Answer: 33%

## Explanation This is a **Bayes' Theorem** application problem. Let's define the events: - **A**: Borrower has an agency-secured mortgage loan - **B**: Borrower is a millennial **Given probabilities:** - P(A) = 62% = 0.62 (probability of agency-secured loan) - P(B) = 32% = 0.32 (probability of being millennial) - P(B|A) = 17% = 0.17 (probability of being millennial given agency-secured loan) **We need to find:** P(A|B) = probability of agency-secured loan given millennial status **Using Bayes' Theorem:** \[ P(A|B) = \frac{P(B|A) \cdot P(A)}{P(B)} \] **Calculation:** \[ P(A|B) = \frac{0.17 \times 0.62}{0.32} = \frac{0.1054}{0.32} = 0.329375 \approx 0.33 \] **Therefore:** P(A|B) = 33% **Why other options are incorrect:** - **A (17%)**: This is P(B|A), not P(A|B) - **B (20%)**: No mathematical basis for this value - **D (52%)**: This might be confused with P(A) = 62% or some other incorrect calculation This demonstrates the importance of understanding conditional probability and Bayes' Theorem in risk analysis contexts.

Author: LeetQuiz .