Dean Preston is the management accountant at Birch Bank, where the data science department is leading an initiative to predict whether loans will default or repay. The default rate in the training set is 25%. After building a model on the training set that predicts whether a loan will default or repay, the data scientist applies it to the validation set of 1,000 observations to evaluate its performance. Read the equirements Requirement 1. Help the data scientist complete the confusion matrixes below for different model thresholds. Start by completing the confusion matrix for the cutoff point 0.40. Confusion Matrix (0.40) Predicted Outcomes Default Repay Total Actual Default Outcomes Repay 470 280 750 Total 650 1,000 Complete the confusion matrix for the cutoff point 0.55. Confusion Matrix (0.55) Predicted Outcomes Default Repay Total Actual Default 195|| 250 Outcomes Repay 750 Total 550 Requirement 2. Assume that Birch Bank has $1,000 to invest in each loan of the validation sample. If Birch Bank does not invest in a loan, it keeps the money in a risk-free investment at 4% a year for 3 years (ignore the time value of money). If Birch invests in a loan that eventually repays, it receives 10% a year for 3 years. If Birch invests in a loan that eventually defaults, Birch loses 75% of the amount of the loan. Fill in the payoff matrix below. Which model threshold should Dean and the data scientist use? Start by construting the payroll matrix. (Enter a loss amount with a minus sign or parentheses.) Payoff Matrix Predicted Outcomes Default Repay (Do Not Invest in Loan) (Invest in Loan) Actual Default Outcomes Repay Calculate the payoff at each cutoff probability. Total payoff at cutoff 0.40 = Total payoff at cutoff 0.55 = Which model threshold should Dean and the data scientist use? Dean and the data scientist should use the cutoff value at V because it results in the predicted payoff.