@article{olmez2024,

   title = {Exploring the Dynamics of the Specialty Insurance Market Using a Novel Discrete Event Simulation Framework: A Lloyd's of London Case Study},

   author = {Olmez, Sedar and Ahmed, Akhil and Kam, Keith and Feng, Zhe and Tua, Alan},

   journal = {Journal of Artificial Societies and Social Simulation},

   ISSN = {1460-7425},

   volume = {27},

   number = {2},

   pages = {7},

   year = {2024},

   URL = {http://jasss.soc.surrey.ac.uk/27/2/7.html},

   DOI = {10.18564/jasss.5401},

   keywords = {Discrete-Event Simulation, Specialty Insurance Market, Lloyd, Individual-Based Model, Financial Markets, Underwriting Cycle},

   abstract = {This research presents a novel Discrete Event Simulation (DES) of the Lloyd's of London specialty insurance market, exploring complex market dynamics that have not been previously studied quantitatively. The proof-of-concept model allows for the simulation of various scenarios that capture important market phenomena such as the underwriting cycle, the impact of risk syndication, and the importance of appropriate exposure management. Despite minimal calibration, our model has shown that it is a valuable tool for understanding and analysing the Lloyd's of London specialty insurance market, particularly in terms of identifying areas for further investigation for regulators and participants of the market alike. The results generate the expected behaviours that, syndicates (insurers) are less likely to go insolvent if they adopt sophisticated exposure management practices, catastrophe events lead to more defined patterns of cyclicality and cause syndicates to substantially increase their premiums offered. Lastly, the syndication of risk via the lead and follow structure lead to less volatile and more coupled loss experiences among syndicates demonstrating that Lloyd's of London's regulatory market structure bolsters a healthier marketplace. Overall, this research offers a new perspective on the Lloyd's of London market and demonstrates the potential of individual-based modelling (IBM) for understanding complex financial systems.},

}