This would be awesome! In fact it would be even better, if the firm would know how the weights would have been generated (for example if the weights might be biased due to ridge regression/lasso).
This knowledge could be added in various ML models as some kind of "pre-knowledge" for example in a Baysian Framework.
Or just be used as a guidline in model building based an theoretical assumptions (doing this well reduces variance, so there is less need for the introduction of bias in data driven model selection/penalizing).