eXsight: An Analytical Framework for Quantifying Financial Loss in the Aftermath of Catastrophic Events
Matthew Coelho, Andrew Rau‐Chaplin · 2014
In this paper we explore the design of an analytical framework for quantifying financial loss in the aftermath of catastrophic events. The idea is to aggregate the thousands of exposure databases received by a single reinsurer into a giant loosely structured exposure portfolio and then use Big Data analysis technology, originally developed in the context of web-scale analytics, to rapidly perform natural but ad-hoc loss analysis immediately after an event. As in many situational analysis problems, the challenge here is to work with both categorical and geospatial data, deal with partial data often at varying levels of aggregation, integrate data from many sources, and provide an analysis framework in which analyses can be rapidly performed in the hours, days, and weeks immediately after an event.