Hello! I'm a little lost on identifying five of the most serious flaws in the below model proposal...any ideas would be much appreciated!

"We will mine the data from the prior USD campaign that was delivered to a random sample of 10,000 alumni. We propose to build a model to predict how much each of the school's alumnus will give, and then target those who will give the most.The school has collected various data points on each alum, including demographic, geographic, major, year, interest, and first-job data, and stored it in the Alumni Database. We will use the amount donated as the target variable, and the data from the Alumni Database as the features. We will build a classification tree and a logistic regression from the data from the random campaign to estimate the amount donated. We will compare the models built based on the area under the ROC curve. The Ninja administration has told us that they would like to target another 5000 alumni in the next test. The 5000 alumni with the highest area under the ROC curve will be targeted."