.

Abstract: The invention enables optimizing performance of a recommendation server. The invention comprises (i) receiving a first set of customer information corresponding to a first set of events recorded in a first time period in which the recommendation server operates in a first configuration state, (ii) generating a first performance evaluation score based on the first set of customer information, (iii) reconfiguring the recommendation server to operate in a second configuration state having a second performance evaluation score associated therewith, and wherein said second performance evaluation score is generated based on a second set of customer information corresponding to a second set of events recorded in a second time period in which the recommendation server operates in the second configuration state and (iv) transmitting to a terminal device, one or more electronic offers selected for transmission to the customer by the recommendation server operating in the second configuration state.