Abstract: In some instances, a method is provided. The method comprises: identifying a first member for reassignment based on determining that the first member is valid for reassignment; obtaining, from a claims repository, one or more claims for the first member within a first time period, wherein the one or more claims are medical claims associated with a primary care provider (PCP); based on the one or more claims indicating a second medical provider that is different from the first medical provider, reassigning the first member from the first medical provider to the second medical provider; and informing the first member of the reassignment from the first medical provider to the second medical provider.

Abstract: A system and method are disclosed for detecting anomalies in input data. The input data can include enrollment information for members of a health insurance product offered by an insurance carrier. A system is configured to process one or more parameters associated with the input data to detect whether an anomaly is indicated in the input data. At least one artificial intelligence algorithm is configured to compare a parameter in the one or more parameters to a range defined by a moving average. When an anomaly is detected, the processing can be paused and manual intervention can be facilitated. When no anomaly is detected, a database is updated based on the input data. In an embodiment, the input data is an ANSI 834 format file that includes a plurality of membership records, and the one or more parameters are derived from statistics related to the membership records.

Abstract: A system and method are disclosed for detecting anomalies in input data. The input data can include enrollment information for members of a health insurance product offered by an insurance carrier. A system is configured to process one or more parameters associated with the input data to detect whether an anomaly is indicated in the input data. At least one artificial intelligence algorithm is configured to compare a parameter in the one or more parameters to a range defined by a moving average. When an anomaly is detected, the processing can be paused and manual intervention can be facilitated. When no anomaly is detected, a database is updated based on the input data. In an embodiment, the input data is an ANSI 834 format file that includes a plurality of membership records, and the one or more parameters are derived from statistics related to the membership records.