Egyptian Insurance Research Articles

Factors Influencing Solvency Margin of the Egyptian Insurance Companies

Factors Influencing Solvency Margin of the Egyptian Insurance Companies

Enhancing operational efficiency of insurance companies: a fuzzy time series approach to loss ratio forecasting in the Egyptian market

ABSTRACT This article analyses the crucial significance of loss ratio (LR) evaluation in assessing the operational efficiency of insurance companies. Fuzzy time series (FTS) models are effective in modelling non-linear with uncertainties and providing adequate performance with limited data availability, which overcomes the shortage of conventional models used in Egyptian insurance market literature. This paper aims to introduce a comprehensive analysis of LR of the property and casualty sectors. Moreover, review and compare various forecasting FTS techniques to discuss the effectiveness of using FTS methods in forecasting LR. The suggested method is based on results from tests done with four models that had Huarng 465 partitions and interval length parts of 5, 10, 50, and 100. The results show LR prediction improved significantly. Yu and Cheng’s models using a Huarng 465 partition for training data and the Yu model with 100 partitions for testing data had high accuracy and low error.

A Novel Hybrid ANFIS-NARX and NARX- ANN models to Predict the profitability of Egyptian Insurance Companies

The use of fuzzy logic models with machine learning (ML) models have become common in many areas, especially insurance field. This study aims to compare between non-hybrid models such as artificial neural network (ANN) model, adaptive neural fuzzy inference system (ANFIS) model, nonlinear auto-regressive external input (NARX) model, and the following hybrid models (ANFIS-NARX) and (NARX-ANN) to predict the profits of the insurance activity which represent the important indicator of the good performance of Egypt's 39 insurance companies in the period from 1st January 2009 to 31 December 2022 , monthly .This prediction based on the following factors (net premiums, reinsurance commissions, net income from earmarked investments, other direct income, net compensation, production cost commissions and general and administrative expenses) that help decision makers to make appropriate decisions . The results found that the (ANN) model is given good results compared with the following models (ANFIS), (NARX), hybrid (ANFIS-NARX) and (NARX-ANN) models according to the following prediction accuracy measures (RMSE, MAPE, MAE and Theil inequality). The explanatory ability (R2) was appeared (0.79, 0.61) respectively for training and testing phases in persons insurance companies. The explanatory ability also was appeared (0.83, 0.68) respectively in property insurance companies.

The main determinants of the absorptive capacity of the Egyptian insurance market using statistical analysis

This research aims to use a statistical and economic model that takes into account all the emerging economic, social and financial variables in the framework of the new world order and the new general situation to determine the most important basic determinants affecting the volume of demand and the supply of insurance policies for each branch of insurance separately. To maximize its financial, economic and social return, that is, to determine the factors affecting the absorptive capacity of the Egyptian insurance market using some statistical models. It was found that the best regression models that can be used to describe the relationship between the number of insurance policies and the economic variables used in the study is the semi-logarithmic model, and the size of insurance amounts is related to a group of economic variables at the national level, including: population - size of the labor force - birth rates, and it is also related to per capita GDP.

Investment Return of Egyptian Insurance Firms Under Political Risks

Investment Return of Egyptian Insurance Firms Under Political Risks

Does bancassurance influence the financial performance of the insurance industry? A case study of life insurance company in a developing country

Purpose This study aims to examine the impacts of bancassurance contracts on the financial performance of the Egyptian insurance market from 2011 to 2022. Design/methodology/approach To achieve this main objective, a mixed methodological approach was adopted: a quantitative methodological approach through analyzing the content of Misr Life Insurance (MLI) Firm’s annual reports from 2011 to 2022. This period frame includes three crucial eras in the history of Egypt: the period covered by the two revolutions in Egypt, the period of political and economic stability and the COVID-19 period. Furthermore, a paired sample test was conducted for two related samples to examine the differences between the averages of financial indicators of MLI Firm for the period prior to and after the bancassurance. Additionally, a qualitative case study approach was adopted, focusing on the MLI Firm in Egypt. To support and confirm the results from quantitative content analysis, an interview was conducted with a financial manager from MLI Company. Findings Generally, the analysis reveals that the financial performance indicators of MLI are significantly influenced by bancassurance because of the variations between the financial performance of MLI Company before and after bancassurance, as the company’s financial performance rose after the bancassurance experience. Therefore, the current research suggests promoting awareness of bancassurance contracts in Egypt to boost financial performance and economic development through bulletins. Research limitations/implications The research has limitations because of its mixed methodological approach, focusing on annual reports, the Egyptian life insurance environment and the insurance sector. Practical implications The findings of this research are probably going to be helpful in clarifying the state of bancassurance in the Egyptian insurance industry for a wide range of interested parties, including managers, investors and scholars. More specifically, this research provides insights into MLI’s financial performance from 2011 to 2022. It aids investors in making informed decisions, boosts shareholder trust and encourages new business in the Egyptian insurance industry. Originality/value This research strives to establish a novel field of study, as there are few studies in developing countries that introduce empirical evidence on the impact of bancassurance on the financial performance of insurance firms in Egypt.

Integration of Financial and ESG Performance Indicators to Measure and Evaluate Egyptian Insurance Companies Performance

This study aims to evaluate the performance of Egyptian insurance companies through the integration of financial and non-financial performance indicators through the dimensions of sustainable development as a mediator variable. The study relied on Allianz Egypt property and liability insurance company data from 2012 to 2021, and the Monte Carlo simulation method was used based on the Mathcad program. This study used structural Equations Modeling via AMOS program to extract the direct and indirect effect through path analysis. The results showed that each environmental dimension, social dimension, and governance dimension plays a mediator role in the relationship between solvency, liquidity, credit, activity, underwriting profitability, and both market share and investment profitability. Our research contributes to the literature of achieving sustainable development in the insurance sector, to keep pace with global developments. This paper presents evidence of the relationship between integrating ESG indicators into insurance companies’ performance and achieving an additional competitive advantage.

Precision in Insurance Forecasting: Enhancing Potential with Ensemble and Combination Models based on the Adaptive Neuro-Fuzzy Inference System in the Egyptian Insurance Industry

ABSTRACT Enhancing the precision of retention ratio predictions holds profound significance for insurance industry decision-makers and those vested in advancing insurance services. Precision helps insurance companies navigate inflationary pressures and evaluate underwriting profitability, enabling reliable prognoses of future underwriting gains. As far as we know, although there have been multiple attempts to construct a predictive model for retention ratio, none of these attempts have used combining models or studied the Egyptian market. Therefore, this study contributes significantly to this developing field by providing combining models, which combined statistical time series models such as Exponential Smoothing (ES), and Autoregressive Integrated Moving Average (ARIMA), with Adaptive Neuro-Fuzzy Inference System (ANFIS). Two different types of combinations are employed with these models. Furthermore, the study introduces three ensemble models designed for the purpose of predicting the retention ratio within the Egyptian insurance market. Dataset was carefully gathered from the EFSA’s annual reports, focused on the property-liability insurance sector within the Egyptian insurance market and covers the time period from 1989 to 2021. Next, the proposed models are assessed employing well-established statistical assessment metrics, namely, Mean Absolute Error (MAE), Mean Absolute Percent Error (MAPE), R Square (R2), and Root Mean Square Error (RMSE). The results show that combining and ensemble methods improve predicted accuracy. A multi-linear regression-based ensemble model that combines ARIMA, ES, and ANFIS models outperforms both single and combined models in robustness. The article concludes that the insurance industry can greatly benefit from modern predictive methods to make sound decisions.

Towards an institutional understanding of risk-based management controls: evidence from a developing market

PurposeIn developing countries, how risk management technologies influence management accounting and control (MAC) practices is under-researched. By drawing on insights from institutional studies, this study aims to examine the multiple institutional pressures surrounding an entity and influencing its risk-based management control (RBC) system – that is, how RBC appears in an emerging market attributed to institutional multiplicity.Design/methodology/approachThe authors used qualitative case study research methods to collect empirical evidence from a privately owned Egyptian insurance company.FindingsThe authors observed that in the transformation to risk-based controls, especially in socio-political settings such as Egypt, changes in MAC systems were consistent with the shifts in the institutional context. Along with changes in the institutional environment, the case company sought to configure its MAC system to be more risk-based to achieve its strategic goals effectively and maintain its sustainability.Originality/valueThis research provides a fuller view of risk-based management controls based on the social, professional and political perspectives central to the examined institutional environment. Moreover, unlike early studies that reported resistance to RBC, this case reveals the institutional dynamics contributing to the successful implementation of RBC in an emerging market.

Exploring the Linkages between Insurance Receivables and Economic Development: Evidence from Egyptian Insurance Sector

Exploring the Linkages between Insurance Receivables and Economic Development: Evidence from Egyptian Insurance Sector

Evaluating the Use of Artificial Intelligence in Egyptian Insurance Companies

Evaluating the Use of Artificial Intelligence in Egyptian Insurance Companies

Impact of Reinsurance Agreements on Assets and Liabilities Management of Property and Casualty Insurance Companies Applied in the Egyptian Insurance Market

Impact of Reinsurance Agreements on Assets and Liabilities Management of Property and Casualty Insurance Companies Applied in the Egyptian Insurance Market

Post Pandemic strategy to the Egyptian Insurance market - A Statistical Approach –

Post Pandemic strategy to the Egyptian Insurance market - A Statistical Approach –

Predicting Insolvency of Insurance Companies in Egyptian Market Using Bagging and Boosting Ensemble Techniques

Insolvency is a crucial problem for several insurance companies that suffer from it. This problem has direct or indirect effects on both the people working in the financial business and normal citizens. Thus, in insurance companies, the ability to predict insolvency is in great demand. There are several efforts proposed to predict insurance company insolvency using computer science methods (e.g., support vector machine and fuzzy systems). Each country has its own data patterns due to interior matters. Thus, insurance companies from different countries may have different data patterns. Consequently, the utilized predictive model should adapt to the dataset at hand. To our best knowledge, despite there are several efforts to build an insolvency predictive model, none of these efforts explored the Egyptian market. In addition, even the existing efforts did not utilize the ensemble learning methods in the insolvency prediction problem. In this context, we have two main contributions to this work. First, we proposed the first public access dataset of Egyptian insurance companies. The collected dataset was gathered from 11 Egyptian insurance companies during the years 1999 to 2019. The dataset consists of a set of 22 ratios (21 input features and one output feature), e.g., retention and investment yield alongside the solvency ration (i.e., the target feature). In the second contribution, we proposed exploring the performance of the ensemble learning methods to address the insolvency prediction problem. Thus, we proposed building several insolvency predictive models using ensemble learning and classic machine learning models. Next, the proposed models are evaluated on different accuracy metrics, e.g., Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The experimental results revealed that the ensemble learning-based models outperformed the classic machine learning-based models. Moreover, the correlation analysis between the utilized 22 financial ratios revealed that the most significant ratios, for the task of predicting the solvency ratio, are the technical provisions to shareholders’ funds, insurance companies’ debit balances to shareholders, and earnings after taxes to shareholders’ funds.

Separating life and health from property/casualty insurance operations: an assessment of solvency in the Egyptian insurance market

In this article, we evaluate the effect of a recent change in regulation of insurers operating in the Egyptian insurance market that required all insurance companies to separate their life and health (L&H) and property/casualty (P/C) activities. We examine,specifically, the effect on the solvency of P/C insurers when they are required to form two completely separate companies for their operations (i.e., divest of their L&H business). Separating into separate entities may increase the transparency of the insurer’s operations, especially with respect to how they allocate capital across the company. Using financial data for all insurers in the Egyptian market for the period 2006–2015, we test whether solvency—captured via 13 solvency surveillance ratios—is affected by the decree. For robustness, we run the analysis for the whole market and for private companies only, focusing on P/C insurers only before and after the decree. Our findings indicate that the likelihood of insolvency, based on our evaluation of solvency ratios, increased after the decree.

Robust SURE estimates of profitability in the Egyptian insurance market

This paper proposes three robust estimators (M-estimation, S-estimation, and MM-estimation) for handling the problem of outlier values in seemingly unrelated regression equations (SURE) models. The SURE model is one of regression multivariate cases, which have especially assumption, i.e., correlation between errors on the multivariate linear models; by considering multiple regression equations that are linked by contemporaneously correlated disturbances. Moreover, the effects of outliers may permeate through the system of equations; the primary aim of SURE which is to achieve efficiency in estimation, but this is questionable. The goal of robust regression is to develop methods that are resistant to the possibility that one or several unknown outliers may occur anywhere in the data. In this paper, we study and compare the performance of robust estimations with the traditional non-robust (ordinary least squares and Zellner) estimations based on a real dataset of the Egyptian insurance market during the financial year from 1999 to 2018. In our study, we selected the three most important insurance companies in Egypt operating in the same field of insurance activity (personal and property insurance). The effect of some important indicators (exogenous variables) issued by insurance corporations on the net profit has been studied. The results showed that robust estimators greatly improved the efficiency of the SURE estimation, and the best robust estimation is MM-estimation. Moreover, the selected exogenous variables in our study have a significant effect on the net profit in the Egyptian insurance market.

The Biopolitics of Transformation to ERM Technologies

How risk management technologies are implemented in developing countries is largely under-researched. Using a perspective on bio-politics, this paper dissects how an infusion of risk management technologies permeates as a powerful managerial tool in governing subordinates. The notions of power/knowledge relations, disciplinary power, and governmentality enabled the authors to rehearse the Foucault's biopolitics perspective in an analysis of risk-based rationalities and risk management technologies. Qualitative case study research methods guided them to gather empirical evidence from a privately owned, Egyptian insurance firm. They found that risk management technologies are conjoined with institutional and discursive ramifications in a developing country where burgeoning neoliberal economic remedies are being diffused and adopted. Further, risk management technologies go hand in hand with this ensuing neoliberal agenda, making it inescapable for organisational managers in such a developing country to adopt these technologies for their survival and sustainability.

Sources Allocation on Risk Performance of Egyptian Insurance Companies

The main objective of current paper was to investigate the relationship between sources allocations measured by (external sources to total assets- free investment and allocated investment to total assets) on risk performance measured by financial risk (standard deviation of return on equity) business risk (standard deviation of return on assets) using ARDL and GARCH model, using a sample of 19 Egyptian insurance companies over a 21 year period form 1999 – 2019, the findings indicate that There is a significant negative linear relationships between the independent variable in terms of capital structure and assets structure on dependent variable standard deviation of return on equity (Y1) at a Significant level less than (0.05). Also there is a significant positive linear relationship between the independent variable in terms of assets structure and dependent variable standard deviation of return on assets (Y2) at a significant level less than (0.001). with regard to ARCH and GARCH result shows the There is a significant positive effect of the ARCH term, measured as the lag of the squared residual from the mean equation, and the GARCH term, Last period’s forecast variance, at a significant level less than (0.05). It means that the high volatility in the conditional variance of standard deviation of return on assets y2. also The sum of the two parameters of: (α+β) in the GARCH model (1, 1) whether the random error are distributed according to normal distribution approaches the positive one, which indicates that the two conditions of non-negative variance, and the variance is not inflated are satisfied, and that Indication of the continuity of volatility shocks in the standard deviation of return on assets (Y2).

The Impact of the Financial Performance on Capital Structure of Insurance Industry in Egypt

This paper attempts to investigate the impact of the profitability and liquidity on capital structure of insurance industry in Egypt as applied on a sample of (19) insurance firms represented in the Egyptian insurance industry over the period from 1999-2019. The capital structure is measured by debt ratio, and the financial performance is measured by (liquidity, return on equity, and retune on investment).The study results show that there are significant negative linear relationships between the independent variable in terms of return on equity (X1), return on investment (X3), and dependent variable for the capital structure (Y) at the level of significant less than (0.001); based on panel data analysis, the results show that Tau-statistic, and z-statistic, are at a significant level less than (0.05).The statistical conclusion is the null significant relationship between the capital structure and liquidity, while there is a significant relationship between the capital structure, return on equity, and return on investment. The results  also show that the R2 for the independent variables are accepted in the model (capital structure Y, lag Y1, return on equity X1, liquidity X2, and return on investment) by (79.3%) from total variation of capital structure (Y).

The usage of logistic regression and artificial neural networks for evaluation and predicting property-liability insurers' solvency in Egypt

<abstract> <p>Unlike prior solvency prediction studies conducted in Egypt, this study aims to set up a real picture of companies' financial performance in the Egyptian insurance market. Therefore, 11 financial ratios commonly used by NAIC, AM BEST Company, and S & P Global Ratings were calculated for all property-liability insurance companies in Egypt from 2010 to 2020. They have been used to measure those companies' financial performance efficiency levels by comparing these ratios with the international standard limits. The financial analysis results for those companies revealed that property-liability insurers in Egypt do not have the same level of financial performance efficiency where those companies are classified into three groups: excellent, good, and poor. Furthermore, this paper investigates using the stepwise logistic regression model to determine the most factors among these selected financial ratios that influence those companies' financial performance. The results suggest that only three ratios were statistically significant predictors: "Risk retention rate", "Insurance account receivable to total assets", and "Net profit after tax to total assets". Finally, this paper presents the multi-layers artificial neural network with a backpropagation algorithm as a new solvency prediction model with perfect classifying accuracy of 100%. The trained ANN could predict the next fiscal year with a prediction accuracy of 91.67%, and this percent is a good and favorable result comparing to other solvency prediction models used in Egypt.</p> </abstract>