Abstract: Computer-implemented method for entity standardization that includes: inputting unstructured transaction data corresponding to a financial transaction to a natural language processor (NLP) to generate NLP output comprising a portion of the unstructured transaction data; inputting the NLP output to an entity service; inputting a recurring transaction indicator to the entity service; based on the NLP output and the recurring transaction indicator, generating a probabilistic confidence indicator via the entity service, the probabilistic confidence indicator meeting or exceeding a threshold for standardized matching of an entity to the financial transaction; and, based on the probabilistic confidence indicator, associating the entity with one or more of the financial transaction and the NLP output in an entity identification database.

Abstract: Computer-implemented method for entity standardization that includes: inputting unstructured transaction data corresponding to a financial transaction to a natural language processor (NLP) to generate NLP output comprising a portion of the unstructured transaction data; based on the NLP output, generating a probabilistic confidence indicator via an entity service, the probabilistic confidence indicator matching an entity to the financial transaction; receiving input from the account holder relating the entity to one or both of the NLP output and the financial transaction; and, based on the input from the account holder, associating the entity with one or both of the financial transaction and the NLP output in an entity identification database.

Abstract: Computer-implemented method for entity standardization that includes: inputting unstructured transaction data corresponding to a financial transaction to a natural language processor (NLP) to generate NLP output comprising a portion of the unstructured transaction data; inputting the NLP output to an entity service; inputting entity feedback data to the entity service; based on the NLP output and the entity feedback data, generating a probabilistic confidence indicator via the entity service, the probabilistic confidence indicator meeting or exceeding a threshold for standardized matching of an entity to the financial transaction; and, based on the probabilistic confidence indicator (i) associating the entity with one or more of the financial transaction and the NLP output in an entity identification database, and (ii) configuring a lookup table to deterministically identify the entity in connection with a second financial transaction based on the NLP output.