European Actuarial Journal

Aims & Scope

Actuarial science and actuarial finance deal with the study, modeling and managing of insurance and related financial risks for which stochastic models and statistical methods are available.

Topics include classical actuarial mathematics such as life and non-life insurance, pension funds, reinsurance, and also more recent areas of interest such as risk management, asset-and-liability management, solvency, catastrophe modeling, systematic changes in risk parameters, longevity, etc.

EAJ is designed for the promotion and development of actuarial science and actuarial finance.

For this, we publish original actuarial research papers, either theoretical or applied, with innovative applications, as well as transfer papers on the evaluation and implementation of new mathematical methods in insurance and actuarial finance.

EAJ is the successor of six national actuarial journals, so it is focused on theory and methods for applications in insurance and finance.

EAJ publishes research articles, survey articles as well as papers for the mutual transfer between research and application.

View Aims & Scope

---

Metrics & Ranking

Impact Factor

Year	Value
2025	1.6
2024	0.80

Journal Rank

Year	Value
2024	10287

Journal Citation Indicator

Year	Value
2024	137

SJR (SCImago Journal Rank)

Year	Value
2024	0.565

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	22

---

---

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

---

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Decision Sciences, Economics, Econometrics and Finance and Mathematics, designed to support cutting-edge academic discovery.

---

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Remarks on quantiles and distortion risk measures

  Citation: 112

  Authors: Jan, Alexander, Daniël, Qihe

• The optimal dividend barrier in the Gamma–Omega model

  Citation: 81

  Authors: Hansjörg, Hans U., Elias S. W.

• Machine learning techniques for mortality modeling

  Citation: 55

  Authors: Philippe, Pavel V., Mario V.

• The impact of policyholder behavior on pricing, hedging, and hedge efficiency of withdrawal benefit guarantees in variable annuities

  Citation: 55

  Authors: Alexander, Frederik, Jochen

• Poisson regression and Zero-inflated Poisson regression: application to private health insurance data

  Citation: 52

  Authors: Younès, El Hadj

• Neural networks applied to chain–ladder reserving

  Citation: 50

  Authors: Mario V.

• Covariate selection from telematics car driving data

  Citation: 49

  Authors: Mario V.

• Cyber risk research in business and actuarial science

  Citation: 49

  Authors: Martin

• Bias regularization in neural network models for general insurance pricing

  Citation: 48

  Authors: Mario V.

• Optimal risk transfers in insurance groups

  Citation: 45

  Authors: Alexandru V., Alexandru M., Andreas

---