Insurance Risk Research Articles

Calculation of Value at Risk of Property Fire Losses in West Jakarta with the Extreme Value Theory Method

Property fires are an inevitable disaster, but their impact can be minimized through proper risk management. In urban areas such as West Jakarta, with high population density and economic activity, fires often cause losses. In therange of 2014 to 2023, the peak of the loss occurred in 2019 of IDR 103,354,500,000. Soto avoid unwanted things, it is necessary to calculate the losses that may occur. The Extreme Value Theory (EVT) method is used in this study to analyze the risk of extreme losses. Using Peaks Over Threshold (POT), the estimated value at Risk (VaR) shows a maximum loss of IDR 86,245,771,176 (95% confidence level) and IDR 255,535,153,859 (99% confidence level). These results help manage fire insurance risks to reduce future economic impacts.

Deposit Insurance Modeling Based on Standard Power Option Payoff Using Picard–Lindelöf Iteration

Deposit insurance is a critical instrument in modern financial systems for protecting depositors’ interests and promoting financial stability. The deposit insurance finance model, which is based on the standard power option pay-off, has been considered in this paper using the Picard–Lindelöf Iteration Method (PIM). Utilizing the repetitive framework of the Picard–Lindelöf iteration approach offers insights into the dynamic behavior of deposit insurance premiums and risk assessments. The study highlights the significance of using the Picard iteration technique to better understand deposit insurance pricing and its implications for financial institutions and regulatory bodies.

Optimal risk management strategies in a diffusion risk process: a simultaneous problem

Different to previous studies, this paper studies the optimal risk management strategies with consideration of reinsurance strategies together with capital injections simultaneously for two insurance companies according to a diffusion approximation risk model whose cash surpluses are modeled with a Brownian motion and reinsurance premium rate. Our focus is on the possibility for two insurance companies to rely on reinsurance premium rate to bring the surplus difference process back to a given level if it has fallen below it and study the optimization problem in the financial market in order to maximize the insurance companies profitability. We formulate the surplus processes based on the capital injections and reinsurance by using the techniques of diffusion approximation. The explicit expressions for optimal reinsurance strategies of two insurance companies are obtained for the controlled operator function of proposal strategies with quadratic form of reinsurance premium rate. The optimal capital injection strategies are computed in the present of reflecting the surplus difference of two insurance risk processes at the upper and lower thresholds. Moreover, using It o ^ formula the risk optimization problem is solved in our risk problem. Finally, numerical analyses are conducted to illustrate the effects of model parameters on the optimal risk management strategies.

Large-scale flood risk assessment in data-scarce areas: an application to Central Asia

Abstract. The countries of Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan in Central Asia are highly prone to natural hazards, particularly floods, earthquakes, and landslides. The European Union, in collaboration with the World Bank and the Global Facility for Disaster Reduction and Recovery (GFDRR), created the programme Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) to advance disaster and climate resilience in the region. As part of the SFRARR project, the “Regionally consistent risk assessment for earthquakes and floods and selective landslide scenario analysis for strengthening financial resilience and accelerating risk reduction in Central Asia” was developed to achieve the project's objectives. This article presents the data, model, methodology, and results for the five Central Asian countries of the flood risk assessment, which represents the first high-resolution regional-scale transboundary risk assessment study in the area aiming to provide tools for decision-making. The output information will inform and enable the World Bank to initiate a policy dialogue. A fully probabilistic risk assessment for fluvial floods has been carried out for these countries to support regional and national risk financing and insurance applications, including potential indemnity and/or parametric risk financing solutions for a regional programme. A homogenised risk assessment methodology for the five countries and across multiple hazards (floods and earthquakes) and asset types has been adopted to obtain strategic financial solutions consistent across geographical areas and economic sectors. The largest relative (to the total exposed value) expected annual damages are found in Kazakhstan and Tajikistan, with values above 6 ‰. In the five considered countries, the largest relative expected annual damages by sector are found for the transport and agricultural sectors. Climate change is expected to have contrasting impacts, with increases in risk for some regions (the most severe increase is found in the Mangistauskaya region in Kazakhstan) and decreases for other regions (Lebap, Turkmenistan; Khatlon, Tajikistan; Samarkand, Uzbekistan; and Batken, Kyrgyz Republic).

Credit Risk Influence on Insurance Performance During Credit Restructuring Policy

This study analyzes the relationship between banking credit risk and general insurance performance during the banking credit restructuring policy period in Indonesia from March 2020 to March 2024. Credit, Nonperforming loans (NPL), and credit interest rates variables are used as proxies for banking risk. General insurance performance is proxied by credit premium, credit claim, and profit before tax. Through multiple regression analysis using Ordinary Least Squares (OLS), this study shows that there is a significant effect of banking risk on general insurance performance. The relationship between banking and insurance can be a complementary or substitution relationship, depending on how important risk transfer and capital allocation. The result provides useful insights to achieve co-evolution of banking and insurance in maintaining financial system stability. Keywords: banking credit risk; credit restructuring policy; general insurance performance

On assessing the sustainability of functioning of microparametric cyber risk insurance facilities

On assessing the sustainability of functioning of microparametric cyber risk insurance facilities

Evaluating Producer Welfare Benefits of Whole-Farm Revenue Insurance

Agricultural insurance is by far the most popular risk management tool used in Iran. Despite many years of experience, Iran’s current insurance policy has not managed to protect all producers in the sector. The basic principle of whole-farm insurance consists of pooling all the insurable risks of a farm into a single policy and overcoming most of the major impediments to existing policies. This study aimed to evaluate the benefits of whole-farm insurance (WFI) in Zanjan province of Iran. This study employed historical farm-level and county-level data from 1982 to 2021 to estimate yield and price density functions and predict future values. Parametric and non-parametric approaches were utilized to calculate farmers’ expected compensation and guaranteed and simulated revenues. The premium rates were then calculated using the PQH simulation and Cholesky decomposition and compared under three scenarios: the single-crop, double-crop, and triple-crop options. Finally, farmers’ welfare benefits were compared under the three scenarios with the no-insurance case. The results demonstrate that WFI provides lower loss ratios compared to yield insurance and crop-specific insurance. Furthermore, producer welfare can be improved when they insure at least one crop compared to no-insurance. For example, the welfare benefits of insuring wheat, barley, alfalfa, wheat–barley, wheat–alfalfa, barley–alfalfa, and barley–alfalfa in terms of cost reduction to producers at 75% coverage are 8.8, 1.8, 2.9, 1.2, 0.9, and 1.8, respectively. Therefore, we recommend that the Iranian Agricultural Insurance Fund adopts WFI as a new risk management tool. This policy has the potential to decrease insurance premiums and administrative costs while improving the certainty equivalents and benefits to farmers through crop insurance.

Legal aspects of the reform of life and health insurance of passengers on land transport

The article is devoted to the issues of reforming the system of insurance protection of passengers during their transportation by regular routes of public land transport. The author analyzes the provisions of the national legislation on insurance of transport risks, in particular, examines the legal essence of the changes that occurred as a result of the insurance sector reform, which took place in 2021–2024. The author emphasizes that as a result of bringing the legislation of Ukraine on insurance into line with the norms of the EU acquis, the contractual structure of passenger insurance has undergone changes, in particular, there has been a transition from insurance of life and health of passengers to insurance of the risk of liability of the carrier for causing harm to passengers during transportation with a corresponding change in the parties to the insurance contract and the financial burden of its execution by the insured; the reform led to an increase in the amount of insurance coverage in the event of insured events, at the same time, the list of such events has also undergone significant changes due to the change in insured risks. Also, the negative practice of the central executive authorities of Ukraine, contrary to the direct instruction of the Parliament of Ukraine, not to ensure timely alignment of their subordinate regulatory framework, necessary for the implementation of the reforms proposed by law, with the newly adopted Laws of Ukraine, was noted. Thus, there are cases of both the absence of regulatory legal acts that should have been developed, and cases of leaving in force regulatory legal acts that are already clearly outdated and contrary to the law, and therefore only create legal uncertainty in the regulation of insurance relations in the transport sector. Thus, business entities – carriers, especially the railway, are forced to violate the requirements of the law. As a result, the author concludes that the successful completion of the reform of passenger insurance on land transport in Ukraine requires additional efforts in the field of regulatory activities, in particular: the adoption of the order of the Ministry of Development of Communities and Territories of Ukraine on the procedure and conditions for implementing liability insurance on railway transport, as well as the cancellation of the resolution of the Cabinet of Ministers of Ukraine No. 959 of 14.08.1996, which directly contradicts the Civil Code of Ukraine and the current Law of Ukraine «On Insurance».

National risk preference, insurance development and exports-a study based on the world values survey

National risk preference, insurance development and exports-a study based on the world values survey

Melhoria da análise de seguro agrícola com dados de zoneamento agrícola

Abstract This article proposes a framework for integrating agricultural zoning data into insurance risk analysis. It is based on combining official public information from the Brazilian zoning program, ZARC, with open insurance data provided by the Brazilian Ministry of Agriculture and Livestock. The methodology presented in this article transforms ZARC information into distributional data and integrates it into a Bayesian model alongside insurance indemnities data, allowing for comprehensive risk analysis. It uses information on soil types from ZARC to develop basic best- and worst-case scenarios and calculate posterior distributions using insurance data. The resulting framework enables the comparison of municipalities, crop types, and overall risk classification. The study applies the framework to analyze the risk of soybeans, corn, wheat, and corn double-crop in Paraná State, resulting in consistent risk classifications across all crops and municipalities. The proposed framework has the potential to enhance agricultural risk management analysis for reinsurers, insurers, government agencies, and private companies. Future research could explore the use of this methodology to compare insurers, analyze risk in structured operations of credit and insurance, and evaluate risks at the farm level. This article presents a potential tool for improving risk analysis and decision-making in the agricultural sector.

Quantum internal models for Solvency II and quantitative risk management

Abstract This paper extends previous research on using quantum computers for risk management to a substantial, real-world challenge: constructing a quantum internal model for a medium-sized insurance company. Leveraging the author’s extensive experience as the former Head of Internal Model at a prominent UK insurer, we closely examine the practical bottlenecks in developing and maintaining quantum internal models. Our work seeks to determine whether a quadratic speedup, through quantum amplitude estimation can be realised for problems at an industrial scale. It also builds on previous work that explores the application of quantum computing to the problem of asset liability management in an actuarial context. Finally, we identify both the obstacles and the potential opportunities that emerge from applying quantum computing to the field of insurance risk management.

Insurability of cryptocurrency wallets

This article concerns the possibilities of insuring cryptocurrency wallets using various assumptions and characteristics of perfectly insurable risk. The main goal of this article is to examine if and how cryptocurrency wallets risk fulfils the requirements of an ideally insurable risk. The topic of the research is important looking at the newest trends in financial markets and the growing number of cryptocurrency investors. The paper presents authors’ innovative method of approaching a part of cryptocurrency risk to insurance industry. Authors analysed requirements of an insurable risk and applied these requirements to a specific risk, i.e. the cryptocurrency wallet risk to further check if it is possible to insure such a risk. By introducing and defining cryptocurrency wallet risk, we found an element of cryptocurrencies which shows traits of a non-speculative risk and possibly fulfils insurability characteristics.

STATE SUPPORT FOR THE DEVELOPMENT OF ALTERNATIVE ENERGY IN UKRAINE

The article provides a theoretical analysis of state support for the development of alternative energy in Ukraine at the current stage. A number of legislative initiatives aimed at supporting the alternative energy sector during martial law are analyzed, and several key directions demonstrating positive dynamics in this sector are highlighted. The necessity of introducing new mechanisms of state support for alternative energy is substantiated, including the transition from the «green tariff» to the feed-in premium mechanism and the implementation of a self-generation system for active consumers. Key directions of international cooperation are revealed, particularly through collaboration with transnational development banks and international financial organizations for risk insurance and project financing. Priority tasks of state regulation are identified, including stimulating investments, creating a transparent legislative framework, simplifying administrative procedures, and ensuring effective coordination between various levels of governance to integrate alternative energy sources into a unified national energy system.

Increasing Literacy of Sharia Disaster Insurance in Indonesia

Natural disaster losses need to be reduced in order to be recovered from. APBN/APBD has a budget for disaster management thanks to the efforts of the Indonesian government, as mandated by Law No. 24 of 2007The government must alter its natural disaster risk finance policies in order to meet the demands for large catastrophe funding that is prompt, targeted, more planned, sustainable, and transparent. Economic losses and the burden on the state budget will be lessened as a result. This funding must be able to satisfy the financial needs for emergency response and catastrophe recovery in addition to the financial requirements for disaster risk transfer and mitigation (rehabilitation and reconstruction). The individual risk insurer is the organization in charge of managing insurance. The agreement between the insured and the insurer is known as a policy in the context of insurance. The insurer agrees to assume a variety of potential future risks under the agreement in exchange for certain payments from the insured. The amounts that the insured pays to the insurer are known as premiums

MECHANISMS OF EXTERNAL FINANCING OF THE UKRAINIAN ECONOMY DURING WAR AND APPROACHES TO THEIR OPTIMIZATION

The article examines the approaches and mechanisms of financing the Ukrainian economy from EU countries during the full-scale aggression of the Russian Federation, which showed a significant limitation of allocated resources for a systemic confrontation with the Russian Federation and full European integration. It has been revealed that the financial resources allocated by Ukraine’s international partners (mainly the USA and the EU) are limited, which are only sufficient for exchange rate, financial and price stabilization, but not enough for economic recovery and development. The author of the article proposed to revise and increase the parameters of the existing largest financial assistance program «Ukraine Facility» for more tangible socio-economic support for Ukraine. The investment component of this program is also a very small amount for large-scale, strategic attraction of Western companies to cooperation and insurance of business risks. Only fundamentally, grant, technical and gratuitous financing with appropriate control mechanisms can change the trajectory of economic recovery of the Ukrainian economy. A number of measures (7 instruments of financial assistance) are proposed to improve the domestic socio-economic sphere and convincing arguments are provided for revising the political dialogue at the international level by the Ukrainian authorities. Active in transforming and improving the program «Ukraine Facility» The Government of Ukraine must show its commitment to European partners in accordance with strategic plans for the development of the domestic socio-economic environment.

Fusing multi-model climate risk assessment and insurance profitability prediction: a machine learning-based cross-country comparative analysis

Climate change-induced increases in the frequency and intensity of extreme weather events year after year pose a significant challenge to the profitability of the global insurance industry. Traditional risk assessment models have limitations in predicting insurance profitability due to the difficulty in coping with the nonlinearity and complexity of climate risk. To this end, this study proposes a multi-model fusion approach that combines fuzzy assessment models, entropy weighting, linear regression, and machine learning models (LightGBM & XGBoost) to assess the impact of climate risk on the profitability of the insurance industry. By analyzing cross-country empirical data from the U.S. and U.K. insurance markets, this study reveals the differences and challenges in coping with climate risk in different countries. The findings show that climate risk significantly affects the profitability of insurance companies and that machine learning models exhibit higher accuracy and reliability in risk prediction compared to traditional methods. This paper provides an empirical basis for insurers and policymakers to address the economic impacts of climate change and makes recommendations for optimizing insurance risk management.

The U.S. Model of Insuring Development Investments Against Political Risks: Tracking Transformative Changes

The paper tracks the trajectory of transformation in the U.S. model of insuring development investments against political risks. First it outlines a novel normative context for providing political risk insurance (PRI), which took shape in the United States in 2018. Then, it compares the numerical parameters of insurance activities by the U.S. International Development Finance Corporation (DFC) over FY 2020–2024 with those of its predecessor, the Overseas Private Investment Corporation (OPIC) in FY 2015–2019, analyzing and explaining the main changes in the scope and geographical priorities of PRI coverage. Finally, the paper unveils the substance of debates around the DFC’s reauthorization which have so far resulted in an increased securitization of development investment support, including political risk insurance.

Flood risk assessment through large-scale modeling under uncertainty

Abstract. The complexity of flood risk models is intrinsically linked to a variety of sources of uncertainty (hydrology, hydraulics, exposed assets, vulnerability, coping capacity, etc.) that affect the accuracy and reliability of the analyses. Estimating the uncertainties associated with the different components allows us to be more confident in the risk values on the ground, thus providing a more reliable assessment for investment, insurance and flood risk management purposes. In this study, we investigate the flood risk of the entire Central Apennines District (CAD) in Central Italy using the laRgE SCale inUndation modEl – Flood Risk (RESCUE-FR), focusing on the interaction between the uncertainty in the hydraulic Manning parameter and the risk variability. We assess the coherence between the quantile flood risk maps generated by our model and the official risk maps provided by the Central Apennines District Authority (CAD Authority) and focusing on three specific zones within the CAD region. Thus, RESCUE-FR is used to estimate the expected annual damage (EAD) and the expected annual population affected (EAPA) across the CAD region and to conduct a comprehensive uncertainty analysis. The latter provides a range of confidence of risk estimation that is essential for identifying vulnerable areas and guiding effective mitigation strategies.

A multi-period model for assessing the reinforcing dependence between climate transition and physical risks of non-life insurers

PurposeClimate risks are crucial for non-life insurers due to their significant exposure to both transition and physical risks. The aim of this study is to develop a multi-period model that represents climate risks in non-life insurance, encompassing the impacts of both physical and transition risks as well as their reinforcing dependence. Literature suggests that as physical climate risks increase, the urgency for climate policies intensifies, leading to higher climate transition risks.Design/methodology/approachOur model includes a stochastic transition process affecting assets based on their exposure in climate policy-relevant sectors (green and brown investments) and a dependence structure between this process and liabilities, where the physical risks manifest as an increase in claims.FindingsOur simulation indicates that the choice of the transition process, as well as the consideration of dependencies, has a significant influence on the insurers’ profit, but even more on the probability of ruin. The impact of green versus brown investment strategies varies considerably based on whether dependencies are taken into account or not.Originality/valueThe results of this study are intended to deepen the understanding of the effects of climate risks on non-life insurers and provide a quantitative analysis of the impact of green and brown investing within this framework.

Determining Driving Risk Factors from Near-Miss Events in Telematics Data Using Histogram-Based Gradient Boosting Regressors

This study introduces a novel method for driving risk assessment based on the analysis of near-miss events captured in telematics data. Near-miss events, which are highly correlated with accidents, are employed as proxies for accident prediction. This research employs histogram-based gradient boosting regressors (HGBRs) for the analysis of telematics data, with comparisons made across datasets from China and Spain. The results presented in this paper demonstrate that HGBR outperforms conventional generalized linear models, such as Poisson regression and negative binomial regression, in predicting driving risks. Furthermore, the findings suggest that near-miss events could serve as a substitute for traditional claims in calculating insurance premiums. It can be seen that the machine learning algorithm offers the prospect of more accurate risk assessments and insurance pricing.