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MSc Actuarial Science with Business Analytics

  • DeadlineStudy Details:

    12 months full-time

Course Description

This pathway is for you if you like to think about innovative tools – there is a rising need for these people in actuarial practice, and demand is far higher than supply. Our dedicated MSc in Actuarial Science with Business Analytics, established in 2020, aims to fill this gap.

Choose this MSc if you are interested in understanding the fundamentals of traditional areas of actuarial practice, and in taking advantage of unique opportunities to grow in the new areas of business analytics methods, machine learning, data management systems and natural language processing. You’ll already hold the equivalent of a UK upper second class degree in a highly quantitative programme, such as mathematics or statistics.

Entry Requirements

  • A UK upper second class degree or above, or the equivalent from an overseas institution, in a highly quantitative programme such as mathematics or statistics is required to enter this course
  • Work experience is not a requirement of this course.

Fees

See our website for fees

Student Destinations

Your Master’s in Actuarial Science with Business Analytics prepares you to tackle roles in actuarial and risk analysis, consultancy and underwriting in leading banking, insurance and financial services firms. As more technology and analytics are introduced across the actuarial industry, your skills will be invaluable to the increasing number of companies seeking actuarial students who have knowledge of business analytics.

Module Details

What will you learn

On the MSc Actuarial Science with Business Analytics you will:

  • Summarise and critically assess fundamental concepts in actuarial science, insurance, economics, finance, investment, financial reporting and business
  • Make use of analytical skills to evaluate and solve complex problems within the organisation’s strategic perspective
  • Demonstrate critical awareness of current analytical methods in order to transform information into knowledge
  • Increase your understanding and knowledge of how current analytical methods could be applied in practice
  • Analyse the breadth of machine learning techniques and their applications
  • Frame analytics problems from a machine learning perspective and suggest practical solutions to them
  • Carry out modelling and effectively communicate the results to a defined audience.

Please see website for actual modules

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