Profitability Policy Research Articles

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.

Nexus of fraud mitigation practices and profitability of insurance companies in South Africa

The objective of this study was to evaluate how measures taken to prevent fraud impact the Profitability of insurance companies operating in South Africa. The study adopted a descriptive research approach and surveyed a sample of 70 licensed insurance companies in the country. Primary sources of data were obtained by engaging claims managers in each of the firms, and descriptive and inferential statistics were used to analyse the data. The results of the study revealed that fraud mitigation measures significantly affect the Profitability of insurance companies in South Africa. The implementation of fraud prevention, detection, and response measures had a positive impact on the Profitability of these firms. Based on the findings, the study recommends that the Insurance Regulatory Authority establish regulations that mandate all insurance providers to collect and report statistics on fraud. Insurance firms should provide their employees with comprehensive training on fraud management and implement strict penalties and disciplinary measures for employees involved in fraudulent activities, as they can undermine the effectiveness of the fraud mitigation process.

Dissecting Indonesian Insurance Profitability and Efficiency: Du Pont Diagnostic Tool.

This research compares the financial performance of insurance companies in Indonesia using the Du Pont method, identifies the determinants of differences in profitability and efficiency, and provides strategic recommendations. The methodology involves analyzing the 2023 audited financial statements of PT Asuransi Dayin Mitra Tbk and PT Asuransi Bintang Tbk as samples, applying the Du Pont method, financial ratios, and qualitative analysis. The results reveal a significant difference in profitability, with PT Asuransi Dayin Mitra Tbk excelling in net profit margin, asset turnover, and a conservative capital structure, while PT Asuransi Bintang Tbk outperforms in underwriting risk management, claims handling, and aggressive marketing strategies. Strategic recommendations include maintaining strengths, exploring revenue growth, enhancing cost efficiency, and adjusting capital structure. This research contributes to understanding the dynamics of financial performance in the Indonesian insurance industry.

Risk Management Strategies and Performance of Selected Insurance Companies in Nairobi City County, Kenya

The insurance industry plays a vital role in the management of risk and therefore helps to support and facilitate business activities. The performance of insurance companies is impacted by various challenges related to their risk management strategies. These challenges can arise from both internal and external factors, and they can have significant implications for the financial stability and profitability of insurance companies. Changes in regulatory requirements can impact the risk management strategies of insurance companies, requiring them to adapt their practices and systems to remain compliant. Therefore, this study seeks to investigate the influence of risk management strategies on the performance of selected insurance companies in Nairobi City County, Kenya. The study was guided by the balanced scorecard model, agency theory, portfolio theory, risk aversion theory, and prospect theory. A descriptive research design was employed. The study targeted 95 respondents, comprising 10 senior-level managers, 30 middle-level managers, and 55 departmental heads from the insurance companies operating in Kenya. A census of 95 respondents was conducted. The study used a structured questionnaire. A pilot group of 9 individuals was selected from the target population. Content validity was applied to the study. Cronbach’s Alpha coefficient was computed for all components of the questionnaire, and their assessment was provided. Descriptive analysis was computed using mean, frequencies, and percentages. Regression analysis tested the relationship between the study variables. The regression model assessed the relationship between the independent variables and the dependent variable. The findings were presented using tables and figures. Through regression analysis with a linear model result showed a strong relationship between risk management strategies and performance. The resulting value of regression coefficient at .000 (p<0.05) indicated existence of relationships that were relatively strong. The study thus concluded that performance of insurance companies is dependent on the careful choice or selection of risk management strategies. It is expected the results will benefit various stakeholders, including the government policy makers, Insurance sector players, and academia. Further studies exploring more strategies to manage risks in other entities including other sectors such as the finance sector could be undertaken by scholars.

The Expected Impact of Applying the Insurance Contracts Standard (IFRS 17) in the Solvency and Profitability of Insurance Companies listed on the Amman Stock Exchange

This study aimed to identify the expected impact of applying International Financial Reporting Standard No. 17 on the solvency and profitability of the insurance companies listed on the Amman Stock Exchange. The descriptive analytical approach was used to achieve the study's aim. The study used the questionnaire as a tool, where the study population consisted of all insurance companies listed on the Amman Stock Exchange. In contrast, the study sample included heads of accounts departments and actuaries working in insurance companies and accountants, and 33 questionnaires were distributed to insurance companies. One of the most important findings of this study was that there is a relationship between the independent variable (application of IFRS No. 17) and the dependent variable (solvency) in the insurance companies listed on the Amman Stock Exchange. And that there is a relationship between the independent variable (application of International Financial Reporting Standard No. 17) and the dependent variable (profitability) in the financial and service insurance companies listed on the Amman Stock Exchange. One of the most important recommendations of the study is the need for insurance companies to be keen to provide employees with ongoing experimental courses to remove the ambiguity surrounding some of the provisions of International Financial Reporting Standard No. 17.

Exploration of Property Insurance Benefits in Extreme Weather

In recent years, the increasing frequency of extreme weather events has highlighted the insurance industry's dilemma - the profitability of insurance companies and the capacity of policyholders to bear the burden are in crisis. Therefore, seeking the development of property insurance in this environment is crucial. This paper establishes a Risk Assessment Model with a four-level index system, including four main indicators: natural, economic, social, and engineering defense, to assess the disaster risk and losses of a specific area. Subsequently, a Rate-Adjusted Break-Even Analysis Model is established and coupled with the Risk Assessment Model to facilitate practical insurance decision-making. By establishing this highly flexible and practical assessment system, precise indicators can be selected for evaluation based on the varying impacts of natural disasters in different regions. This will enable more accurate decision-making for local catastrophic insurance coverage. Consequently, it allows local residents to obtain better post-disaster relief protection against natural calamities, while businesses can also benefit from substantial reconstruction returns.

Research on Underwriting Decision-Making of Insurance Companies in Areas with Frequent Extreme Weather Based on Comprehensive Evaluation Method

The purpose of this research is to develop an insurance company underwriting model by pre-processing and model construction of collected data in order to assess whether to underwrite insurance in extreme weather-prone areas and to analyse the factors that influence underwriting decisions. In this paper, data such as insurance company payout rate, number of insured, homeowners' income in selected areas, health insurance coverage, year of construction of historical landmarks, GDP per capita, and tourism income were processed, and minimum-maximum normalisation and zero-mean normalisation were used to eliminate differences in feature magnitude. In the model construction, the logistic regression model and BP neural network were used to derive the underwriting probability, and the three main factors of natural disaster risk assessment, payout rate, and homeowner influence were introduced, and the relationship between these factors and the underwriting probability was described by the logistic distribution function, which determined that the underwriting probability should be underwritten when the underwriting probability Pi≥0.5. The natural disaster risk assessment model selects disaster factors, disaster environment and disaster receptors as assessment indicators, constructs the CEDP model, and calculates the weights using the AHP model, the Topsis model and the CPITIC weighting method, and carries out fuzzy clustering analysis on the CEDP index of 25 regions to classify the risk into five levels. For insurer profits, solvency, premium income and claims ratios were analysed, ratios based on annual claims to total premiums were calculated, and the impact of homeowners' incomes, property and historic buildings on underwriting decisions was assessed. Insurance company underwriting decision factors in areas prone to extreme weather are ultimately determined.

IMPACT OF CAPITAL STRUCTURE ON PROFITABILITY OF VIETNAMESE INSURANCE COMPANIES

Insurance companies have an important function of absorbing and storing economic risks. Therefore, companies need to have optimal, safe, and stable capital sources to be able to finance, diversify, and transfer risks. Previous studies have only focused on market share, customers, competitive strategies, and insurance premiums without paying attention to the capital sources of insurance companies. This is more necessary when Vietnamese insurance companies have a non-optimal capital structure, leading to low profitability. The study aims to fill the above gap by analyzing the impact of capital structure on the profitability of insurance companies through the research sample of the Data Set of 40 insurance companies (listed on HNX, HOSE, UPCOM), corresponding to 297 observations in the period from 2013 - 2023. By using GMM estimation, the author has identified three independent variables explaining (and two control variables) the variation of the dependent variable profitability (ROE), including (i) General debt ratio (GDR), (ii) Debt ratio (DR), (iii) Long-term debt ratio (LDR). Based on the research results, the authors discuss and assess the important role of capital structure in insurance companies and provide financial solution recommendations to improve their profitability.

Reinforcement learning-based portfolio optimization with deterministic state transition

Portfolio optimization has attracted substantial interest within the artificial intelligence community due to its significant impact on financial decision-making, risk management, and market analysis. Reinforcement learning fits well with portfolio optimization because their goal is to maximize cumulative returns. In reinforcement learning, state transition probabilities are often unknown and must be estimated. However, in portfolio backtesting experiments, these probabilities are deterministic, making the conventional reinforcement learning approach to estimating state transitions suboptimal for portfolio optimization. Addressing this issue, this study decomposes the portfolio optimization into two core tasks: prediction and profit policy optimization and proposes a novel reinforcement learning framework that assumes deterministic state transition probabilities, comprised of three main modules: feature extraction, prediction, and profit strategy optimization. To model assets more effectively and comprehensively, we capture their temporal features, relational features, and market state. We introduce a patch-wise correlation method and attribute based gate to enhance feature extraction. In the profit policy module, we utilize a deterministic strategy, employing a recursive reinforcement learning method based on Monte Carlo sampling to train the policy network. This enables dynamic adjustments of asset investment weights, ensuring the maximization of cumulative returns. Extensive experiments conducted on cryptocurrency datasets demonstrate the superior performance of our approach, and achieving 36.6%-75.6% improvements in main measurements on cryptocurrency datasets.

Pricing models for small and micro loan portfolio insurance

From the perspective of the insurance deductible, this article constructs pricing models suitable for small and micro loan portfolio insurance under realistic conditions, and summarizes relevant pricing laws through examples. It is found that the option attribute of loan portfolio insurance contracts endowed by absolute or relative deductible clause can be used to price small and micro loan portfolio insurance. Meanwhile, owing to the offset effect of the loan portfolio on the credit risk of different single loans, the premium rate of loan portfolio insurance should be controlled between that of corresponding single loan insurance. Moreover, properly adjusting the deductible ratio, insurance period, and composition of the insured loan portfolio can create more space for reducing the insurance price of the loan portfolio or expanding insurance profits. Our study improves the pricing model system of small and micro loan insurance, which has important theoretical value and practical significance for the scientific pricing of loan portfolio insurance.

Pengaruh Kebijakan Hutang Dan Profitabilitas Terhadap Nilai Perusahaan Pada Perusahaan Makanan Dan Minuman Yang Terdaftar Di Bursa Efek Indonesia

This study aims to examine the effect of debt and profitability policies on company value in food and beverage companies listed on the Indonesia Stock Exchange (IDX) for the 2020-2022 period. The sampling technique uses the purposive sampling method. The total research sample is 81 companies with 3 years of research. This research is a quantitative research. The type of data carried out in this study is secondary data, which is in the form of financial statements and annual reports of food and beverage companies. The analysis method used is multiple linear regression using SPSS version 26 software. Data testing was carried out using descriptive statistical analysis, classical assumption test, multiple regression analysis test, determination coefficient and t-test. Meanwhile, profitability has a significant effect on the company's value

The Impacts of Political Unrest, Firm Specific and Macroeconomic Factors on the Financial Performance of Insurance Industry in Ethiopia during Youth-Led Mass Anti-Government Protests (2014-2022)

This study investigates the impacts of political unrest; firm-specific and macroeconomic factors on the financial performance of the insurance industry in Ethiopia during youth-led mass anti-government protests. The study used, Return on Assets (ROA) and Return on Equity (ROE) as dependent variables. Eight key independent (internal and external) variables are also used. The study selected 17 out of 18 due to the availability of data for the period ranging from 2014 to 2022. The descriptive and multiple regression analyses were done. The results of the study indicate that political violence and terrorism (PV&T) have a negative and significant effect on ROA and ROE, while GDP has a positive and significant effect on ROA and ROE. The findings also show that financial risk (FR) has a negative and significant effect on ROA and ROE but a positive and significant effect on ROA and ROE. Furthermore, the study reveals that the size of company (SZ) and premium growth (PG) have a significant and positive impact on ROA but insignificant effect on ROE as well as liquidity (LQ) and asset tangibility (ATG) have a significant negative effect on ROE but insignificant effect on ROA. The inflation rate (INF) has no effect for both models on Ethiopian insurance financial performance. This study is considered one of the first pioneering studies that determined the factors affecting the financial performance of insurance companies in Ethiopia. Therefore, the study gives good insights to policymakers, regulators, and interested parties about enhancing the profitability of insurance companies in Ethiopia. Keyword: - political unrest, firm specific factor, macroeconomic factor, financial performance, insurance industry, Ethiopia JEL Classification G22 G32 F50

A Study on Maximizing Insurance Company Profits under Extreme Weather Events Based on an Optimization Model

A Study on Maximizing Insurance Company Profits under Extreme Weather Events Based on an Optimization Model

The Effect of Financial Performance on the Profitability of General Insurance Companies Listed on the Indonesia Stock Exchange (IDX) for the Period 2016-2022

This research aims to examine the influence of financial performance on the profitability of general insurance listed on The Indonesia Stock Exchange (IDX) for the Period 2016-2022. The approach used in this research is a quantitative approach. The sample used in this research is insurance companies listed on The Indonesia Stock Exchange (IDX) namely a total of 14 general insurance companies in 2022, totaling 14 companies. Research data is secondary data obtained from company financial reports. Research data was analyzed using Panel Regression analysis techniques with the help of the Eviews program. The results of this research show that liquidity and premium growth has no significant effect on ROA, self-retention and RBC has a positive effect on ROA.

Intellectual capital and firm performance of Jordanian financial institutions

This study aims to explore the financial implications of intellectual capital in the Jordanian financial sector during the period 2009–2018. It uses Pulic’s (2004) value-added intellectual capital model, particularly capital employed efficiency, structural capital efficiency, and human capital efficiency, and tests its potential effect on firm financial performance measures, including return on assets, return on equity, asset utilization ratio, and Tobin’s Q. The study’s findings demonstrate that value-added intellectual capital positively influences the financial performance of Jordanian financial companies. Value-added intellectual capital is not found to have a significant impact on productivity, but it is strongly and positively related to firm profitability and market value. As for the main components of value-added intellectual capital, human capital efficiency has a significantly positive impact on a company’s performance, but regarding structural capital efficiency, the outcomes vary depending on the measure of firm performance. Notably, when firms are categorized into sub-industries (banks, insurance companies, and financial service companies), it is found that the profitability of insurance companies is more affected by intellectual capital than that of banks or financial services. The results also show that investors place great importance on the efficiency of intellectual capital, particularly within the banking industry. Furthermore, implementing Shariah compliance standards boosts the positive effect of structural capital efficiency on corporate market value and reinforces the positive influence of human capital efficiency on productivity.

Utility Function's Influence on Insurance Policy Customer Choices

This research examines the influence of utility functions on consumer decisions regarding insurance plans, emphasizing the importance of expected utility theory in making choices amidst uncertainty. Originated by Daniel Bernoulli, this concept plays a crucial role in contemporary economics by guiding individuals towards options that maximize their anticipated satisfaction. Through an examination of deductible options—percentage and straight—this study demonstrates how these decisions impact both the profitability of insurers and the behavior of customers. Utilizing a literature review methodology, the research scrutinizes previous studies to clarify the relationship between utility theory and insurance choices. The results highlight that utility functions offer a numerical structure for assessing personal preferences and tolerance for risk, assisting in the creation of policies that harmonize customer requirements with insurer goals. This holistic approach to comprehending insurance decisions underscores the pivotal function of utility theory in economic evaluations, providing valuable insights into the financial security and welfare of individuals in an unpredictable environment.

The Impacts Of Political Unrest, Firm Specific And Macroeconomic Factors On The Financial Performance Of Insurance Industry In Ethiopia During Youth-Led Mass Anti-Government Protests (2014-2022)

This study investigates the impacts of political unrest; firm-specific and macroeconomic factors on the financial performance of the insurance industry in Ethiopia during youth-led mass anti-government protests. The study used, Return on Assets (ROA) and Return on Equity (ROE) as dependent variables. Eight key independent (internal and external) variables are also used. The study selected 17 out of 18 due to the availability of data for the period ranging from 2014 to 2022. The descriptive and multiple regression analyses were done. The results of the study indicate that political violence and terrorism (PV&T) have a negative and significant effect on ROA and ROE, while GDP has a positive and significant effect on ROA and ROE. The findings also show that financial risk (FR) has a negative and significant effect on ROA and ROE but a positive and significant effect on ROA and ROE. Furthermore, the study reveals that the size of company (SZ) and premium growth (PG) have a significant and positive impact on ROA but insignificant effect on ROE as well as liquidity (LQ) and asset tangibility (ATG) have a significant negative effect on ROE but insignificant effect on ROA. The inflation rate (INF) has no effect for both models on Ethiopian insurance financial performance. This study is considered one of the first pioneering studies that determined the factors affecting the financial performance of insurance companies in Ethiopia. Therefore, the study gives good insights to policymakers, regulators, and interested parties about enhancing the profitability of insurance companies in Ethiopia.

Supply chain/transaction cost insights into the profitability of health insurers during 2020, the start of COVID‐19

AbstractVarious US populations make up different health care markets/segments, and health insurers specialize in serving specific populations. US health insurers soared in profits during 2020, the first year of the Covid‐19 pandemic. The profit gains were unequal among segments. This research uses a supply chain/transaction costs economics (SC/TCE) model to find insights into the profitability differences. The SC/TCE model consists of three spheres of profitability determinants: health care characteristics, transactions costs differentials, and governance methods. Our univariate analyses combined with weighted regression results reveal that, for Medicaid, a significant increase in profitability was associated with a decrease in medical expenses, whereas the opposite is observed for the group and Medicare Advantage plans. Another finding is that transaction costs differentials led to significant increases in profitability for group and Medicare plans with opposite results for Medicaid plans. These results provide important practical implications for policymakers.

Based on Symmetric Jump Risk Market: Study on the Ruin Problem of a Risk Model with Liquid Reserves and Proportional Investment

In order to deal with complex risk scenarios involving claims, uncertainty, and investments, we consider the ruin problems in a compound Poisson risk model with liquid reserves and proportional investments and study the expected discounted penalty function under threshold dividend strategies. Firstly, the integral differential equation of the expected discounted penalty function is derived. Secondly, since the closed-form solution of the equation cannot be obtained, a sinc method is used to obtain the numerical approximation solution of the equation. Finally, the feasibility and superiority of the sinc method are illustrated by error analysis. In addition, based on a symmetric jump risk market, we discuss the influence of some parameters on the ruin probability with some examples. This study can help actuaries develop more robust risk management strategies and ensure the long-term stability and profitability of insurance companies. It provides a theoretical basis for actuaries to carry out risk management.

Development of the best investment strategy for insurance companies based on ARIMA-SVM

The purpose of this article is to develop the best investment strategy for insurance companies in the context of extreme weather, aiming to improve the profitability of insurance companies and reduce investment risks. This research focuses on Asia and North America, and constructs an ARIMA model to accurately predict the frequency of extreme weather in the next decade. At the same time, a comprehensive evaluation model was constructed by combining the entropy weight method to quantitatively evaluate the payment ability of local residents. On this basis, the SVM classification model was established to predict whether the insurance company should be insured in a certain place, and the performance of the model was deeply analyzed, and the recall rate and accuracy of the classification model were 0.93 and 0.94, respectively, indicating that the model had good reliability. After a series of rigorous model analysis and data validation, it was finally concluded that China in Asia is the best choice for insurance companies. This strategy not only helps insurers optimize resource allocation, but also achieves stable and sustainable development in the context of complex and volatile extreme weather.