Problem based on decision tree.
A manufacturer must decide whether to extend credit to a retailer who would like to open an account with the firm. Past experience with new accounts indicates that 45% are high-risk customers, 35% are moderate-risk customers, and 20% re low-risk customers. If credit is extended, the manufacturer can expect to lose $60,000 with a high-risk customer, make $50,000 with a moderate-risk customer, and make $100,000 with a low-risk customer. If the manufacturer decides not ot extend credit to a customer, the manufacturer neither make nor loses any money. Prior to making a credit extension decision, the manufacturer can obtain a credit rating agency concedes that its rating procedure is not completely reliable. In particular, the credit rating procedure will rate a low-risk customer as a moderate-risk customer with probability 010 and as ahigh-risk customer with probability 0.05. Furthermore, the given rating procedure will rate a moderate-risk customer as a low-risk customer with probability 0.06 and as a high-risk customer with probability 0.07. Finally, the rating procedure will rate a high-risk customer as a low-risk customer with probability 0.01 and as a moderate-risk customer with probability 0.05
Find the strategy that maximizes the manufacturer's expected net earnings.
Should the manufacturer routinely obtain credit rating reports on those retailers who seek credit approval? Why or why not?