Actuary Studies vs Computer Science? (1 Viewer)

[Wizjaro]

To be quite honest, being an actuary isn't very math heavy. Even when you're doing the lower level tasks. The truth is most systems/models have already been built so your job essentially becomes analysing and optimising those systems which doesn't require the math you learn at uni to be honest. And the higher you go the less math you see. Pretty sure the managers have forgotten most of the stuff they learnt at Uni by that point. So if you want a very math heavy job I really wouldn't recommend being an Actuary. You do a ton of crazy math in Uni but you don't really do much more after you've got your fellowship qualification. While I do think you could do the job of an actuary without being great at math, the barrier to entry into the role requires you to be very good at math which is weird in my opinion. If I were to recommend what Uni to go to I would say Macquarie predominately for the scholarship haha, but to each his own. As for comp sci and coding, unfortunately coding isn't super useful in every actuary role, and even if there was need for coding it typically isnt anything super intensive so I personally wouldn't recommend learning comp sci, but rather learn a bit of python and the sorts on the side as you complete your degree. As for the question about collecting data and making models and stuff, you dont really do any of that, as its all already been done like ages ago. The real skills that will help you do well as an actuary is attention to detail, pattern recognition, research ability(i.e. being able to independently investigate problems if they arise), and understanding the psychology of humans + the market. In saying that I do still think being an actuary is a worthwhile endeavour, I came for the math but I stayed for the complexities. It is a quite interesting job methinks. If you have any specific questions you can pm me and I can help to the best of my ability, but at the end of the day I'd just say trust your hit and do whatever you think feels the most fun.

 

[real_actuary]

From my limited knowledge:

Actuarial is basically just tons of really hard statistics. The main purpose of an actuary is for insurance companies etc. to calculate the probability of certain events happening, such as the probability of someone dying for life insurance. Nowadays, this will often involve some computer science

Computer science is pretty much just fancy word for programmer, and I guess you could analyse code and stuff as well

It doesn't involve much if any CS depending on your job. Most actuarial jobs are completed through Excel spreadsheets with light work in R studio. However, the code written by most actuaries is truly pathetic. You don't get any CS training in the degree but you do get a bunch of code written out for specific examples.

 

[real_actuary]

Thank you so much for the reply! How do actuaries present these findings?

In a written report typically.

 

[real_actuary]

if youre gonna do actuarial I would recommend MQ because of their business school scholarships
basically: get ATAR of 97, get in to actuarial. get ATAR of 98, get in to actuarial and be paid $5000 a year. get ATAR of 99, get in to actuarial and be paid $10000 a year

also, lots of people at uni seem to be doing actuarial because they were ok at maths and then looked up well paying maths jobs and actuarial came up (you can expect to earn $160,000 once out of uni and have passed the external exams - so by age 23)

This is false. The average actuarial salary out of uni is approximately 80,000 without superannuation. The most prestigious actuarial companies i.e. Taylor Fry and Finity pay approximately 90,000. SKL surveys show the salary progression for an actuary. Take this SKL survey from 2021 as an example:

These are the post FIAA salaries (which can be achieved by 22-23 if you dont fail any exams)

 

[real_actuary]

yea, that was the deciding factor to at least try actuarial rather than engineering (like my bio says). so far i’m enjoying it and will probably stay with actuarial

also, going back to @moonsuyoung you could do actuarial + comp sci double degree at UNSW if you want. the coding skills and the way of thinking about code and logic in comp sci is useful for actuarial (and as an actuary you can go into working on data science or machine learning with banks when a comp sci degree is very useful). AND doing any double degree with actuarial is good because then at the end of your degree you will have part I exemptions and most of your part II exemptions (a single degree only gives you part I exemptions)

Actuarial has better pay and employment than engineering yes. With an actuarial degree you can work in more fields as well so the job opportunities are indeed better. Just a note here to get the part II exemptions you'd also need to choose a degree that has significant overlap with actuarial like finance or commerce which allows you to take more electives such that you can take the part II courses.

 

[StudyNotesTips]

Hi!
I was wondering what the main difference is between acturial studies and computer science. I'm very confused on what an actuary does. I know they measure financial risks but how (is it through data they collect??) ? How do they apply maths and what type of maths? Are there components in computer science in actuarial studies?

Also, I was wondering why people do degrees in actuary and computer science? Does it benefit each other in careers?

Hi! Very Very late reply but..


Actuarial Studies
Definition and Role: Actuarial studies focus on assessing financial risks, particularly in insurance and finance. Actuaries use mathematical and statistical methods to evaluate the likelihood of future events, helping organizations minimize financial losses.

Key Components:

1. Mathematics Used:
   • Probability and Statistics: Actuaries rely heavily on probability theory to predict future events and model financial risks.
   • Calculus: This is used in modeling and solving problems related to continuous variables.
   • Financial Mathematics: Involves the calculation of present and future values of cash flows, annuities, and investments.
2. Data Collection and Analysis:
   • Actuaries collect and analyze data related to risks (like claims history, mortality rates, etc.) to create predictive models.
   • They use software and statistical tools to analyze trends and evaluate risks quantitatively.
3. Applications:
   • Actuaries work with insurance companies to set premiums, develop pension plans, and assess solvency.
   • They also advise on investments and risk management strategies.

Computer Science
Definition and Role: Computer science involves the study of computation, programming, algorithms, and data structures. It encompasses a wide range of topics, from software development to artificial intelligence.

Key Components:

1. Programming: Learning languages like Python, Java, or C++ to build software applications.
2. Algorithms and Data Structures: Understanding how to efficiently organize and process data.
3. Machine Learning and Data Analysis: These areas are increasingly important for processing large datasets, which can overlap with actuarial work.

Overlap Between the Two Fields

• Use of Data: Both fields require strong analytical skills and an understanding of how to interpret and manipulate data.
• Statistical Analysis: Actuarial studies use statistical methods that are also foundational in computer science, particularly in data science and machine learning.
• Software Tools: Actuaries often use statistical software (like R or SAS), which involves some programming knowledge—this is where computer science skills can be beneficial.

Why Pursue Each Degree?

1. Actuarial Studies:
   • High demand in the finance and insurance sectors.
   • Competitive salaries and opportunities for career advancement.
   • It offers a stable career with a focus on risk assessment and management.
2. Computer Science:
   • Versatile career options in various industries (tech, healthcare, finance, etc.).
   • Strong job growth and high earning potential.
   • Provides skills applicable to emerging fields like artificial intelligence and cybersecurity.

Benefits of Combining Both Degrees
Having expertise in both actuarial studies and computer science can make candidates more attractive to employers, particularly in data-driven fields. Skills in programming and data analysis can enhance the ability to model risks and analyze trends effectively in actuarial roles.

If you want to delve deeper into these topics, you might find these sources helpful:

• What is an Actuary?
• Careers in Computer Science
• The Importance of Data Science in Actuarial Science

Hope this helps