Abstract
Today's advances in big data technologies readily allow for storing large inter-dependent data sets of historical and modeled natural hazard and financial data and unifying their granularity and accuracy with common geo-spatial and risk-type record identifiers. This is a significant component at both single insurance account, and even more so at the larger multi-policy portfolio scale for enabling optimal and socially responsible insurance underwriting practices. This supports insurance risk transfers by creating more accurate and all-uncertainty encompassing pricing techniques, and exposes these techniques and methodologies to all market players, including insurance policy holders via transparent statistical and actuarial principles.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
