I managed to find a wonderful resource that discusses the similarities and differences between statistical prediction and algorithmic machine learning models in this open access text:
The acknowledgment section states this was sponsored by the Swiss Association of Actuaries, an the company Swiss Re.
There is coverage of many topics involved in predictive models: Generalized Linear Models (both Bayesian and Frequentist perspectives), various machine learning techniques, validation methods sch as cross validation and the bootstrap.
It will be interesting to compare and contrast the materials with RMS.