Insurance is, at its core, a business of pricing uncertainty: exchanging a fixed premium today against costs that may or may not materialize tomorrow. Getting that price right depends entirely on statistics — on knowing the real odds behind every policy.

Statistical agencies and insurers alike depend on accurate, timely data to support decisions, plan operations, and evaluate performance. Few people outside the profession realize how much of this rests on the work of insurance statisticians and actuaries, who calculate the probability of events and use that knowledge to price policies correctly and allocate assets responsibly.

The Advanced Statistics on Insurance programme by the Arab British Fellowship Training Academy builds these skills directly — from statistical foundations to writing the reports that shape administrative and financial decisions across an organization.

Who should attend?

• Managers of the Central Administration.
• Employees in information management centers.
• Statistical analysts.
• Employees at business risk management.

How attendees will benefit?

After completion of the programme, delegates will be able to:

• Apply probabilistic and statistical skills to solve financial and insurance problems.
• Build a broad understanding of how statistics applies across financial and insurance processes.
• Construct risk models appropriate to short-term insurance contracts and make related statistical inferences.
• Apply the fundamental concepts of credibility theory and general insurance rating methodology.
• Demonstrate enhanced conceptual skills and logical reasoning to support decision analysis.

• Module 1: Statistics as the Foundation of Insurance Decision-Making
  • Descriptive statistics, indirect statistics, and comprehensive population inventory.
  • Statistical measures: central tendency, absolute dispersion, and skewness.
  • How these measures translate into meaningful insight for insurers.
• Module 2: Reading and Presenting Statistical Reports
  • Types and forms of statistical reports and how they are structured.
  • Methods for presenting statistical data: tables, drawings, and graphs.
  • Descriptive (analytical) reading of statistical reports.
• Module 3: Pricing Life, Health and Pension Insurance Products
  • Life insurance pricing for individual and group products.
  • Health insurance and pension fund pricing for individuals.
• Module 4: Reinsurance, Catastrophe Modelling and Non-Traditional Roles
  • Reinsurance and CAT (catastrophe) modelling, and how reinsurers insure insurance companies.
  • Non-traditional roles of banking within the insurance and risk landscape.
• Module 5: Statistical Tools for Actuarial Work
  • Probability theory applied to insurance risk.
  • Simulation techniques and predictive modelling.
  • Big data techniques supporting modern actuarial analysis.