Abstract: Methods and apparatuses for dynamic data normalization and duplicate analysis include normalizing data (e.g., merchant identifier data) received from a source entity (e.g., transaction card provider), as well as identifying and resolving potential duplicate transaction data objects based on one or more transaction characteristics. For example, data normalization includes partitioning an identifier into one or more merchant identifier portions, sending a merchant identifier request to a merchant database, and receiving a set of merchant representation candidates in response to sending the merchant identifier request. Further, for instance, duplicate analysis includes determining whether a transaction data object from the first set of transaction data objects that falls within the overlapping portion is not present in the second set of transaction data objects, and identifying the transaction data object within the second set of transaction data objects and the one or more non-overlapping portions.

Abstract: Methods and apparatuses for dynamic data normalization and duplicate analysis include normalizing data (e.g., merchant identifier data) received from a source entity (e.g., transaction card provider), as well as identifying and resolving potential duplicate transaction data objects based on one or more transaction characteristics. For example, data normalization includes partitioning an identifier into one or more merchant identifier portions, sending a merchant identifier request to a merchant database, and receiving a set of merchant representation candidates in response to sending the merchant identifier request. Further, for instance, duplicate analysis includes determining whether a transaction data object from the first set of transaction data objects that falls within the overlapping portion is not present in the second set of transaction data objects, and identifying the transaction data object within the second set of transaction data objects and the one or more non-overlapping portions.

Abstract: Methods and apparatuses for dynamic data normalization and duplicate analysis include normalizing data (e.g., merchant identifier data) received from a source entity (e.g., transaction card provider), as well as identifying and resolving potential duplicate transaction data objects based on one or more transaction characteristics. For example, data normalization includes partitioning an identifier into one or more merchant identifier portions, sending a merchant identifier request to a merchant database, and receiving a set of merchant representation candidates in response to sending the merchant identifier request. Further, for instance, duplicate analysis includes determining whether a transaction data object from the first set of transaction data objects that falls within the overlapping portion is not present in the second set of transaction data objects, and identifying the transaction data object within the second set of transaction data objects and the one or more non-overlapping portions.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.

Abstract: Methods and apparatus for adaptive expense processing and management include receiving and generating expense data objects, performing one or more expense processing and/or management procedures, adjusting/updating expense data from a first set to a second set for use in an autonomous expense procedure, and generating one or more additional or subsequent expense data objects based on the second set of expense data. For example, one or more account formation characteristics may be determined during an account formation procedure. Further, a merchant identity procedure may be performed. Additionally, the methods and apparatus may perform an expense category estimation procedure. The methods and apparatus may also determine a duplicate expense data object and perform an expense resolution procedure.