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Home > Universities > Heriot-Watt University Malaysia Campus > BSc (Hons) Actuarial Science

BSc (Hons) Actuarial Science

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Heriot-Watt University Malaysia Campus

BSc (Hons) Actuarial Science

university icon
Heriot-Watt University Malaysia Campus

BSc (Hons) Actuarial Science

Qualification
Bachelor's Degree
Duration
3 years
Intake
SepSep
English Requirement
IELTS 6.5
Offer Letter
Free
Class Type
Physical
Course Fee for International Students
First year from MYR N/A excludes 6% SST & other fees
Estimated total tuition from ~MYR 0 3 years programme
Published fees don't include possible scholarships and YourUni discounts — most students pay less than the sticker price.

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The BSc (Hons) Actuarial Science program is an undergraduate degree that prepares students for careers as actuaries in insurance and finance. It combines mathematics, statistics, economics, and finance to analyze and manage financial risks. Graduates apply mathematical models and statistical methods to provide valuable insights and advice to organizations.

Future Careers 

  • Actuaries 
  • Risk analysts/managers 
  • Insurance underwriters 
  • Investment analysts
  • Pension consultants 
  • Data scientists/analysts 
  • Financial consultants/advisors.

Year 1

  • Probability and Statistics A & B
  • Actuarial and Financial Mathematics A & B
  • Multivariable Calculus and Real Analysis A & B
  • Linear Algebra
  • Algorithmic and Scientific Programming

Optional and elective courses available for Year 1 include:

  • Finance and Financial Reporting
  • Database Management Systems

Year 2

  • Life Insurance Mathematics A & B
  • Stochastic Processes
  • Survival Models
  • Derivative Markets and Discrete-time Finance
  • Statistical Models A & B
  • Portfolio Theory & Asset Models

Year 3

Students typically take Introductory Economics, Continuous-time Finance, Risk Theory, and Time Series Analysis. They can also
choose from a range of options such as Statistics for Social Science, Bayesian Inference and Computational Methods, Statistical
Machine Learning, and Optimisation.

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