Imam Muhammad Ibn Saud Islamic University | Saudi Arabia
Dr. Eslam Abdelhakim Kamel Seyam is an accomplished academic and researcher in the fields of insurance, risk management, and actuarial science. He currently serves as an Assistant Professor at the Depa rtment of Insurance and Risk Management, College of Business, Imam Mohammad Ibn Saud Islamic University, Saudi Arabia. With a rich background in teaching, research, and institutional development, Dr. Seyam has contributed significantly to academia through innovative curriculum design, quality assurance processes, and applied research. His work integrates mathematical rigor, statistical modeling, and data analytics to address contemporary challenges in the insurance sector, bridging theoretical foundations with practical solutions.
Education
Dr. Seyam’s academic foundation is deeply rooted in commerce, statistics, and insurance. He earned his Bachelor’s degree in Commerce with a specialization in Statistics and Insurance, followed by a Master’s degree in Insurance focusing on corporate governance and its impact on asset and liability management in insurance companies. His doctoral studies in Insurance were part of a joint program between Zagazig University, Egypt, and Michigan State University, USA, allowing him to collaborate with esteemed professors and engage in international research environments. This educational trajectory provided him with expertise in mathematical modeling, statistical analysis, actuarial methods, and insurance economics.
Experience
Dr. Seyam’s career spans progressive academic positions, beginning as a Demonstrator and Teaching Assistant in the Mathematics, Statistics, and Insurance Department at Zagazig University. He advanced to Assistant Professor, contributing extensively to teaching undergraduate and postgraduate courses in financial mathematics, risk management, actuarial statistics, applied statistics, and reinsurance. His responsibilities extended beyond teaching, as he played key roles in performance evaluation, quality assessment, and accreditation processes. He developed innovative systems for managing academic accreditation, designed technical support frameworks, and authored institutional guidelines to streamline accreditation activities. His teaching experience covers multiple universities, including Zagazig University, Zagazig National University, Suez Canal University, the Higher Technological Institute, and Imam Mohammad Ibn Saud Islamic University.
Research Interests
Dr. Seyam’s research interests encompass a broad spectrum of insurance and actuarial science domains. He focuses on decision-making under risk and uncertainty, credibility theory, and insurance analytics, integrating statistical and machine learning methods into quantitative risk management. His work explores health and mortality modeling, auto and life insurance, annuities, loss reserves, and property and casualty insurance. He also examines the implications of insurance regulations, macroeconomic factors affecting insurance performance, and the adoption of advanced accounting standards such as IFRS 17. His interdisciplinary approach merges statistical modeling, computational tools, and economic theory to produce impactful insights for the insurance industry.
Awards and Contributions
Throughout his career, Dr. Seyam has been recognized for his scholarly contributions through publications in peer-reviewed journals and conference presentations at prestigious platforms such as the American Risk and Insurance Association Annual Meeting. His academic outputs include books on risk management, insurance mathematics, and financial mathematics with practical implementations in R programming. In addition to research excellence, he has designed educational programs, training modules, and institutional strategies for enhancing accreditation standards in higher education. He has also delivered numerous training courses in areas ranging from statistical methods and investment theory to scientific publishing and academic conference organization, contributing to professional capacity building in academia and industry.
Publications
Predicting High-Cost Healthcare Utilization Using Machine Learning: A Multi-Service Risk Stratification Analysis in EU-Based Private Group Health Insurance
Authors: Eslam Abdelhakim Seyam
Journal: Risks
Year: 2025
Modeling the Determinants of Insurtech Adoption: Evidence from the Saudi Insurance Industry
Authors: Eslam Abdelhakim Seyam
Journal: International Journal of Innovative Research and Scientific Studies
Year: 2025
Analyzing the Impact of IFRS 17 on Insurance Reserves Management: A Multifaceted Assessment
Authors: Ahmed Nasr, Mahmoud Mohamed Elsayed, Eslam Abdelhakim Seyam
Journal: Journal of Financial and Business Research (مجلة البحوث المالية والتجارية)
Year: 2024
Comprehensive Analysis of Credit Risk Determinants in the Egyptian Property and Casualty Insurance Sector: Exploring Macroeconomic, Industrial, and Company Specific Factors
Authors: Eslam Abdelhakim Seyam
Journal: Scientific Journal for Financial and Commercial Studies and Research (المجلة العلمية للدراسات والبحوث المالية والتجارية)
Year: 2024
Proposed Models for Comprehensive Automobile Insurance Ratemaking in Egypt with Parametric and Semi-Parametric Regression: A Case Study
Authors: Eslam Abdelhakim Seyam, Hussien Elsalmouny
Journal: Journal of Statistics Applications & Probability
Year: 2022
Conclusion
Dr. Eslam Abdelhakim Kamel Seyam stands out as a dedicated educator, innovative researcher, and institutional leader in insurance and risk management education. His expertise in actuarial science, combined with advanced statistical and computational skills, positions him as a key contributor to the evolving landscape of insurance research and education. Through his teaching, publications, and institutional initiatives, he continues to shape the next generation of professionals equipped to navigate the complexities of global insurance markets. His work not only advances academic knowledge but also delivers practical frameworks for addressing real-world challenges in risk management and insurance analytics.