Abstract: Improved entity identification is provided. Reference data sourced from various data sources may be used to more accurately identify an individual to improve the ability for multiple transaction processing systems to more effectively match identities for the transmission, receipt, and linking of data records. Accordingly, various enterprises are enabled to communicate about a particular entity without each enterprise having the same identifier or having the same, accurate entity demographic information.

Abstract: Generating and providing match justifications in association with record matching results for improved record matching is provided. An entity resolution system generates a set of deterministic rules based on patterns of attribute comparison outcomes of known matched and unmatched records. Each rule includes matching conditions and an action instruction including a message of a justification for a match/non-match. The system receives a request to determine a match between two records. A matching engine compares various attributes of the records using probabilistic matching technologies to determine a match outcome. A justification engine compares attribute comparison outcomes to the stored rules. When the matching conditions of a rule are satisfied, the rule is activated and a human-readable justification is linked to the match output and provided in a match response. The justification provides insights into the match outcome, and improves the speed and accuracy of a verification process of the match output.

Abstract: Improved entity identification is provided. Reference data sourced from various data sources may be used to more accurately identify an individual to improve the ability for multiple transaction processing systems to more effectively match identities for the transmission, receipt, and linking of data records. Accordingly, various enterprises are enabled to communicate about a particular entity without each enterprise having the same identifier or having the same, accurate entity demographic information.

Abstract: Identifying and addressing an individual's socio-economic factors related to negative health outcomes for reducing the likelihood of negative health outcomes for the individual in the form of readmission rates, emergency department utilization, missed appointments/no-shows, etc., may be realized by employing aspects of the present disclosure. A social determinants of health (SDoH) system accesses and analyzes consumer marketing data associated with the individual, business data, and public transportation data held by various databases for identifying indicators of SDoH factors, determines an individual's propensity for SDoH factors, and determines an engagement strategy to address SDoH that impact the individual. The results may be included in a report or included in a user interface that is transmitted to the requestor. The results may be displayed in a way that enables the requestor to easily identify and act on the individual's SDoH using recommended engagement strategies.

Abstract: A request for a most reliable demographic fields data for a selected demographic field associated with an entity may be received at an entity matching system. A plurality of records associated with the entity may be received at the entity matching system. Each of the plurality of records may include at least one demographic field. A demographic field corresponding to the selected demographic field may be identified from the at least one demographic field for each of the plurality of records. A reliability score may be determined for the corresponding demographic field for each of the plurality of records. The corresponding demographic field with the highest reliability score may be determined as the most reliable demographic fields data.

Abstract: Expanded data processing for entity matching is provided. A request for determining a matching entity is received. The received request is parsed to determine demographic field data associated with the request. A first look up operation is performed in an indexed demographic data for a first demographic field associated with the request. A first list of entities matching with the first demographic field data is received in response to the first look up operation. A second look up operation is performed in the indexed demographic data to determine a set of demographic attributes associated with each entity on the first list. The demographic attributes correspond to a second demographic field associated with the request. A matching confidence for whether the entity is associated with a given entity in the first list is determined based on a comparison between the demographic field data and the demographic attributes.

Abstract: Generating and providing match justifications in association with record matching results for improved record matching is provided. An entity resolution system generates a set of deterministic rules based on patterns of attribute comparison outcomes of known matched and unmatched records. Each rule includes matching conditions and an action instruction including a message of a justification for a match/non-match. The system receives a request to determine a match between two records. A matching engine compares various attributes of the records using probabilistic matching technologies to determine a match outcome. A justification engine compares attribute comparison outcomes to the stored rules. When the matching conditions of a rule are satisfied, the rule is activated and a human-readable justification is linked to the match output and provided in a match response. The justification provides insights into the match outcome, and improves the speed and accuracy of a verification process of the match output.

Abstract: Improvements in data processing to match entities allow for more accurate records to be kept, with less memory storage used and fewer processing resources to be expended when accessing records. When receiving a request for an identifier for an entity, the request is parsed to identify various demographic fields within the request. A probabilistic search is performed to compare the entity to the candidate records that are augmented with expanded demographic data, which improve the reliability in matching the requested entity to its records. As updates are made to the external resources, the requests are rerun to update the internal resource and to eliminate any new identifiers created due to non-updated data, thus reducing data storage overhead.

Abstract: Expanded data processing for entity matching is provided. A request for determining a matching entity is received. The received request is parsed to determine demographic field data associated with the request. A first look up operation is performed in an indexed demographic data for a first demographic field associated with the request. A first list of entities matching with the first demographic field data is received in response to the first look up operation. A second look up operation is performed in the indexed demographic data to determine a set of demographic attributes associated with each entity on the first list. The demographic attributes correspond to a second demographic field associated with the request. A matching confidence for whether the entity is associated with a given entity in the first list is determined based on a comparison between the demographic field data and the demographic attributes.

Abstract: A request for a most reliable demographic fields data for a selected demographic field associated with an entity may be received at an entity matching system. A plurality of records associated with the entity may be received at the entity matching system. Each of the plurality of records may include at least one demographic field. A demographic field corresponding to the selected demographic field may be identified from the at least one demographic field for each of the plurality of records. A reliability score may be determined for the corresponding demographic field for each of the plurality of records. The corresponding demographic field with the highest reliability score may be determined as the most reliable demographic fields data.

Abstract: Improvements in data processing to match entities allow for more accurate records to be kept, with less memory storage used and fewer processing resources to be expended when accessing records. When receiving a request for an identifier for an entity, the request is parsed to identify various demographic fields within the request. A probabilistic search is performed to compare the entity to the candidate records that are augmented with expanded demographic data, which improve the reliability in matching the requested entity to its records. As updates are made to the external resources, the requests are rerun to update the internal resource and to eliminate any new identifiers created due to non-updated data, thus reducing data storage overhead.