1. A computer-implemented method comprising: receiving training data for updating an updateable trained first predictive model; inputting the training data into a trained second predictive model and generating predictive output data; based on the predictive output data, detecting an anomaly in the training data as compared to previously received training data; and generating a retrained first predictive model based on the updateable trained first predictive model, a training function and training data that includes the received training data and previously received training data, wherein the received training data is weighted differently than the previously received training data based on the detected anomaly.