Abstract

The nature for enhancing the operational efficiency of insurance products using Big Data Analytics is found to be a common concept in many insurance companies. The problems for identifying at earlier stage of risks in insurance and management of related products for both internal and external use including the brokers and underwriters to determine the key needs of insurance is vital. Therefore, the user needs for insurance products to be set up and the process for renewal differs from one organisation to the other. The research work in insurance risks and cyber security for protecting IT/IS infrastructures in insurance business organisation is still in its infancy. The research will investigate into the process of cyber insurance and risks associated to business data relevant to the insurance products in the context of sample organisation. This includes the risk policy requirements, pricing, and cost of insurance on different products as applicable to an insurer. This study aims to conclude how data analytics can be best used to derive maximum business insight from an organisation to enhance the operational efficiency of the insurance and risk function. The research findings will provide insightful information about various stakeholders involved in the insurance renewal and implementation process. The main goal is to use data analytics to gain insight, improve processes and collaboration between stakeholders and to potentially reduce insurance premiums. This research will be conducted from the stance of the insurance and risk division within the business as the beneficiary. As external insurers and brokers charge a fee for their services, the research question will focus on how insurers always charge a fair premium based on data provided to them. Security metric for insurance and risk control and mitigation procedures for insurance and insurer will be formulated and data presentation will be determined on how organisation’s reaction on cyber insurance risk based on data accuracy are made available and risks identified are interpreted for organisation use.

Authors: Francesca Pye, Funminiyi Olajide

Published in: International Conference for Internet Technology and Secured Transactions (ICITST-2023)

  • Date of Conference: 13-15 November 2023
  • DOI: 10.20533/ICITST.2023.0016
  • ISBN: 978-1-913572-63-1
  • Conference Location: St Anne’s College, Oxford University, UK

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