I want to build a model to support decision making for loan insurance proposal. The problem is for a human to decide whether or not he/she should propose a loan insurance to a loan applicant. The risk is that some banks reject loan applicant when they want a loan insurance. The profile of the applicant can matter in their rejection from banks but all criteria influencing the decision are quite uncertain.
I’ve researched online and found several scholarly articles on using Monte Carlo for decision making. Is there a good example somewhere, which explains both the model? And are there other possibility like machine learning model?
I am new to Decision Making and I code in Python. Thank you!