Abstract: A system and a method are disclosed for a tool that generates a provider score corresponding to a predicted performance of a provider based on data of claims involving the provider. For a given claim, the tool provides the data as input into a supervised machine learning model and receives as output from the supervised machine learning model a predicted performance of the claim. The tool also inputs the data of the claim into an unsupervised machine learning model that is selected based on a stage of claim processing that the claim belongs to and receives as output from the unsupervised machine learning model an identification of a cluster of candidate claims to which the claim belongs. The tool combines the outputs of the supervised machine learning model and the unsupervised machine learning model to generate the provider score.

Abstract: A system and a method disclosed herein provides search and recommendation mechanisms for selecting attorneys. In an embodiment, a processor identifies a claim litigated by a candidate attorney. The processor uses historical claim data and a claim score for an attorney who opposed the candidate attorney when litigating the claim to determine a claim score for the candidate attorney. The processor then uses the candidate attorney claim score to recalculate the opposing attorney claim score, and checks to see whether the claim scores have converged. If the scores have not converged, the processor iteratively recalculates the claim scores of the candidate attorney and the opposing attorney until the scores converge. Finally, the candidate attorney claim score is used to determine an overall score for the candidate attorney which can be compared against the scores of other attorneys and used for attorney search and recommendation.

Abstract: A system and a method disclosed herein provides search and recommendation mechanisms for selecting attorneys. In an embodiment, a processor identifies a claim litigated by a candidate attorney. The processor uses historical claim data and a claim score for an attorney who opposed the candidate attorney when litigating the claim to determine a claim score for the candidate attorney. The processor then uses the candidate attorney claim score to recalculate the opposing attorney claim score, and checks to see whether the claim scores have converged. If the scores have not converged, the processor iteratively recalculates the claim scores of the candidate attorney and the opposing attorney until the scores converge. Finally, the candidate attorney claim score is used to determine an overall score for the candidate attorney which can be compared against the scores of other attorneys and used for attorney search and recommendation.