12-27 Thinking through the data. James Silva is a management accountant at Keebler-Olson, where he is in charge of their investment portfolio. In 2015, James worked with a data scientist to develop a model that predicts how a given loan will perform in the future based on the characteristics of the borrower available on the peer-to-peer lending platform Mandel Credit. On April 1, 2016, he purchased $100,000 worth of loans with 36-month terms (3 years). His investments had performed well. James planned to invest another $100,000 on January 1, 2020. Looking ahead, he debated some strategic questions around the model. Required 1. James wonders whether he should use new data to train a new model in December 2019, just prior to his planned investment on January 1, 2020. What should he do with the older data? 2. How much of the actual performance of the loans (such as repayments, loan restructuring, delayed repayments, hardship plans, etc.) should James use in classifying loans as default or repay when building his prediction model