ACTL1101 Introduction to Actuarial Studies

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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
  • PLO1 : Business Knowledge
  • PLO2 : Problem Solving
CLO2 : Evaluate the fundamental principles underlying risk management and insurance
  • PLO1 : Business Knowledge
  • PLO2 : Problem Solving
CLO3 : Evaluate and apply fundamental actuarial mathematics techniques
  • PLO1 : Business Knowledge
  • PLO2 : Problem Solving
CLO4 : Describe how the actuarial profession is organised, its code of conduct, its main practice areas, as well as its current challenges and opportunities
  • PLO1 : Business Knowledge
  • PLO5 : Responsible Business Practice
  • PLO6 : Global and Cultural Competence
CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode)
  • PLO1 : Business Knowledge
  • PLO2 : Problem Solving
CLO6 : Communicate data insights effectively
  • PLO3 : Business Communication
CLO7 : Perform efficient computation, as well as manipulate data, in R
  • PLO1 : Business Knowledge
  • PLO2 : Problem Solving


Course Learning Outcomes Assessment Item
CLO1 : Evaluate and apply basic principles of probability, statistics and financial mathematics
  • Weekly Formative Discussion Forum
  • Quiz
CLO2 : Evaluate the fundamental principles underlying risk management and insurance
  • Final Examination (2 hours)
  • Weekly Formative Discussion Forum
CLO3 : Evaluate and apply fundamental actuarial mathematics techniques
  • Final Examination (2 hours)
  • Weekly Formative Discussion Forum
CLO4 : Describe how the actuarial profession is organised, its code of conduct, its main practice areas, as well as its current challenges and opportunities
  • Quiz
  • Final Examination (2 hours)
CLO5 : Interpret and create basic algorithms and control loops (in R and in pseudocode)
  • Assignment
  • Quiz
  • Weekly Formative Discussion Forum
  • Final Examination (2 hours)
CLO6 : Communicate data insights effectively
  • Assignment
  • Weekly Formative Discussion Forum
  • Final Examination (2 hours)
CLO7 : Perform efficient computation, as well as manipulate data, in R
  • Assignment
  • Final Examination (2 hours)

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

Weekly Formative Discussion Forum
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.

Quiz
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

Assignment
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.

Final Examination (2 hours)
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

Theory Slides


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