An actuary is a business professional who analyzes the financial consequences of risk. They use mathematics, statistics and financial theory to study uncertain future events.
Actuarial Science is the discipline that applies mathematical and statistical methods to assess risk in insurance, finance and other industries and professions.
It can also be defined as a branch of science that uses Mathematics, Statistics, Economics and Financial knowledge to model and manage future uncertainty in the financial and insurance industries.
Actuarial science includes a number of interrelated subjects, including mathematics, probability theory, statistics, finance, economics, and computer science.
The minimum entry requirements for this degree program are:
Kenya Certificate of Secondary Education (KCSE) applicants with a mean aggregate of at least C+
(plus) and at least C+ in both Mathematics and English.
Kenya Advanced Certificate of Education (KACE) or A-level equivalent applicants with at least 2 principal passes, including Mathematics.
Holders of Diploma in Applied Sciences with at least a credit pass in relevant subjects from an Institution recognized by the University Senate,
The program is offered on a full time basis in JKUAT and takes four (4) academic years to complete; each comprising of two (2) semesters.
Students are required to undertake at least eight (8) weeks of practical attachment during their 3rd and 4th years of study.
The graduates are expected to find employment in the following sectors upon completion of the degree program:
- employee benefits
- management consulting industry
- brokerage houses
- software development companies (e.g. writing software for pension managers and risk analysts)
Postgraduate degree programs offered by the Department of Statistics and Actuarial Sciences include:
- Master of Science in Statistics
- Master of Science in Applied Statistics
- Master of Science in Actuarial Sciences
- Master of Science in Bio-statistics
- Master of Science in Financial Engineering
- Masters of Science in Operations Research