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Part $1$

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.

Read the

requirements

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Part $1$

Requirement $1.$ 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?

In machine learning models it is often better to

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Machine learning relies on the

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future data being accurate.

past being a good predictor of the future.

A management accountant

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need not worry about the additional costs of updating the data set as newer data will always result in a more predictive model.

will have to judge the costs and benefits of updating a data set.