Determination and Verification of the Key Assessment Indicators for the Insurance Market by Applying the Decomposition Multiattribute Methods and Regression Analysis Cover Image

Determination and Verification of the Key Assessment Indicators for the Insurance Market by Applying the Decomposition Multiattribute Methods and Regression Analysis
Determination and Verification of the Key Assessment Indicators for the Insurance Market by Applying the Decomposition Multiattribute Methods and Regression Analysis

Author(s): Martina Borovcová, Adéla Špačková
Subject(s): Methodology and research technology, Financial Markets
Published by: Masarykova univerzita nakladatelství
Keywords: multi-attribute methods; AHP; ANP; Key Assessment Indicators; Saaty Pair Comparison Approach; regression analysis;
Summary/Abstract: The insurance industry is one of the most important sectors of the economy. The insurance market is very much intertwined in the financial markets, therefore assessment of its level is important. The assessment and analysis of the insurance market is done by using selected indicators. The aim of the article is determination and verification of the key assessment indicators for the insurance market by applying the decomposition multi-attribute methods and regression analysis. This paper is focused on the description, verification and application of the multi-attribute decomposition methods AHP and ANP based on the Saaty pair comparison approach. The AHP and ANP methods are described, including the computation procedure. The applicability of the methods is presented at the preferences determination. The linear AHP and nonlinear ANP methods are applied. These methods are applied for insurance market assessment, particularly, for determination of preference indicators for the assessment of the insurance market. We consider importance of setting the ratio for evaluation indicators of the development of the insurance market by applying Saaty methods in the framework of decomposition methods AHP and ANP (insurance penetration ratio, claims frequency ratio, concentration ratio, premium indicator, benefit indicator, number of insurance company indicator and more). Subsequently, a custom regression model is created.

  • Page Range: 44-52
  • Page Count: 9
  • Publication Year: 2018
  • Language: English