z53924 02 THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF INFORMATION SYSTEMS AND TECHNOLOGY MANAGEMENT TERM 3 2021 INFS5720: BUSINESS ANALYTICS METHODS FINAL EXAMINATION 1. Time Allowed: 24 Hours. 2. This is a Take-Home Exam, your responses must be your own original work. You must attempt this Take-Home Exam by yourself without any help from others. Thus, you have NOT worked, collaborated or colluded with any other persons in the formulation of your responses. The work that you are submitting for your Take-Home Exam is your OWN work. 3. Release date/time (via Moodle): Tuesday, 30 November 9:00am (Australian Eastern Time Zone) 4. Submission date/time (Via Turnitin): Wednesday, 1 December 9:00am (Australian Eastern Time Zone) 5. Failure to upload the exam by the submission time will result in a penalty of 15% of the available marks per hour of lateness. 6. This Examination Paper has 4 pages, including the cover page. 7. Total number of Questions: 5 Questions. 8. Answer all 5 Questions. 9. Total marks available: 100 marks. This examination is worth 55% of the total marks for the course. 10. Questions are not of equal value. Marks available for question sub-parts are shown on this examination paper. 11. Some questions have word limits as indicated on the question. These word limits must be adhered to. Text in excess of the specified word limit(s) may not be considered in the marking process. 12. Candidates must submit a signed Declaration Form together with the Take- Home Exam answer document. Failure to submit the signed Declaration Form may result in your Take-Home Exam answer sheet not being marked. PAGE 2 OF 4 z53924 02 13. Answers to questions are to be written in the template provided. Please ensure that you provide the following details on your Take-Home Exam answer sheet: Student ID: 14. In accordance with the Declaration Form, this Take-Home Exam paper cannot be copied, forwarded or shared. 15. Students are reminded of UNSW’s rules regarding Academic Integrity and Plagiarism. Plagiarism is a serious breach of ethics at UNSW and is not taken lightly. For details see Examples of plagiarism. 16. This Take-Home Exam is an open book/open web, further information is available “Here”. You are permitted to refer to your course notes, any materials provided by the course convenor or lecturer, books, journal articles, or tutorial materials. It is sufficient to use in-text citations that include the following information: the name of the author or authors; the year of publication; the page number (where the information/idea can be located on a particular page when directly quoted), For example, (McConville, 2011, p.188). You are required to cite your sources and attribute direct quotes appropriately when using external sources (other than your course materials). When citing Internet sources, please use the following format: website/page title and date. If you provide in-text citations, you MUST provide a Reference List. The Reference list will NOT BE counted towards your word limit. 17. Students are advised to read the Take-Home Exam paper thoroughly before commencing. 18. The Lecturer-in-Charge (LiC) / Exam Referee will be available online (via Moodle) after the Take-Home Exam paper is released for a period of two hours. PAGE 3 OF 4 z53924 02 You need to answer Questions 1, 2, 3, and 4 based on a business case: Retail Cre
dit Scoring for Auto Finance Ltd. Please access the case via the link provided on Moodle. You DO NOT need to answer the questions on the case document (if any). 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. [max 200 words] (10 marks) b) Select an analytics model for each problem you have identified in Q1a and justify your choice. [max 100 words] (5 marks) c) Outline relevant variables (i.e., target variables; input variables) for each analytics model you have identified in Q1(b). Justify your choice of these variables. [max 200 words] (10 marks) 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. [max 300 words] 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. [max 250 words] 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. [max 300 words] PAGE 4 OF 4 z53924 02 QUESTION 5 35 MARKS To answer the following questions, you need to deploy the dataset “Cars” on SAS Viya and perform the analysis using SAS Viya. The description of variables in the dataset is shown in the table below. No Variables Description 1 Make Manufacturing company 2 Model Model name 3 DriveTrain Type of drivetrain (e.g., front wheel drive; rear wheel drive) 4 Origin Regions by continent 5 Cylinders Number of cylinders 6 EngineSize Engine displacement size (in litres) 7 Horsepower Maximum horsepower 8 Invoice Retail price shown on an invoice 9 MSRP Manufacturer’s suggested retail price 10 Length Length of a vehicle 11 MPG_Highway How far the car is able to travel for every gallon of fuel it uses on the highway 12 MPG_City How far the car is able to travel for every gallon of fuel it uses around the city 13 Type Type of a car 14 Weight Weight of a car 15 Wheelbase The distance between the front and rear axles of a car a) Given the choice of linear regression vs. logistic regression vs. decision tree, select a modelling technique that is suitable for evaluating a car’s travelling capability around the city and justify your choice. [max 200 words] (10 marks) b) Based on the modelling technique you selected in Question 5a), report your model by specifying variables (i.e., dependent variables; independent variables), reporting corresponding parameters and fit statistics. Note: specify intercept and coefficient parameters if you develop a linear or logistic regression model. Specify decision rules if you develop a decision tree model. [No word limit] (10 marks) c) Based on the output of your model in Question 5b), explain the impact of each independent variable you chose on a car’s travelling capability around the city. [300 words] (15 marks) — END OF EXAMINATION PAPER —