Machine learning systems and methods to evaluate a claim submission

A system for evaluating an insurance claim prior to submission, the system comprising:

• one or more computer processors;
• and
• computer memory storing computer-executable instructions that are configured to, when executed by the one or more computer processors, cause the system to:
• extract a plurality of data features from data for the insurance claim;
• process one or more of the plurality of data features using a machine learning model to generate an initial propensity to deny data object comprising a plurality of potential denial data objects, wherein (i) the machine learning model is configured as an ensemble of classifiers in which each classifier in the ensemble corresponds to a potential issue of a plurality of potential issues for the insurance claim and is trained to generate a data value for the potential issue representing an impact of the potential issue on the insurance claim being at least one of denied or underpaid, (ii) the initial propensity to deny data object represents a likelihood of the insurance claim being at least one of denied or underpaid, and (iii) each potential denial data object of the plurality of potential denial data objects represents a potential issue of the plurality of potential issues and comprises the corresponding data value;
• process at least one potential denial data object of the plurality of potential denial data objects using a mitigating model to identify at least one mitigating action configured to cure the potential issue associated with the at least one potential denial data object;
• provide the potential issue associated with the at least one potential denial data object, the data value corresponding to the at least one potential denial data object, and the at least one mitigating action for display via a user interface through a user device;
• receive an indication of a completion of the at least one mitigating action to cure the potential issue for the at least one potential denial data object;
• and
• responsive to receiving the indication of the completion of the at least one mitigating action:
• extract the plurality of data features from the data for the insurance claim, wherein the plurality of data features reflects the completion of the at least one mitigating action;
• process one or more of the plurality of data features using the machine learning model to generate a working propensity to deny data object comprising the plurality of potential denial data objects, wherein the working propensity to deny data object represents a likelihood of the insurance claim being at least one of denied or underpaid in light of the completion of the at least one mitigating action and the at least one potential denial data object of the plurality of potential denial data objects comprises an updated data value based at least in part on the completion of the at least one mitigating action;
• and
• provide the potential issue associated with the at least one potential denial data object, the updated data value corresponding to the at least one potential denial data object, and an indication that the at least one mitigating action has been completed for display via the user interface through the user device.

A non-transitory computer-readable medium storing computer-executable instructions for evaluating an insurance claim prior to submission, the computer-executable instructions are configured to, when executed by one or more computer processors, cause the one or more computer processors to:

• extract a plurality of data features from data for the insurance claim;
• process one or more of the plurality of data features using a machine learning model to generate an initial propensity to deny data object comprising a plurality of potential denial data objects, wherein (i) the machine learning model is configured as an ensemble of classifiers in which each classifier in the ensemble corresponds to a potential issue of a plurality of potential issues for the insurance claim and is trained to generate a data value for the potential issue representing an impact of the potential issue on the insurance claim being at least one of denied or underpaid, (ii) the initial propensity to deny data object represents a likelihood of the insurance claim being at least one of denied or underpaid, and (iii) each potential denial data object of the plurality of potential denial data objects represents a potential issue of the plurality of potential issues and comprises the corresponding data value;
• process at least one potential denial data object of the plurality of potential denial data objects using a mitigating model to identify at least one mitigating action configured to cure the potential issue associated with the at least one potential denial data object;
• provide the potential issue associated with the at least one potential denial data object, the data value corresponding to the at least one potential denial data object, and the at least one mitigating action for display via a user interface through a user device;
• receive an indication of a completion of the at least one mitigating action to cure the potential issue for the at least one potential denial data object;
• and
• responsive to receiving the indication of the completion of the at least one mitigating action:
• extract the plurality of data features from the data for the insurance claim, wherein the plurality of data features reflects the completion of the at least one mitigating action;
• process one or more of the plurality of data features using the machine learning model to generate a working propensity to deny data object comprising the plurality of potential denial data objects, wherein the working propensity to deny data object represents a likelihood of the insurance claim being at least one of denied or underpaid in light of the completion of the at least one mitigating action and the at least one potential denial data object of the plurality of potential denial data objects comprises an updated data value based at least in part on the completion of the at least one mitigating action;
• and
• provide the potential issue associated with the at least one potential denial data object, the updated data value corresponding to the at least one potential denial data object, and an indication that the at least one mitigating action has been completed for display via the user interface through the user device.