INSURANCE LINKED SECURITIES (ILS)
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
- 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.
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.