Search

This study examines the capability of ChatGPT to provide financial advice based on personal finance cases. We first write our own cases and feed them to ChatGPT to get its advice (recommendations) on them. Next, we assess the quality and the validity of ChatGPT's recommendations on these cases. We find that ChatGPT serves as a suitable starting point, but its recommendations tend to be generic, and they often overlook alternative solutions and viewpoints and priority of recommendations. Overall, our analysis demonstrates the strengths and weaknesses of using ChatGPT in personal finance matters. Further, it serves as a helpful guide to financial advisors, households, and instructors of personal finance who are already using or considering using ChatGPT and want to develop a suitable understanding of the benefits and limitations of this new technology in addressing their professional and personal needs. [ABSTRACT FROM AUTHOR]

In today's complex economic environment, individuals and households alike grapple with the challenge of financial planning. This paper introduces novel methodologies for both individual and cooperative (household) financial budgeting. We firstly propose an optimization framework for individual budget allocation, aiming to maximize savings by efficiently distributing monthly income among various expense categories. We then extend this model to households, wherein the complexity of handling multiple incomes and shared expenses is addressed. The cooperative model prioritizes not only maximized savings but also the preferences and needs of each member, fostering a harmonious financial environment, whether they are short-term needs or long-term aspirations. A notable innovation in our approach is the integration of recommendations from a large language model (LLM). Given its vast training data and potent inferential capabilities, the LLM provides initial feasible solutions to our optimization problems, acting as a guiding beacon for individuals and households unfamiliar with the nuances of financial planning. Our preliminary results indicate that the LLM-recommended solutions result in budget plans that are both economically sound, meaning that they are consistent with established financial management principles and promote fiscal resilience and stability, and aligned with the financial goals and preferences of the concerned parties. This integration of AI-driven recommendations with econometric models, as an instantiation of an extended coevolutionary (EC) theory, paves the way for a new era in financial planning, making it more accessible and effective for a wider audience, as we propose an example of a new theory in economics where human behavior can be greatly influenced by AI agents. [ABSTRACT FROM AUTHOR]

The psychological implication of retirement is underemphasised. This study examined the relationship between proactive personality, social comparison, and retirement anxiety among Nigerian civil servants. The study is a cross-sectional design, using proactive personality, social comparison orientation, and Nigerian pre-retirement anxiety scales. Five hundred and eight staff members in government-owned tertiary institutions with five years or less to go until retirement, and at a mean age of 57.47 (SD = 3.02), were surveyed. The study established that a proactive personality negatively predicted retirement anxiety and that civil servants engage in diverse forms of intrapreneurship/entrepreneurship to augment their savings. The study also revealed that social comparison (opinion) mediated the relationship between proactive personality and retirement anxiety (financial preparedness and social alienation). In addition, the study found that social comparison (opinion and ability) mediated the relationship between proactive personality and retirement anxiety (financial preparedness) in a sequential order. The findings suggest that retirees in Nigeria face complex challenges, including financial unpreparedness, social alienation, and uncertainty. The study highlights the importance of understanding the relationship between personality traits, social comparison, and retirement anxiety in order to develop effective interventions and policies that support retirees in Nigeria. [ABSTRACT FROM AUTHOR]

Estate planning is a financial tool for an individual to manage wealth upon his incapacitation or death. Although there are numerous studies on estate planning, there still needs to be an effort to systematically review the estate planning measurements. The paper aims to systematically review the literature published between 1990 to 2021 and evaluate the measures of estate planning and its methodological qualities. The systematic literature review process was guided by the PRISMA protocol, where the articles were selected based on established databases such as WOS, SCOPUS, and Google Scholar. The final sample of 24 articles was reviewed for the estate planning measurement, and it was found that previous studies examined estate planning as a tool for financial, wealth distribution, and succession planning. The measurements of only 10 studies were found to be sufficiently validated, rendering other studies under review to be inadequate in establishing sound empirical conclusions. This review contributes to assisting future researchers in choosing well-validated measurements of estate planning and adapting them accordingly to each context. [ABSTRACT FROM AUTHOR]

The dynamics of the financial reliability of insurers show rather unstable and often unfavorable trends, which indicate an increase in the risks of their financial insecurity and requires searching for reserves to improve their financial condition in the context of digitalization. The aim of the present research is to develop approaches for managing financial risks and profitability in Russian insurance companies in the context of digitalization. Structurally, the study consisted of a comprehensive analysis of the insurance market in the Russian Federation, as well as an identification of the components of the risk management process of insurance companies in the context of digitalization. Documents containing key features of the risk management system were selected for the study. We determined that to optimize the structure of the insurance portfolio, the insurer must regulate its portfolio by increasing the share of insurance receipts for personal insurance, which is highly profitable but occupies a meager share in the insurance portfolio. To do this, it is necessary to carry out active work to expand the insurance field, in particular, in relation to voluntary personal insurance, attracting a significant number of policyholders by conducting explanatory mass work using advertising events and agency-broker networks regarding the need and effectiveness of such insurance. Further research prospects should include proposals for replenishing the insurance portfolio with new types of personal insurance, making adjustments to the tariff policy of insurers for all types of voluntary personal insurance, and determining optimal tariffs. [ABSTRACT FROM AUTHOR]

Stop-loss reinsurance is a risk management tool that allows an insurance company to transfer part of their risk to a reinsurance company. Ruin probabilities allow us to measure the effect of stop-loss reinsurance on the solvency of the primary insurer. They further permit the calculation of the economic capital, or the required initial capital to hold, corresponding to the 99.5% value-at-risk of its surplus. Specifically, we show that under a stop-loss contract, the ruin probability for the primary insurer, for both a finite- and infinite-time horizon, can be obtained from the finite-time ruin probability when no reinsurance is bought. We develop a finite-difference method for solving the (partial integro-differential) equation satisfied by the finite-time ruin probability with no reinsurance, leading to numerical approximations of the ruin probabilities under a stop-loss reinsurance contract. Using the method developed here, we discuss the interplay between ruin probability, reinsurance retention level and initial capital. [ABSTRACT FROM AUTHOR]

Customer relationship management and marketing analytics have become critical for non-life insurers operating in highly competitive markets. As it is easier to develop an existing customer than to acquire a new one, cross-selling and retention are key activities. In this research, we focus on both car and household-liability insurance products and consider the time a customer owning only a single product takes before buying the other product at the same insurer. Based on longitudinal consumer data from a Swiss insurance company covering the period from 2011 to 2015, we aim to study the factors driving the duration to cross-selling. Given the different dynamics observed in both products, we separately study the car and household-liability insurance customer cohorts. Considering the framework of survival analysis, we provide descriptive statistics and Kaplan–Meier estimates along major customer characteristics, contract history and distribution channel usage. For the econometric analysis of the duration, we compare the results from Cox and accelerated failure time models. We are able to characterize the times related to the buying behavior for both products through several covariates. Our results indicate that the policyholder age, the place of residence, the contract premium, the number of contracts held, and the initial access channel used for contracting influence the duration to cross-selling. In particular, our results underline the importance of the tied agent channel and the differences along the geographic region and the urbanicity of the place of residence. By quantifying the effects of the above factors, we extend the understanding of customer behavior and provide a basis for developing models to time marketing actions in insurance companies. [ABSTRACT FROM AUTHOR]

With COVID-19 still making headlines around the world, many people currently feel uncertain about many aspects of life, including family financial planning and wealth management. Financial planning is important at all times, but it becomes essential during a crisis such as the coronavirus pandemic, which has disrupted people's finances. Some economic consequences are already apparent, but the financially-induced stress caused by the uncertainty is less visible. With the increase in family wealth and size of organizations, there is a comparable increase in their assets. There is considerable demand for professionals to manage these assets and coordinate investment activities in order to maintain growth. This raises the issue of how to increase a wealth management bank's competitive advantages. This study approached the issue by using experts and the application of fuzzy logic and decision-making trial and evaluation laboratory and multiple criteria decision-making to segment a set of the selection criteria used by prospective customers, to select a wealth management bank that can effectively manage personal wealth. The results showed that the management's learning and growth perspective was the most important factor in respondents' selection of a wealth management bank. This paper also provides managerial practice implications. [ABSTRACT FROM AUTHOR]

A stable and healthy insurance industry plays a vital role in sustaining an economy resistant to economic shocks by providing an efficient risk-transition mechanism. There is a relative scarcity of research inspecting the impact of insurers' financial insolvency on the profitability of insurance firms. Employing 2011–2019 panel data of 16 non-life insurance companies operating in Bangladesh, this research endeavors to examine the impacts of insurers' financial insolvency on the profitability of insurance companies measured by return ratios, return on assets (ROA), and return on equity (ROE). Fixed-effect regression outcome implies that insurers' financial insolvency has a significant adverse influence on non-life insurance companies' profitability. Further findings indicate that financial leverage, technical provision, age, and inflation have a noteworthy adverse influence on profitability. The outcomes of this research are of greater significance for policymakers in tackling insolvency and formulating policies to boost the growth of insurance profitability. In addition, this study aims to serve as a benchmark for other countries' insurance industries to emulate recovery strategies from financial insolvency. [ABSTRACT FROM AUTHOR]

The objective of the study was to identify the main factors influencing farmers' willingness to take up agricultural insurance and participate in a mutual fund for non-insurable risks in the Czech Republic. Responses from 214 representative farms were processed using descriptive statistics, paired t-tests, binary logistic regression, and contingency analysis. The regression model showed the influences of agricultural area, distrust in insurance companies, the probability of losing more than 20% of production, the price of insurance premiums, and having a developed formal strategy on the likelihood of taking up agricultural insurance. Unlike previous empirical studies, this study did not attempt to look at agricultural insurance as an isolated risk management tool but rather to show the interrelationship between farmers' decisions to join a mutual fund and their choice of agricultural insurance. Farmers expect most agricultural production risks to become significantly more important. With the ongoing economic crisis in the EU, there is growing pressure to reduce ad hoc public spending on coverage of non-insurable risks and to seek alternative solutions. The study also shows the need for a holistic approach to the design of risk management support systems in EU countries. [ABSTRACT FROM AUTHOR]

In Australia, there are over 20,000 financial advisers, with only 1% registered as independent financial advisers. This study investigates why there has been no significant transition to independent advising. The importance of the study is underlined by the substantial losses suffered by thousands of consumers from advice that has been found to be influenced by conflicts of interest. Using a qualitative technique, the study undertook exploratory semi-structured interviews among financial advisers. The study found that over 90% of privately owned advisers will not be transitioning to independent advising due to the belief that clients will not pay fees for insurance advice. The study finds strong evidence that the affordability of paying fees for insurance advice arguably outweighs the conflicts of interest associated with non-independent insurance advice. [ABSTRACT FROM AUTHOR]

Life insurers, whose contractual liabilities include providing minimum guaranteed interest rates to policyholders, are significantly affected by persistently low interest rates. Hence, this study reviews the literature on the prolonged low interest rate environment and its impact on the life insurance industry, incorporating multiple perspectives and practices in different countries. The effect of low interest rates on life insurance products depends on the sensitivity of the interest rate of each product type and the level of minimum interest rate guarantee. In addition, their impacts on the valuation of life insurance companies depend on shifts in the valuation interest rate, which is used to discount the present value of future benefits, as well as the financial and solvency issues faced by insurers. Overall, the literature suggests that insurers need both short- and long-term solutions to respond to a prolonged low interest rate environment. [ABSTRACT FROM AUTHOR]

The detection of anomalous data patterns is one of the most prominent machine learning use cases in industrial applications. Unfortunately very often there are no ground truth labels available and therefore it is good practice to combine different unsupervised base learners with the hope to improve the overall predictive quality. Here one of the challenges is to combine base learners that are accurate and divers at the same time, where another challenge is to enable model explainability. In this paper we present BHAD, a fast unsupervised Bayesian histogram anomaly detector, which scales linearly with the sample size and the number of attributes and is shown to have very competitive accuracy compared to other analyzed anomaly detectors. For the problem of model explainability in unsupervised outlier ensembles we introduce a generic model explanation approach using a supervised surrogate model. For the problem of ensemble construction we propose a greedy model selection approach using the mutual information of two score distributions as a similarity measure. Finally we give a detailed description of a real fraud detection application from the corporate insurance domain using an outlier ensemble, we share various feature engineering ideas as well as discuss practical challenges. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate Pension Benefit Guaranty Corporation (PBGC) insurance values through regime-switching models. We separate periods of the economy with faster growth from those with slower growth to observe long-term trends in the economy. We derive a fair PBGC insurance pricing formula under distress termination and intervention termination using regime-switching processes. We set parameters by estimating the S&P 500 index and one-year treasury bills via expectation maximization particle swarm optimization (EM-PSO)-Gradient, which is an extension of the EM-Gradient method. Then, we conduct sensitivity analysis to investigate the impact of model parameters on insurance values. According to the maximum likelihood estimation results, the Akaike information criterion (AIC) and Bayesian information criterion (BIC) estimators show that the regime-switching process has better goodness of fit than the geometric Brownian motion. Scenario analysis also supports the adequacy of our pricing formula. [ABSTRACT FROM AUTHOR]

We introduce here a diffusion-type approximation of the ruin probability both in finite and infinite time for a two-dimensional risk process, where claims and premiums are shared with a predetermined proportion. This type of process is often called the insurer–reinsurer model. We assume that the flow of claims is governed by a general renewal process. A simple ruin probability formula for the model is known only in infinite time for the special case of the Poisson process and exponentially distributed claims. Therefore, there is a need for simple analytical approximations. In the literature, in the infinite-time case, for the Poisson process, a De Vylder-type approximation has already been introduced. The idea of the diffusion approximation presented here is based on the weak convergence of stochastic processes, which enables one to replace the original risk process with a Brownian motion with drift. By applying this idea to the insurer–reinsurer model, we obtain simple ruin probability approximations for both finite and infinite time. We check the usefulness of the approximations by studying several claim amount distributions and comparing the results with the De Vylder-type approximation and Monte Carlo simulations. All the results show that the proposed approximations are promising and often yield small relative errors. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change is accelerating, and severe and widespread consequences are expected in many areas. Although the insurance sector is not closely associated with any of the sustainability dimensions, expectations may change rapidly. Against this background, we analyze the role of insurers, especially in the property and casualty areas, in addressing the environmental and climate risk challenges and developing a truly sustainable, environmentally friendly business model—green insurance. Building on the Principles of Sustainable Insurance set by the United Nations, we develop a comprehensive roadmap along the insurance value chain for executive management to design their company's sustainability efforts, with special focus on property and casualty. The roadmap indicates actions to be taken as well as metrics to be managed in product development, marketing and sales, risk management and underwriting and operations and claims management towards green insurance. The existing products, risk appetite and operational processes must be reviewed to support sustainability goals and include the full portfolio of activities, including claims. The time to act is now, the sustainability journey is complex and the proposed business model transformation should provide benefits for early movers. [ABSTRACT FROM AUTHOR]

Climate insurance has become a crucial issue due to the increasing number of climate-related catastrophic events and the associated losses for the economy in general and insurance companies in particular. The extremely hot and dry summers of 2018 and 2019 in some European countries highlighted existing weaknesses in European agricultural insurance mechanisms, with farmers having to wait for months before compensation payments could be made. Our paper compares features of yield-based insurance and index-based insurance (IBI) in agriculture in the light of new developments and trends in information technology (IT). The results show that applying Distributed Ledger Technologies (DLT) in combination with IBI could not only resolve existing problems but also facilitate the development of innovative risk management tools under the EU's Common Agricultural Policy (CAP) post-2020 reform. [ABSTRACT FROM AUTHOR]

Actuaries utilize demographic features such as mortality and longevity rates for pricing, valuation, and reserving life insurance and pension contracts. Capturing accurate mortality estimates requires factual mortality assumptions in mortality models. However, the dynamic and uncertain nature of mortality improvements and deteriorations necessitates better approaches in tracking mortality changes, for instance, using the causes of deaths features. This paper aims to determine temporal homogeneous clusters using unsupervised learning, a clustering approach to group causes of death based on (dis)similarity measures to set representative clusters in detection and monitoring death trends. The causes of death dataset were derived from the World Health Organization, Global Health Estimates for males and females, from 2000 to 2019, for Kenya. A hierarchical agglomerative clustering technique was implemented with modified Dynamic Time Warping distance criteria. Between 6 and 14 clusters were optimally achieved for both males and females. Using visualisations, principal clusters were detected. Over time, the causes of death trends of these clusters have demonstrated a correlated association with mortality and longevity rates, rationalizing why insurance and pension offices may include this approach as a preliminary step to undertake mortality and longevity modelling. [ABSTRACT FROM AUTHOR]

The life expectancy rate of individuals worldwide has risen, and Saudi Arabia is not excluded. Rising long-life expectancy may jeopardize employees' pensions and reduce the chances of adequate earnings and a decent life after retirement. Moreover, the number of employees, who have paid into pension funds and are now retired, has increased, indicating that pension funds are expected to decrease. Apart from the above, the level of financial literacy in Saudi Arabia was substandard. Therefore, the ultimate objective of this research is to examine the measurable factors that could impact employees in their financial planning for retirement (FPR). These factors comprise the employee's financial literacy (FL), financial risk tolerance (FRT), and cultural factors based on the CWO model. Moreover, this study aims to investigate the mediating roles of culture in their relationship with financial planning for retirement. Primary data was collected during the COVID-19 pandemic from mid-July 2020 until the end of January 2021 using a non-probability convenience sampling approach involving 525 participants. The Structural Equation Modelling (SEM) technique was used to analyze the data. To determine the type of study variables, either a formative or reflective model of Confirmatory Tetrad Analysis (CTA-PLS) was used. The results show the significant influence of basic FL, FRT, and culture on FPR. Moreover, it shows the critical role of culture among those with advanced FL and FRT. Previous studies have examined FL and FRT in FPR without considering the effect of culture as a mediator. [ABSTRACT FROM AUTHOR]

In this paper, we present a new family of bivariate mixed exponential regression models for taking into account the positive correlation between the cost of claims from motor third party liability bodily injury and property damage in a versatile manner. Furthermore, we demonstrate how maximum likelihood estimation of the model parameters can be achieved via a novel Expectation-Maximization algorithm. The implementation of two members of this family, namely the bivariate Pareto or, Exponential-Inverse Gamma, and bivariate Exponential-Inverse Gaussian regression models is illustrated by a real data application which involves fitting motor insurance data from a European motor insurance company. [ABSTRACT FROM AUTHOR]

The aim of this article is to identify the risk and the likelihood of potential consequences of the COVID-19 pandemic on the business insurance market in the medium- and long-term horizon. The first section of this elaboration presents the theoretical approach connected with the nature of the pandemic. The second section outlines the presentation of the COVID-19 measurement rules and the third describes the potential effects of COVID-19 on the insurance market. Contrary to other elaborations on this topic which have appeared so far (these are mostly reports describing the financial market in short- and long-term horizons), here, the authors present the medium-term horizon as well. The possible consequences of COVID-19 are outlined both in relation to the insurance company client, e.g., change in the amount of the insurance premium under the insurance agreement, as well as in relation to the insurer, e.g., appearance of innovative and competitive offers (Trott's concept Special attention has been paid to the way in which the insurer's strategy (scenario analysis) may be used to build resilience to other crises as well as to the planning of emergency solutions. Actual events confirm the hypothesis that changes in the business insurance market dominated the losses in the aftermath of the pandemic. [ABSTRACT FROM AUTHOR]

In policy-making, the design of a policy is considered to be one of the most significant steps. A well designed policy will be able to solve sectoral problems across stakeholders as well as support the competitive development of the entire economy. Enterprises of the maritime sector have been influenced by environmental, social, and governance (ESG) changes with the push coming from financiers, insurers, regulators, and customers. To meet the ESG challenges and utilize the benefits ahead, they need to be addressed in the new policy design processes. The specificities of a maritime sector as well as science-based policy-making framework are the fundamentals of successful maritime policy development. Estonia is located on the eastern border of the EU, and has always aimed to be a maritime state. National maritime policy has been adopted (2012–2020) and currently, the Estonian Transport and Mobility Master Plan incorporates maritime aspects. Actors of the maritime sector have remained dissatisfied and advocate the reinstatement and redevelopment of Estonian maritime policy. The aim of this study was to present a framework for the design of maritime policy that uses maritime economics, ESG performance goals, and policy design analyses as inputs. As a result, a maritime policy design framework is proposed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this article is to describe the initial concept of household bridging insurance. Design/methodology/approach: In the first part of the article, an extensive literature review is made. This is made to show the research gap of insufficient protection of households against destabilization resulting from the lost personal contribution. Data shown in the text present the scale of the loss of lost unpaid work (based on household time budgets). The existing methods of managing this loss, based on social insurance, are also shown. Findings: This paper discusses the possibility of creating a new insurance. Its need is indicated (research gap, the scale of the problem, and insufficient protection by the social insurance system) and a preliminary outline of its structure is indicated (annuities character, dynamic sum insured related to the lifecycle of the household). The article contains the theoretical background of the new product, and introduces further research on the use of multistate models in the construction and calculation of insurance premiums. Originality/value: So far, studies concerning, inter alia, personal damage indicate the lost personal contribution (unpaid work for household members) and even try to evaluate it. However, no private insurance has been proposed to mitigate the destabilization resulting from the death of an adult household member. The article therefore proposes a new life insurance (a separated policy or as an extension option) that would help the household to return to normal operation after the death of one of the household members. [ABSTRACT FROM AUTHOR]

This paper explores the tuning and results of two-part models on rich datasets provided through the Casualty Actuarial Society (CAS). These datasets include bodily injury (BI), property damage (PD) and collision (COLL) coverage, each documenting policy characteristics and claims across a four-year period. The datasets are explored, including summaries of all variables, then the methods for modeling are set forth. Models are tuned and the tuning results are displayed, after which we train the final models and seek to explain select predictions. Data were provided by a private insurance carrier to the CAS after anonymizing the dataset. These data are available to actuarial researchers for well-defined research projects that have universal benefit to the insurance industry and the public. Our hope is that the methods demonstrated here can be a good foundation for future ratemaking models to be developed and tested more efficiently. [ABSTRACT FROM AUTHOR]

The rapid growth over recent decades of the impact of natural disasters on economies, especially in vulnerable areas, urges stakeholders to promote innovative solutions involving risk transfers that account for the new risk exposures. These proposed solutions are designed to optimize and expedite the indemnification process, which can ultimately be beneficial for both policyholders and insurers alike. This article explores the possibility of supplementing the current Romanian dwelling insurance protection scheme with a parametric mechanism. To determine the triggering parameter of the insurance pay-out, the authors consider various hazard scenarios developed based on historical events. This paper focuses on Probable Maximum Loss (PML) determination computed for events with epicenters in the Vrancea (a region and a mountain in the Carpathians) seismic area. This area is the most exposed in Romania to earthquakes, and it includes the capital, Bucharest, which is the urban area with the highest population concentration and, consequently, the highest exposure to the discussed risks. [ABSTRACT FROM AUTHOR]

This study aims to examine the determinants of investors' behavioral intentions to participate in the stock market. In this attempt, this research investigated the direct and moderating effects of the financial cognitive abilities and the financial considerations on the nexus of attitudes and behavioral intentions of investors. Data for this study were collected from active and potential investors in the Dhaka Stock Exchange of Bangladesh using a structured questionnaire. The partial least squares method was used to examine the nature and extent of the relationships of investors' behavioral intentions with their attitude, financial cognitive abilities, and financial considerations in making stock market investment-related decisions. The findings of this study suggest that investors' attitudes, financial planning ability, and perceptions of financial risks and benefits are important factors that influence their decisions in stock market participation. Moreover, financial planning, financial satisfaction, and perceived financial risk moderate the nexus of attitude and behavioral intentions to participate in the stock market. This study, therefore, has significant implications for policymakers, stock market regulators, and financial service providers. [ABSTRACT FROM AUTHOR]

US crop insurance is subsidized to encourage producers to participate and reduce their risk exposure. However, what has been the impact of these subsidies on insurance demand and crop acres planted? Using a simultaneous system of two equations, we quantify both insurance participation and acreage response to subsidized crop insurance for cotton-producing counties across the US at the national and regional levels. We also quantify the impact of both the realized rate of return and the expected subsidy per pound, plus the combined effects of expected yield and price while accounting for the adoption of Bacillus thuringiensis (Bt) technology and other factors. Results show that both the rate of return and the expected subsidy per unit of production have a statistically significant and positive effect on the percentage of arable acres planted. Furthermore, the marginal effect of expected price on insurance participation is much more significant for low-than high-yield counties. Results indicate that not all regions respond the same to subsidized crop insurance and that subsidies should be based on dollars per expected unit of production rather than expected production to be less distorting. Overall, US cotton acreage response is estimated to be inelastic (0.58) to insurance participation. [ABSTRACT FROM AUTHOR]

The high volatility in financial markets, together with the ultra-low interest rates environment and the increased expectation of life, constitute serious threats for providers of long-term investment guarantees and lifelong benefits. The paper by [3] ([3]) addresses the problem of approximating the future value distribution of a large and heterogeneous life insurance portfolio by proposing two regression-based methodologies: the former is an extension of the well-known least squares Monte Carlo approach; the latter is grounded on the class of generalized beta distribution of the second kind. Then, a more accurate assessment of these risks enables enlargement of the insurance portfolios and to keep premiums at reasonable levels. [Extracted from the article]

One of the most difficult problems analysts and decision-makers may face is how to improve the forecasting and predicting of financial time series. However, several efforts were made to develop more accurate and reliable forecasting methods. The main purpose of this study is to use technical analysis methods to forecast Jordanian insurance companies and accordingly examine their performance during the COVID-19 pandemic. Several experiments were conducted on the daily stock prices of ten insurance companies, collected by the Amman Stock Exchange, to evaluate the selected technical analysis methods. The experimental results show that the non-parametric Exponential Decay Weighted Average (EDWA) has higher forecasting capabilities than some of the more popular forecasting strategies, such as Simple Moving Average, Weighted Moving Average, and Exponential Smoothing. As a result, we show that using EDWA to forecast the share price of insurance companies in Jordan is good practice. From a technical analysis perspective, our research also shows that the pandemic had different effects on different Jordanian insurance companies. [ABSTRACT FROM AUTHOR]

This article aims to evaluate the effect of insurance on production, technical efficiency, and input use of Italian specialised-quality grape growers. A panel instrumental variable stochastic frontier approach is applied over the years 2008–2017 using data from the Farm Accountancy Data Network. The results show the requirement to correct for the endogeneity that stems from insurance adoption. Insurance has an enhancing effect on production and efficiency and reduces the use of intermediate inputs. It suggests that insurance helps to diminish the risk-averse farmers' suboptimal input use due to the presence of uncertainty. Crop insurance leads risk-averse farmers to behave as if they were risk neutral and employs the profit-maximising input vector. Therefore, by reducing the risks linked to the uncertainty of outcomes, crop insurance leads grape growers to go in the direction of profit maximisation. [ABSTRACT FROM AUTHOR]

Every US state requires private health insurers to cover certain conditions, treatments, and providers. These benefit mandates were rare as recently as the 1960s, but the average state now has more than forty. These mandates are intended to promote the affordability of necessary health care. This study aims to determine the extent to which benefit mandates succeed at this goal. Using fixed effects and difference-in-difference research designs with data from the restricted Medical Expenditure Panel Survey—Household Component (MEPS-HC), it provides the first empirical estimates of how health insurance benefit mandates affect out-of-pocket costs and total spending on health care. Both strategies find that mandates significantly reduce out-of-pocket spending, but they are divided on whether mandates also reduce overall health care spending and spending by private insurers. [ABSTRACT FROM AUTHOR]

This paper reports the results of analysing desk-based data on organisational support for high performance athletes to develop their financial literacy and self-management skills when transitioning out of sport. There are two research questions: (1) Do sport organisations provide support schemes or other interventions such that high-performance athletes develop their financial literacy and self-management skills? and (2) Do sport organisations provide financial support schemes for high-performance athletes' retirements? If so, what do they involve? Desk-based data collection was applied to 23 sporting organisations; these comprised 21 national organisations representing 19 countries, the International Olympic Committee (IOC) and the Oceanic National Olympic Committee (ONOC). Fifteen of the 23 organisations, representing 14 countries, provided some support or interventions on financial planning and self-management within their career assistance programmes. The findings also indicate that most organisations in 17 different countries did not provide any financial support for athletes' retirements. While a number of sport organisations have developed appropriate interventions to assist high-performance athletes to develop financial literacy and self-management skills, such schemes appear only to be provided to high-performance athletes who have competed at the highest level e.g., Olympics, world championships, etc. Support for athletes at lower levels should also be developed and delivered by national governments, or by national sport organisations. [ABSTRACT FROM AUTHOR]

The risk-based capital (RBC) ratio, an insurance company's financial soundness system, evaluates the capital adequacy needed to withstand unexpected losses. Therefore, continuous institutional improvement has been made to monitor the financial solvency of companies and protect consumers' rights, and improvement of solvency systems has been researched. The primary purpose of this study is to find a set of important predictors to estimate the RBC ratio of life insurance companies in a large number of variables (1891), which includes crucial finance and management indices collected from all Korean insurers quarterly under regulation for transparent management information. This study employs a combination of Machine learning techniques: Random Forest algorithms and the Bayesian Regulatory Neural Network (BRNN). The combination of Random Forest algorithms and BRNN predicts the next period's RBC ratio better than the conventional statistical method, which uses ordinary least-squares regression (OLS). As a result of the findings from Machine learning techniques, a set of important predictors is found within three categories: liabilities and expenses, other financial predictors, and predictors from business performance. The dataset of 23 companies with 1891 variables was used in this study from March 2008 to December 2018 with quarterly updates for each year. [ABSTRACT FROM AUTHOR]

The drivers of financial success of the insurance industry are of interest to several players in any economy including the government; policymakers; policyholders; and investors. In Kenya; there have been relatively few studies on this topic; most of which look at narrow elements that determine insurance companies' performance. This article sought to explore the components contributing to the financial performance of insurance firms. We employed a sample consisting of 37 general insurers and 16 life insurers for the period running from 2009 to 2018 and utilised panel data methods in order to establish the determinants of financial performance of Kenyan insurers. The pooled OLS; fixed effects and random effects models were estimated with the financial performance measures (proxied by either ROA or ROE) as the dependent variables. The results of the study documented that insurer financial performance and size were positively related. The study also found that insurer financial performance was negatively related to the age variable. The study also unraveled that higher leveraged insurance companies performed better than their lowly geared peers. This article provides broad analyses of the various drivers of financial performance of the insurance industry in Kenya. The findings of this study contribute to the academic literature on the financial performance of the insurance sector in Kenya and Africa as a whole. Furthermore; it gives pointers to the management of insurance companies on the aspects of their business that would need greater attention to drive and sustain superior financial performance. [ABSTRACT FROM AUTHOR]

Cyber insurance ratemaking (CIRM) is a procedure used to set rates (or prices) for cyber insurance products provided by insurance companies. Rate estimation is a critical issue for cyber insurance products. This problem arises because of the unavailability of actuarial data and the uncertainty of normative standards of cyber risk. Most cyber risk analyses do not consider the connection between Information Communication and Technology (ICT) sources. Recently, a cyber risk model was developed that considered the network structure. However, the analysis of this model remains limited to an unweighted network. To address this issue, we propose using a graph mining approach (GMA) to CIRM, which can be applied to obtain fair and competitive prices based on weighted network characteristics. This study differs from previous studies in that it adds the GMA to CIRM and uses communication models to explain the frequency of communications as weights in the network. We used the heterogeneous generalized susceptible-infectious-susceptible model to accommodate different infection rates. Our approach adds up to the existing method because it considers the communication frequency and GMA in CIRM. This approach results in heterogeneous premiums. Additionally, GMA can choose more active communications to reflect high communications contribution in the premiums or rates. This contribution is not found when the infection rates are the same. Based on our experimental results, it is apparent that this method can produce more reasonable and competitive prices than other methods. The prices obtained with GMA and communication factors are lower than those obtained without GMA and communication factors. [ABSTRACT FROM AUTHOR]

This study investigates the level, structure, and pay-for-performance relationship of CEO compensation in Korean non-life insurance companies. We find that seniority plays an important role in setting CEO compensation practices and that performance-based pay, such as bonus, is more effective than base salary in enhancing shareholder value for Korean non-life insurers. Unlike previous studies that show that international differences in executive pay have been diminished considerably since the 2000s, our evidence shows that there is a remarkable difference in CEO compensation between Korean non-life insurers and U.S. property-liability insurers. Furthermore, we provide evidence that the pay-performance relationship is weaker in Korean non-life insurance companies relative to US counterparts, suggesting that it is necessary for Korean non-life insurers to tie performance-based compensation more closely to shareholder value in the design of CEO compensation. [ABSTRACT FROM AUTHOR]

Technology is sometimes seen as a disruption that although provides opportunities for growth and development, also provides opportunities for deception, theft, and fraud. On the other hand, automation can make it easier to identify and protect from threats. Hence, a proposal was made by the European Commission to enact a digital operations resilience act. Therefore, our objective in this paper is to lay out the perceived characteristics of effective regulation by using DORA as our case study. We do this by carrying out a literature review and extracting using the thematic analysis approach propositions for these characteristics. Then, we test these using exploratory factor analysis and design a model for perceived effective regulation (PERM). We test the reliability and validity of this model by using the Cronbach alpha. Results show that according to our model, an effective regulation should have four characteristics, specifically "Flexibility and Integration", "Proportionality and Cost", "Reliability and Transparency", and "Relevance and Timeliness". Findings laid out in this paper and PERM can be used to test other proposed regulations to ensure that they are effective before being enacted and also to determine when there is a need for a revamp in specified areas of current regulations and requirements. [ABSTRACT FROM AUTHOR]

Often, the claims reserves exceed the available equity of non-life insurance companies and a change in the claims reserves by a small percentage has a large impact on the annual accounts. Therefore, it is of vital importance for any non-life insurer to handle claims reserving appropriately. Although claims data are time series data, the majority of the proposed (stochastic) claims reserving methods is not based on time series models. Among the time series models, state space models combined with Kalman filter learning algorithms have proven to be very advantageous as they provide high flexibility in modeling and an accurate detection of the temporal dynamics of a system. Against this backdrop, this paper aims to provide a comprehensive review of stochastic claims reserving methods that have been developed and analyzed in the context of state space representations. For this purpose, relevant articles are collected and categorized, and the contents are explained in detail and subjected to a conceptual comparison. [ABSTRACT FROM AUTHOR]

The concordance probability, also called the C-index, is a popular measure to capture the discriminatory ability of a predictive model. In this article, the definition of this measure is adapted to the specific needs of the frequency and severity model, typically used during the technical pricing of a non-life insurance product. For the frequency model, the need of two different groups is tackled by defining three new types of the concordance probability. Secondly, these adapted definitions deal with the concept of exposure, which is the duration of a policy or insurance contract. Frequency data typically have a large sample size and therefore we present two fast and accurate estimation procedures for big data. Their good performance is illustrated on two real-life datasets. Upon these examples, we also estimate the concordance probability developed for severity models. [ABSTRACT FROM AUTHOR]

There is an increasing pressure by the community and customers forcing companies to insert environmental concerns in their practices. To help companies initiatives, the green bonds market was created. Our research question is "How to select bonds in a growing billion-dollar market?" This paper presents a multi-criteria decision analysis (MCDA) model to enable investors identify opportunities based not only in opinions, but grounded on objective facts. Analytic hierarchy process (AHP), complex proportional assessment (COPRAS), full consistency method (FUCOM), step-wise Weights Assessment Ratio Analysis (SWARA), and technique of order preference similarity to the ideal solution (TOPSIS) are MCDA methods applied in this paper. Top-fifteen green bonds ranked by specialized media were assessed with the proposed MCDA model. Criteria included the Environmental Performance Index (EPI) proposed by Yale University, and common financial indicators as assets, risks (β), and dividends. The new ranks from MCDA are compared each other and compared with the rank published by specialized media. [ABSTRACT FROM AUTHOR]