Systemic Risk in the Insurance Sector: A Review and Directions for Future Research

Peer-to-peer insurance platforms (P2P insurance), in Poland often called “social platform insurance”, are entering the European insurance market. Although this is not the case for the Polish insurance sector yet, the concept keeps evolving rapidly. P2P insurance is often considered an alternative to the traditional form of insurance. As yet, no legally relevant definition of P2P insurance has been created, and no insurance regulation refers to such platforms. This paper seeks to provide an overview of the existing research both in Polish and foreign literature, to analyze various contributions, highlight current research deficits and future research directions. Finally, the paper attempts to address key research questions which have been already raised in respect of P2P insurance, particularly in the context of the Polish insurance regulations.

Download Full-text

Systemic Risk in the Insurance Sector: A Review of Current Assessment Approaches

The Geneva Papers on Risk and Insurance Issues and Practice ◽

10.1057/gpp.2013.7 ◽

2014 ◽

Vol 39 (3) ◽

pp. 440-470 ◽

Cited By ~ 9

Author(s):

Andreas A Jobst

Keyword(s):

Systemic Risk ◽

Insurance Sector ◽

Current Assessment

Download Full-text

A dynamic MST-deltaCoVaR model of systemic risk in the European insurance sector

Statistics in Transition New Series ◽

10.21307/stattrans-2021-022 ◽

2021 ◽

Vol 22 (2) ◽

pp. 173-188

Author(s):

Anna Denkowska ◽

Stanisław Wanat

Keyword(s):

Systemic Risk ◽

Insurance Sector ◽

European Insurance

Download Full-text

Dynamic Time Warping Algorithm in Modeling Systemic Risk in the European Insurance Sector

Entropy ◽

10.3390/e23081022 ◽

2021 ◽

Vol 23 (8) ◽

pp. 1022

Author(s):

Anna Denkowska ◽

Stanisław Wanat

Keyword(s):

Systemic Risk ◽

Dynamic Time Warping ◽

Spanning Trees ◽

Tail Dependence ◽

Risk Identification ◽

Insurance Companies ◽

Time Warping ◽

Insurance Sector ◽

Dynamic Time ◽

European Insurance

We are looking for tools to identify, model, and measure systemic risk in the insurance sector. To this aim, we investigated the possibilities of using the Dynamic Time Warping (DTW) algorithm in two ways. The first way of using DTW is to assess the suitability of the Minimum Spanning Trees’ (MST) topological indicators, which were constructed based on the tail dependence coefficients determined by the copula-DCC-GARCH model in order to establish the links between insurance companies in the context of potential shock contagion. The second way consists of using the DTW algorithm to group institutions by the similarity of their contribution to systemic risk, as expressed by DeltaCoVaR, in the periods distinguished. For the crises and the normal states identified during the period 2005–2019 in Europe, we analyzed the similarity of the time series of the topological indicators of MST, constructed for 38 European insurance institutions. The results obtained confirm the effectiveness of MST topological indicators for systemic risk identification and the evaluation of indirect links between insurance institutions.

Download Full-text

Systemic Risk and the U.S. Insurance Sector

SSRN Electronic Journal ◽

10.2139/ssrn.1725512 ◽

2011 ◽

Cited By ~ 6

Author(s):

J. David Cummins ◽

Mary A. Weiss

Keyword(s):

Systemic Risk ◽

Insurance Sector ◽

The U.S

Download Full-text

A Tail Dependence-Based MST and Their Topological Indicators in Modeling Systemic Risk in the European Insurance Sector

Risks ◽

10.3390/risks8020039 ◽

2020 ◽

Vol 8 (2) ◽

pp. 39 ◽

Cited By ~ 1

Author(s):

Anna Denkowska ◽

Stanisław Wanat

Keyword(s):

Time Series ◽

Systemic Risk ◽

Spanning Trees ◽

Hybrid Approach ◽

Market Price ◽

Garch Model ◽

Tail Dependence ◽

Insurance Companies ◽

Insurance Sector ◽

European Insurance

In the present work, we analyze the dynamics of indirect connections between insurance companies that result from market price channels. In our analysis, we assume that the stock quotations of insurance companies reflect market sentiments, which constitute a very important systemic risk factor. Interlinkages between insurers and their dynamics have a direct impact on systemic risk contagion in the insurance sector. Herein, we propose a new hybrid approach to the analysis of interlinkages dynamics based on combining the copula-DCC-GARCH model and minimum spanning trees (MST). Using the copula-DCC-GARCH model, we determine the tail dependence coefficients. Then, for each analyzed period we construct MST based on these coefficients. The dynamics are analyzed by means of the time series of selected topological indicators of the MSTs in the years 2005–2019. The contribution to systemic risk of each institution is determined by analyzing the deltaCoVaR time series using the copula-DCC-GARCH model. Our empirical results show the usefulness of the proposed approach to the analysis of systemic risk (SR) in the insurance sector. The times series obtained from the proposed hybrid approach reflect the phenomena occurring in the market. We check whether the analyzed MST topological indicators can be considered as systemic risk predictors.

Download Full-text

What do you know about me? Digital privacy and online data sharing in the UK insurance sector

Journal of Information Communication and Ethics in Society ◽

10.1108/jices-04-2019-0046 ◽

2019 ◽

Vol 18 (2) ◽

pp. 281-303 ◽

Cited By ~ 2

Author(s):

Ian R. Blakesley ◽

Anca C. Yallop

Keyword(s):

Data Sharing ◽

Data Privacy ◽

Small Sample ◽

Consumer Perceptions ◽

Future Research ◽

Research Approach ◽

Exploratory Research ◽

Content Type ◽

Insurance Sector ◽

The Uk

Purpose In addition to data transforming the insurance sector from within, insurance consumers and their behaviour has transformed significantly over the past 20 years from traditional retail to, predominantly, online trading. Data are a fundamental part of how the sector operates, and the use of data in insurance is constantly evolving. This paper aims to explore consumer perceptions about digital privacy and their subsequent motivations to disclose personal data for insurance purposes. Design/methodology/approach The study uses an exploratory research approach based on in-depth interviews to generate metathemes to provide an understanding of consumer perceptions about digital privacy and data sharing in the insurance sector. Findings Consumers were extrinsically motivated to disclose data by financial reward and convenience; however, subsequent intrinsic motivations may be an influence on the initial motivations. Consumers perceived transactions as “fair” if they received the expected rewards, retained control of the data, and the data was not unilaterally used to their detriment. Concern for privacy was generally low, provided antecedent conditions were met. Research limitations/implications As the study uses an exploration for discovery approach, the main limitation of this study is its small sample. However, this research aimed to identify metathemes and issues that may be the focus of future research in this area and is, therefore, not proposing to suggest strong conclusions and definitive answers. Originality/value This paper presents the first empirical research to examine data privacy issues in the UK insurance context. It contributes to knowledge in the areas of motivation, applied ethics and online consumer behaviour in general.

Download Full-text