Risk prediction vs classification model
I will try to answer your question as shortly as possible. 


Yes, if you define probability as a risk, then the probabilities are risk scores. But, there's a catch in these scenarios, you will have to include the prevalence of a class to calibrate them. If Person A has a risk score of 0.9 but you have observed that the positive class is only 20% of the data, then the actual risk is much lower than the probability it self. You can use clf.predict_proba() function to get these probabilities.
Once you have these probabilities, you should be able to set your custom threshold.
Yes, most of these models in different libraries have predict_proba() functions.


Let me know if you have more questions.