Final answer:
Using Bayes' Theorem, the posterior probability of a customer defaulting given they missed a monthly payment is 0.303. Since this probability is above the bank's threshold of 0.20, the bank should recall the credit card.
Step-by-step explanation:
To calculate the posterior probability of default given that a customer missed a payment, we need to use Bayes' Theorem, which is expressed as:
P(A|B) = (P(B|A) * P(A)) / P(B)
Where:
- P(A|B) is the posterior probability of defaulting given a missed payment.
- P(B|A) is the probability of missing a payment given that the customer will default, which is 1.
- P(A) is the prior probability of defaulting, which is 0.08.
- P(B) is the total probability of missing a payment.
First, we need to calculate P(B), which is the total probability of missing a payment:
P(B) = P(B|A) * P(A) + P(B|not A) * P(not A)
P(B) = (1 * 0.08) + (0.20 * 0.92)
P(B) = 0.08 + 0.184
P(B) = 0.264
Now we can calculate the posterior probability:
P(A|B) = (1 * 0.08) / 0.264
P(A|B) = 0.08 / 0.264
P(A|B) = 0.303 (to three decimals)
Given that the bank wants to recall a credit card if the probability of defaulting is greater than 0.20, and the calculated posterior probability is 0.303, the bank should recall the credit card as the condition is met.