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ACTL1101 Introduction to Actuarial Studies
Course Details & Outcomes
Course Description
This course is designed to provide an introduction to actuarial studies. It covers the fundamental modelling tools used by actuaries (probability, statistics, financial mathematics), as well as some of the basic actuarial models in areas such as insurance, superannuation or financial risk management, and which will be studied in great depth during the remainder of the degree. The main areas of actuarial practice and research are also introduced and discussed. Finally, labs will provide a foundation in programming, as well as data manipulation and visualisation, with a particular focus on R.
Course Aims
This course is offered as part of the first year core in the Bachelor of Actuarial Studies and dual degrees. The course is a prerequisite, along with MATH1251, for the courses ACTL2111 Financial Mathematics for Actuaries, and ACTL2131 Probability and Mathematical Statistics.
Relationship to Other Courses
This course is offered as part of the first year core in the Bachelor of Actuarial Studies and dual degrees. The course is a prerequisite, along with MATH1251, for the courses ACTL2111 Financial Mathematics for Actuaries, and ACTL2131 Probability and Mathematical Statistics.
Course Learning Outcomes
| Course Learning Outcomes | Program learning outcomes |
|---|---|
| CLO1 : Evaluate and apply basic principles of probability, statistics and financial mathematics |
|
| CLO2 : Evaluate the fundamental principles underlying risk management and insurance |
|
| CLO3 : Evaluate and apply fundamental actuarial mathematics techniques |
|
| CLO4 : Describe how the actuarial profession is organised, its code of conduct, its main practice areas, as well as its current challenges and opportunities |
|
| CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode) |
|
| CLO6 : Communicate data insights effectively |
|
| CLO7 : Perform efficient computation, as well as manipulate data, in R |
|
| Course Learning Outcomes | Assessment Item |
|---|---|
| CLO1 : Evaluate and apply basic principles of probability, statistics and financial mathematics |
|
| CLO2 : Evaluate the fundamental principles underlying risk management and insurance |
|
| CLO3 : Evaluate and apply fundamental actuarial mathematics techniques |
|
| CLO4 : Describe how the actuarial profession is organised, its code of conduct, its main practice areas, as well as its current challenges and opportunities |
|
| CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode) |
|
| CLO6 : Communicate data insights effectively |
|
| CLO7 : Perform efficient computation, as well as manipulate data, in R |
|
Learning and Teaching Technologies
Moodle - Learning Management System | EdStem
Learning and Teaching in this course
We are here to HELP students (you) in the learning process by developing your understanding of course topics and to provide opportunities to reflect on and gain deeper understanding of the applications of the course material. The learning process is collaborative, and the more you interact with us (teaching staff) and with fellow students, the more you will learn and get from the course. Interaction can occur in class, in tutorials, in labs, during consultation, on online forums, etc.
Furthermore, the course will use extensive digital resources, some of which have been tailor made for the course; see Course Resources.
Assessments
Assessment Structure
| Assessment Item | Weight | Relevant Dates |
|---|---|---|
|
Weekly Formative Discussion Forum
Assessment FormatIndividual
Short ExtensionYes (7 days)
|
30% | |
|
Quiz
Assessment FormatIndividual
|
10% |
Start DateNot Applicable
Due DateNot Applicable
|
|
Assignment
Assessment FormatIndividual
Short ExtensionYes (7 days)
|
20% |
Start DateNot Applicable
Due DateNot Applicable
|
|
Final Examination (2 hours)
Assessment FormatIndividual
|
40% |
Assessment Details
Assessment Overview
These are aimed at encouraging students to keep up with the course materials.
Course Learning Outcomes
- CLO1 : Evaluate and apply basic principles of probability, statistics and financial mathematics
- CLO2 : Evaluate the fundamental principles underlying risk management and insurance
- CLO3 : Evaluate and apply fundamental actuarial mathematics techniques
- CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode)
- CLO6 : Communicate data insights effectively
Detailed Assessment Description
This course includes weekly formative activities, such as online discussion questions and class discussions, designed to reinforce the concepts learned each week. These activities encourage students to stay engaged with the course materials, helping them identify areas for improvement and enhancing their overall learning experience.
A task due every week may sound like a lot, but each task will be reasonable in terms of the effort and time needed to complete. The purpose of those tasks is to motivate students to keep up with the content, to allow them to test their learning along the way, and to receive feedback. They are intended as an opportunity to learn, not as a burden.
Warning: while students are encouraged to help each other, those weekly questions are individual assignments and therefore academic misconduct will be treated very seriously. Any academic misconduct (such as plagiarism) will be reported to the School Student Integrity Adviser. It is far better not to submit, rather than doing the wrong thing (which of course you should never do!). Furthermore, the plagiarism software is very good, hence you have very high chances of being caught, if you do something you should not do.
Assessment Overview
These are to assess the learning outcomes.
Course Learning Outcomes
- CLO1 : Evaluate and apply basic principles of probability, statistics and financial mathematics
- CLO4 : Describe how the actuarial profession is organised, its code of conduct, its main practice areas, as well as its current challenges and opportunities
- CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode)
Detailed Assessment Description
There will be a in-person quiz held in Week 5, worth 10% of the total mark for the course. The online quiz will focus exclusively on topics related to the Theory of weeks 1-2-3, and associated tutorials. The quiz will be formative: a good attempt (even with minor mistakes) will grant students full marks. The purpose of the quiz is to test knowledge acquired thus far in the term, provide feedback to students in preparation for the final exam, and allow them to adjust their studying strategy if improvements are needed.
Assessment Length
1 hour
Assessment Overview
An individual assignment task involving application of course concepts.
Course Learning Outcomes
- CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode)
- CLO6 : Communicate data insights effectively
- CLO7 : Perform efficient computation, as well as manipulate data, in R
Detailed Assessment Description
The main assignment (attracts 20% of the total mark) will have a focus on R programming (but some "Theory" knowledge will be needed as well). It is meant for students to demonstrate a more extensive knowledge their R programming abilities, with a particular emphasis on the content not assessed through previous weekly online questions.
Assessment Overview
The examination will aim to assess the achievement of the learning course outcomes.
Course Learning Outcomes
- CLO2 : Evaluate the fundamental principles underlying risk management and insurance
- CLO3 : Evaluate and apply fundamental actuarial mathematics techniques
- CLO4 : Describe how the actuarial profession is organised, its code of conduct, its main practice areas, as well as its current challenges and opportunities
- CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode)
- CLO6 : Communicate data insights effectively
- CLO7 : Perform efficient computation, as well as manipulate data, in R
Detailed Assessment Description
The final exam is intended to test students' knowledge, understanding and application of all the "Theory" component of the course, as well as their ability to concisely express themselves. This final examination will be a two hour in-person exam.
Assessment Length
2 hours
Assignment submission Turnitin type
Not Applicable
General Assessment Information
As a student at UNSW you are expected to display academic integrity in your work and interactions. Where a student breaches the UNSW Student Code with respect to academic integrity, the University may take disciplinary action under the Student Misconduct Procedure. To assure academic integrity, you may be required to demonstrate reasoning, research and the process of constructing work submitted for assessment.
To assist you in understanding what academic integrity means, and how to ensure that you do comply with the UNSW Student Code, it is strongly recommended that you complete the Working with Academic Integrity module before submitting your first assessment task. It is a free, online self-paced Moodle module that should take about one hour to complete.
Grading Basis
Standard
Requirements to pass course
In order to pass this course students must:
- Achieve a composite mark of at least 50 out of 100
- Engage actively in course learning activities and attempt all assessment requirements
- Meet any additional requirements specified in the assessment details
- Meet the specified attendance requirements of the course
Course Schedule
| Teaching Week/Module | Activity Type | Content |
|---|---|---|
| Week 1 : 27 May - 2 June | Lecture |
Probability |
| Lecture |
Introduction to R |
|
| Tutorial |
Probability |
|
| Week 2 : 3 June - 9 June | Lecture |
Financial Math and Actuarial Management |
| Lecture |
Exploratory Statistics |
|
| Tutorial |
Financial Math |
|
| Week 3 : 10 June - 16 June | Lecture |
Mortality and Life Annuities |
| Lecture |
Functions and Simple Plotting |
|
| Tutorial |
Mortality and Life Annuities |
|
| Week 4 : 17 June - 23 June | Lecture |
Economics of Risk and Risk Management Systems |
| Lecture |
Advanced Plotting |
|
| Tutorial |
Economics of Risk and Risk Management Systems |
|
| Week 5 : 24 June - 30 June | Lecture |
Statistical Machine Learning and AI Techniques |
| Lecture |
Regression Modeling |
|
| Tutorial |
In-person quiz |
|
| Week 6 : 1 July - 7 July | Module |
Flexibility week: no lecture, no tutorials, no new content! |
| Week 7 : 8 July - 14 July | Lecture |
Life Insurance |
| Lecture |
Introduction to Banking |
|
| Tutorial |
Regression Modeling |
|
| Week 8 : 15 July - 21 July | Lecture |
General Insurance |
| Lecture |
Guest Lecturer |
|
| Tutorial |
Life Insurance |
|
| Week 9 : 22 July - 28 July | Lecture |
Retirement, Health and Disability Insurance |
| Lecture |
Actuarial Practice |
|
| Tutorial |
General Insurance |
|
| Week 10 : 29 July - 4 August | Lecture |
Emerging topics, Regulation and Ethics |
| Lecture |
What's on the Exam? |
|
| Tutorial |
Revision |
Attendance Requirements
Students are strongly encouraged to attend all classes and review lecture recordings.
General Schedule Information
Note: for more information on the UNSW academic calendar and key dates including study period, exam, supplementary exam and result release, please visit: https://student.unsw.edu.au/new-calendar-dates
Course Resources