Abstract: Systems, methods, and computer-readable medium storing instructions for using a machine learning to predict dwell times for shipments along routes are described herein. The method, system, or instructions may include training the machine learning model using training data, storing the machine learning model in a memory, accessing route data of a shipment of interest, analyzing the route data using the machine learning model, and, based on the analyzing of the route data, outputting a predicted dwell time at a stop of the shipment of interest.

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.