Topic 1. June 05-06


Professor Alan Punter (London)


1. Principal forms of Insurance-Linked Securitisation (ILS):

2.Catastrophe bonds, case studies of landmark transactions covering Property risks, Non-property risks, Life & health risks.

3.The evolution of Alternative Reinsurance Capital (ARC):

  • Introduction – the convergence of re/insurance and capital markets.
  • Characteristics of cat bonds – inc. triggers, pricing, resets, defaults
  • Industry Loss Warranties
  • Sidecars
  • Contingent capital

4.Comparison of reinsurance/retro with various types of ILS

5. Current developments in re/insurance & ILS, and future prospects:

  • Trends in the supply of, and demand for, risk capital.
  • Trading of insurance risk.
  • Changing re/insurance industry dynamics.
  • Future prospects for ILS.

6. List of reference sources and further reading.

Topic 2. June 07-08


Professor Christian Heumann (Munich)


  • Big data: definition; examples; problems; to make useful use of big data, one has first to learn from smalldata.
  • Introduction to important principles which are necessary for all machine learning algorithms (randomization, regularization, re-sampling, cross- validation,etc.).
  • Popular learning algorithms for regression and classification: random forest, neural network, boosting, LASSO,etc.
  • Special topics: text mining, sentiment analysis, deeplearning.
  • Practical work: software for analyzing big data. Participants should apply the methods to (big) data sets which are publiclyavailable.