Article: Application of flood catastrophe model to estimate revenue and insurance losses under unpredictable precipitation conditions Journal: International Journal of Business and Systems Research (IJBSR) 2024 Vol.18 No.2 pp.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. Inderscience Publishers - linking academia, business and industry through research

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

Authors: Monica R. Mundada; B.J. Sowmya; M. Shilpa; Rajeshwar S. Kadadevaramath

Addresses: Department of Computer Science and Engineering, Ramaiah Institute of Technology, Bangalore, 560054, India ' Department of Computer Science and Engineering, Ramaiah Institute of Technology, Bangalore, 560054, India ' Department of Industrial Engineering and Management, Ramaiah Institute of Technology, Bangalore, 560054, India ' Industrial Engineering and Management, Siddaganga Institute of Technology, Tumakuru, 572103, Karnataka, India

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.

DOI: 10.1504/IJBSR.2024.137104

International Journal of Business and Systems Research, 2024 Vol.18 No.2, pp.170 - 189

Received: 28 Apr 2022
Accepted: 23 Sep 2022
Published online: 01 Mar 2024 *

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

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