EconPapers    
Economics at your fingertips  
 

Application of flood catastrophe model to estimate revenue and insurance losses under unpredictable precipitation conditions

Monica R. Mundada, B.J. Sowmya, M. Shilpa and Rajeshwar S. Kadadevaramath

International Journal of Business and Systems Research, 2024, vol. 18, issue 2, 170-189

Abstract: Flooding is the most common source of natural disaster losses worldwide. No part of the planet is immune to flooding. As flood risk is a function of flood danger, exposed goods, and their susceptibility, the growth in flood losses must be attributed to changes in each of these components. Flood insurance has been increasingly popular in recent years. As a result, the insurance business is being forced to provide acceptable solutions. The proposed model constructs the catastrophe risk model for flooding to assess the impact of typical precipitation data uncertainty on loss predictions. Here just a city area is thought about as opposed to an entire region and approach definite information and processing assets ordinarily inaccessible to industry modellers. The model comprises of four parts, a stochastic module, a hydrological and water driven flood danger module, a weakness module, and a monetary misfortune module. It accepts openness information as information and yields the assessed AAL misfortune, EP bend, OEP, AEP bend and PML misfortune.

Keywords: flood disasters; flood risk; catastrophe risk model; flood insurance. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=137104 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbsre:v:18:y:2024:i:2:p:170-189

Access Statistics for this article

More articles in International Journal of Business and Systems Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijbsre:v:18:y:2024:i:2:p:170-189