Abstract: Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Abstract: Systems, apparatus, and methods for determining incentives based on consumer history. When, how, and to whom incentives are sent can be determined. For example, an incentive can be sent to a consumer to encourage a transaction at a time when the particular consumer is predisposed to initiate the transaction. Also, an incentive for a transaction can be sent to a consumer when that transaction has a high likelihood of leading to other transactions. An incentive can also be sent after a consumer initiates a transaction that is known to not have many subsequent transaction correlated to it.

Abstract: Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Abstract: Systems, apparatus, and methods for determining incentives based on consumer history. When, how, and to whom incentives are sent can be determined. For example, an incentive can be sent to a consumer to encourage a transaction at a time when the particular consumer is predisposed to initiate the transaction. Also, an incentive for a transaction can be sent to a consumer when that transaction has a high likelihood of leading to other transactions. An incentive can also be sent after a consumer initiates a transaction that is known to not have many subsequent transaction correlated to it.

Abstract: Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Abstract: Systems, apparatus, and methods for determining incentives based on consumer history. When, how, and to whom incentives are sent can be determined. For example, an incentive can be sent to a consumer to encourage a transaction at a time when the particular consumer is predisposed to initiate the transaction. Also, an incentive for a transaction can be sent to a consumer when that transaction has a high likelihood of leading to other transactions. An incentive can also be sent after a consumer initiates a transaction that is known to not have many subsequent transaction correlated to it.

Abstract: Methods, apparatus, and systems are provided for tracking and analyzing data of consumer activity. The tracked data can be organized (e.g. as stored in cache, RAM, hard drives) in certain types of tables, where the tables can be associated with certain tags (keys) for efficiently accessing the data. The organization and associations of the data can also provide simple mechanisms for manipulating the data to obtain results specifically relevant for a task, such as detection of fraud or prediction of consumer behavior to provide better customer service or new services. For example, the tables may contain counters that store the number of times that two correlated consumer events occur within specific time intervals of each other. Such time data can provide efficient determination of patterns of consumer activity.

Abstract: Embodiments of the invention is directed to a dynamic network analytics system capable of receiving and analyzing queries sent in data messages from data requesters. The queries contain a request from the data requester as to a risk level associated with an interaction conducted by a user. The dynamic network analytics system can determine an optimized process for determining the risk level of the interaction, based on an analysis of past interactions by the user and past interactions by users similar to the user. The dynamic network analytics system can retrieve data from internal and external data sources to generate a response to the query. The dynamic network analytics system conducts the optimized process and uses the retrieved data to generate risk assessments and risk scores in response to the query from the data requester.

Abstract: Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Abstract: The GRADUATED SECURITY SEASONING APPARATUSES, METHODS AND SYSTEMS (“GSS”) transform user virtual wallet activity and historical fraud reports via GSS components into transaction authorization triggers generated pursuant to graduated, transaction risk-appropriate, escalated security protocols. In one implementation, the GSS obtains a current transaction request, the request utilizing a user virtual wallet account for payment. The GSS identifies a transaction risk type associated with the request, and calculates a transaction risk level associated with the transaction risk type. Based on the transaction risk level, the GSS selects a security protocol for processing the current transaction request; and provide a security data request in accordance with the selected security protocol.

Abstract: The SOCIAL NETWORK PAYMENT AUTHENTICATION APPARATUSES, METHODS AND SYSTEMS (“SNPA”) transform social networking user login inputs via SNPA components into notifications of authenticated purchase transactions. In one embodiment, the SNPA obtains an authentication request for a purchase transaction. The SNPA extracts card account data related to the authentication request, and provides the card account data related to the authentication request to a social networking server. The SNPA also provides an indication for a user to authenticate via logging into a social networking service associated with the social networking server. The SNPA obtains an indication from the social networking server that the user is authenticated. In response to obtaining the indication that the user is authenticated, the SNPA initiates completion of the purchase transaction.

Abstract: Embodiments of the invention is directed to a dynamic network analytics system capable of receiving and analyzing queries sent in data messages from data requesters. The queries contain a request from the data requester as to a risk level associated with an interaction conducted by a user. The dynamic network analytics system can determine an optimized process for determining the risk level of the interaction, based on an analysis of past interactions by the user and past interactions by users similar to the user. The dynamic network analytics system can retrieve data from internal and external data sources to generate a response to the query. The dynamic network analytics system conducts the optimized process and uses the retrieved data to generate risk assessments and risk scores in response to the query from the data requester.

Abstract: Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Abstract: Systems and methods are provided that empowers various parties to combine transactional data and local non-transactional data using the collective intelligence gathered from a variety of sources to help the parties make more intelligent decisions relating to consumers. For example, the system can help select consumers based on the probability that the consumers will take advantage of an offer, coupon, or other item. In some embodiments, the present invention can be deployed as a part of a system that processes transactions. In this system, information associated with the transactions is analyzed in conjunction with non-transactional data in order to probabilistically determine whether a further action should be taken with the consumer.

Abstract: Systems, apparatus, and methods for determining incentives based on consumer history. When, how, and to whom incentives are sent can be determined. For example, an incentive can be sent to a consumer to encourage a transaction at a time when the particular consumer is predisposed to initiate the transaction. Also, an incentive for a transaction can be sent to a consumer when that transaction has a high likelihood of leading to other transactions. An incentive can also be sent after a consumer initiates a transaction that is known to not have many subsequent transaction correlated to it.

Abstract: Systems, apparatus, and methods for determining groups of similar consumers and for identifying a trend in consumer behavior are provided. Likelihoods of a transaction being initiated at various times by one consumer can be calculated based on previous transactions of the consumer. The likelihoods for different consumers can be used to determine a group of similar consumers as a demographic. The likelihoods of a transaction being initiated at various times by a consumer of a demographic (or other entity) can be used to forecast trends (such as a demand for a product) and make business decisions, such as for marketing campaigns, inventory levels (e.g. at particular stores or for all stores), pricing, and store locations. Such likelihoods when focused to a particular category of transactions can provide even greater accuracy.

Abstract: Systems, apparatus, and methods are provided for efficiently authorizing a transaction initiated by a consumer. An authorization can be generated before the consumer actually initiates the transaction. For example, a future transaction can be predicted, and an authorization can be generated for the predicted transaction. In this manner, the authorization can be ready and quickly used when the consumer does initiate the transaction. Previous transactions made by the consumer can be used to predict when the future transaction is likely. In various examples, the authorization can be sent to a specific merchant or to the consumer for use when the consumer initiates the predicted transaction, or saved by an authorization server for use in response to an authorization request from the merchant.

Abstract: Methods, apparatus, and systems are provided for tracking and analyzing data of consumer activity. The tracked data can be organized (e.g. as stored in cache, RAM, hard drives) in certain types of tables, where the tables can be associated with certain tags (keys) for efficiently accessing the data. The organization and associations of the data can also provide simple mechanisms for manipulating the data to obtain results specifically relevant for a task, such as detection of fraud or prediction of consumer behavior to provide better customer service or new services. For example, the tables may contain counters that store the number of times that two correlated consumer events occur within specific time intervals of each other. Such time data can provide efficient determination of patterns of consumer activity.

Abstract: Systems, apparatus, and methods for authorizing a transaction initiated by a consumer are provided. A likelihood function can approximate a pattern of previous transactions and provide a measure of how likely it is for a transaction to occur as a function of time. The time of a current transaction can be used to determine a corresponding likelihood value of a likelihood function associated with the transaction. The likelihood value can then be used to determine a score for authorizing the transaction. As the likelihood corresponds to a particular time of a pattern, the score can be tailored to the current transaction and achieve greater accuracy.

Abstract: Transaction scoring is performed in a distributed manner across a client-server computing system. A computing system for processing a transaction includes a server system and a client system. The server system is arranged to process information associated with the transaction, while the client system communicates with the server system and includes a key engine which is arranged to generate keys. The client system and the server system are arranged to cooperate to make probabilistic determinations associated with the transaction. The client is arranged to send the keys generated by the key engine as a transaction to the server system.