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Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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Open AccessEditor’s ChoiceArticle

Weather Conditions and Telematics Panel Data in Monthly Motor Insurance Claim Frequency Models

and

Risks 2023, 11(3), 57; https://doi.org/10.3390/risks11030057 - 09 Mar 2023

Viewed by 1253

Abstract

Risk analysis in motor insurance aims to identify factors that increase the frequency of accidents. Telematics data is used to measure behavioural information of drivers. Contextual variables include temperature, rain, wind and traffic conditions that are external to the driver, but may also influence the probability of having an accident, as well as vehicle and personal characteristics. This paper uses a monthly panel data structure and the Poisson model to predict the expected frequency of claims over time. Some meteorological information is included. Two types of claims are considered separately: only those related to at-fault third-party liability accidents, and all types of claims including assistance on the road. A sample of drivers in Spain in 2018–2019 is analysed with information on claiming frequency per month. Drivers were observed for seven months. Our analysis is novel because monthly summaries of telematics information are combined with weather data in a panel structure, revealing that external factors affect the expected claims frequencies. Reckless speeding behaviours and intense urban circulation increase the risk of an accident, which also increases with windy conditions. Full article

(This article belongs to the Special Issue Risks: Feature Papers 2023)

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Open AccessEditor’s ChoiceArticle

Measuring Systemic Governmental Reinsurance Risks of Extreme Risk Events

Elroi Hadad

Tomer Shushi

and

Rami Yosef

Risks 2023, 11(3), 50; https://doi.org/10.3390/risks11030050 - 23 Feb 2023

Viewed by 816

Abstract

This study presents an easy-to-handle approach to measuring the severity of reinsurance that faces a system of dependent claims, where the reinsurance contracts are of excess loss or proportional loss. The proposed approach is a natural generalization of common reinsurance methodologies providing a conservative framework that deals with the fundamental question of how much money should a government hold to prepare for natural or human-made extreme risk events that the government will cover? Although the ruin theory is commonly used for extreme risk events, we suggest a new risk measure to deal with such events in a new framework based on multivariate risk measures. We analyze the results for the log-elliptical model of dependent claims, which are commonly used in risk analysis, and illustrate our novel risk measure using a Monte Carlo simulation. Full article

(This article belongs to the Special Issue Catastrophe Risk and Insurance)

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Open AccessEditor’s ChoiceArticle

Cryptocurrency Risks, Fraud Cases, and Financial Performance

David S. Kerr

Karen A. Loveland

Katherine Taken Smith

and

Lawrence Murphy Smith

Risks 2023, 11(3), 51; https://doi.org/10.3390/risks11030051 - 23 Feb 2023

Cited by 3 | Viewed by 3364

Abstract

In this study, we examine major cryptocurrencies, present notable fraud cases, describe fraud risks, and analyze cryptocurrency financial performance. People debate whether cryptocurrency is an investment opportunity, the new Dutch Tulip Bubble, or a giant Ponzi scheme. There have been a number of high-profile fraud cases associated with cryptocurrencies, such as the FTX scandal in late 2022, thereby making fraud a real concern to current and potential future investors. Regarding financial performance, cryptocurrencies experienced a major collapse in value in the most recent period of the study, about three times worse than the major stock market indices. While in prior periods, cryptocurrencies have significantly outperformed stock market indices, recent fraud cases and the extreme volatility of cryptocurrencies indicate that investing in cryptocurrencies comes with much higher risk than traditional stock market investments. The debate over the investment potential of cryptocurrencies continues, whether they have long term value or are simply the new Dutch Tulip Bubble. The study’s findings will be useful to investors, regulators, and academic researchers regarding the cryptocurrency industry. Full article

(This article belongs to the Special Issue Cryptocurrencies and Risk Management)

Open AccessEditor’s ChoiceArticle

Optimal Investment in a Dual Risk Model

Arash Fahim

and

Lingjiong Zhu

Risks 2023, 11(2), 41; https://doi.org/10.3390/risks11020041 - 09 Feb 2023

Viewed by 922

Abstract

Dual risk models are popular for modeling a venture capital or high-tech company, for which the running cost is deterministic and the profits arrive stochastically over time. Most of the existing literature on dual risk models concentrates on the optimal dividend strategies. In this paper, we propose to study the optimal investment strategy on research and development for the dual risk models to minimize the ruin probability of the underlying company. We will also study the optimization problem when, in addition, the investment in a risky asset is allowed. Full article

(This article belongs to the Special Issue Emerging Topics in Finance and Risk Engineering—In Memory of Peter Carr)

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Open AccessFeature PaperEditor’s ChoiceArticle

Dependence Modelling of Lifetimes in Egyptian Families

Kira Henshaw

Waleed Hana

Corina Constantinescu

and

Dalia Khalil

Risks 2023, 11(1), 18; https://doi.org/10.3390/risks11010018 - 11 Jan 2023

Viewed by 1505

Abstract

In this study, we analyse a large sample of Egyptian social pension data which covers, by law, the policyholder’s spouse, children, parents and siblings. This data set uniquely enables the study and comparison of pairwise dependence between multiple familial relationships beyond the well-known husband and wife case. Applying Bayesian Markov Chain Monte Carlo (MCMC) estimation techniques with the two-step inference functions for margins (IFM) method, we model dependence between lifetimes in spousal, parent–child and child–parent relationships, using copulas to capture the strength of association. Dependence is observed to be strongest in child–parent relationships and, in comparison to the high-income countries of data sets previously studied, of lesser significance in the husband and wife case, often referred to as broken-heart syndrome. Given the traditional use of UK mortality tables in the modelling of mortality in Egypt, the findings of this paper will help to inform appropriate mortality assumptions specific to the unique structure of the Egyptian scheme. Full article

(This article belongs to the Special Issue Interplay between Financial and Actuarial Mathematics II)

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Open AccessEditor’s ChoiceArticle

Regulating Robo-Advisors in Insurance Distribution: Lessons from the Insurance Distribution Directive and the AI Act

Pierpaolo Marano

and

Shu Li

Risks 2023, 11(1), 12; https://doi.org/10.3390/risks11010012 - 04 Jan 2023

Cited by 1 | Viewed by 1455

Abstract

Insurance distributors are increasingly using robo-advisors for a variety of tasks, ranging from facilitating communication with customers to providing substantive advice. Like many other AI-empowered applications, robo-advisors have the potential to pose substantial risks that should be regulated and corrected by legal instruments. In this article, we attempt to discuss the regulation of robo-advisors from the perspective of the Insurance Distribution Directive and the draft AI Act. We ask two questions for each. (1) From a positive legal perspective, what obligations are imposed on insurance distributors by the legislation when they deploy robo-advisors in their business? (2) From a normative perspective, are the incumbent provisions within that legislation effective at ensuring the ethical and responsible use of robo-advisors? Our results show that neither the Insurance Distribution Directive nor the AI Act adequately address the emerging risks associated with robo-advisors. The rules implicated by them regarding the use of robo-advisors for insurance distribution are inconsistent, disproportionate, and implicit. Legislators shall further address these issues, and authorities such as EIOPA and national competent authorities must also participate by providing concrete guidelines. Full article

(This article belongs to the Special Issue The Risk Landscape in the Digital Transformation of Finance and Insurance)

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