Scoring and detecting anomalies in a dynamic number of transaction records within a
relational database management system by initiating a function for accepting and storing a transaction
record in the
relational database management system; This function and the analytics are integral to the RDBMS, as distinguished from extracting the data and passing the data to a separate application external to the RDBMS. The function determines if the transaction is for a different individual then a previous transaction or for the same individual. If the transaction is not for a different individual, adding the new
transaction data to a memory
work space and returning a NULL statement, otherwise passing the memory
work space to a service. In the next step the memory
workspace is accepted and an
analytic model is executed to produce a
score, and return the
score to a calling function. This
score is received at the calling function, the memory
work space for the individual is released, and the score is returned to the calling statement. All of the NULL statements are collapsed and a single
record is retained for the individual. This
record contains the score, that is, a buying preference or pattern, a travel pattern, a calling pattern, a maintenance prediction, a risk score, or a credit score, by way of illustration.