| CPC G06Q 40/03 (2023.01) | 16 Claims |
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1. An apparatus for generating an optimization model, the apparatus comprising:
at least a processor; and
a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to:
receive user metrics related to a user using a graphical user interface comprising a user metric field, wherein the user metrics comprises a transaction history;
classify the user metrics to a plurality of sets of protocol parameters, wherein classifying the plurality of sets of protocol data comprises determining causative and predictive links between protocol parameters of the plurality of sets of protocol parameters and the transaction history using a machine learning process;
identify the plurality of sets of protocol parameters related to a plurality of contingent payments;
determine an efficiency score of each of the contingent payments as a function of the plurality of protocol parameters and an efficiency criterion, wherein determining the efficiency score further comprises:
generating a weight for each of the plurality of sets of protocol parameters of the plurality of contingent payments based on significance relative to the efficiency score;
generating scoring training data, wherein the scoring training data comprises correlations between protocol parameters inputs and efficiency score outputs;
iteratively training a scoring machine-learning model using the scoring training data and the weight;
updating the scoring training data as a function of previous iterations of the trained scoring machine-learning model;
retraining the scoring machine-learning model as a function of the updated scoring training data; and
determining the efficiency score using the retrained scoring machine-learning model;
select a first contingent payment of the plurality of the contingent payments as a function of the efficiency score, wherein the first contingent payment comprises a first set of protocol parameters of the plurality of parameters, wherein selecting the first contingent payment comprises comparing the efficiency score to a predetermined threshold to accept or eliminate the first set of protocol parameters;
generate an optimization model of the first contingent payment as a function of the user metrics and the accepted first set of protocol parameters, wherein the optimization model comprises one or more regulatory elements;
display the optimization model on the graphical user interface using an executable data structure;
generate a report for the user as a function of the executable data structure; and
display the report on the graphical user interface.
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