Explain how each of your proposed modelling techniques in Question 1 b) can help Auto Finance Ltd. generate insights about a potential customer defaulting on a loan.

QUESTION 1 25 MARKS
With reference to the above case, answer all of the following questions:
a) Based on the business challenges that Auto Finance Ltd. is facing, list and
explain a segmentation problem and a classification problem respectively.
b) Select an analytics model for each problem you have identified in Q1a and justify
your choice.
c) Outline relevant variables for each analytics
model you have identified in Q1(b). Justify your choice of these variables.

QUESTION 2 15 MARKS
Explain how each of your proposed modelling techniques in Question 1 b) can help
Auto Finance Ltd. generate insights about a potential customer defaulting on a loan.

QUESTION 3 10 MARKS
With reference to the above case, describe the pros and cons of using a metric
accuracy vs. recall vs. Area-Under-Curve for your classification modelling. Justify
which metric is the best based on the context of the case.
QUESTION 4 15 MARKS
There are concerns about the ethical issues involved in scoring a customer’s credits.
Identify three ethical issues that Auto Finance Ltd. could face. Provide your
recommendations to mitigate each ethical issue identified.

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