Bachelor of Science in

Actuarial Science

Who can join?

This course has a heavy mathematical and statistical component. It is suited for those who enjoy solving mathematical problems and are interested in the application of statistics to business, finance, society and the social relationships found therein.

Career opportunities

Career opportunities can be found in investment banking, investment management, commercial banking, financial analysis, auditing, insurance, business consultancy, data analytics, accounting, statistics, and the civil service.

Entry qualifications

KCSE mean grade B+ (plus) with a B (plain) in Mathematics OR any other equivalent qualification approved by the university senate.

For actual subject and work experience requirements please contact the enrollment office.

Duration: 3 years (nine trimesters)

Curriculum Road Map

Fee Structure

Notes:

  • This fee structure is subject to review by the University

  • All fees are payable in installments

  • Please contact the Enrollment office for additional information on programme requirements and fees structure

Learn how to turn risks into opportunities: we will equip you with the skills to measure, assess, manage, mitigate and sometimes, profit from risk. By the end of the programme you will be able to apply mathematical skills and business knowledge to solve important problems for insurance, the financial service industry, government, and researchers.

Request information:

Contact us on:

0715 532187 or callcentre@kca.ac.ke

Request information

+254 715 532187

KSh. 90,645

KSh. 78,270

KSh. 78,270

KSh. 88,645

KSh. 88,645

Trimester 5

Trimester 4

Trimester 3

Trimester 2

Trimester 1

Trimester 6

KSh. 88,645

Trimester 7

KSh. 88,645

Trimester 8

KSh. 88,645

Trimester 9

KSh. 67,895

  • Calculus and linear algebra

  • Probability and statistics

  • Risk management and insurance

  • Interest theory

  • Economics

  • Finance

  • Contingent payment models

  • Survival models

  • Frequency and severity models

  • Stochastic process models

  • Ruin models

  • Simulation models

  • Estimation and fitting of models

  • Regression, forecasting, and time series

  • Credibility theory

  • Accounting

  • Computer science

  • Statistical programming