INSURANCE MATHEMATICS & ECONOMICS

Scope & Guideline

Unveiling the complexities of insurance through economic lenses.

Introduction

Delve into the academic richness of INSURANCE MATHEMATICS & ECONOMICS with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageMulti-Language
ISSN0167-6687
PublisherELSEVIER
Support Open AccessNo
CountryNetherlands
TypeJournal
Convergefrom 1982 to 2024
AbbreviationINSUR MATH ECON / Insur. Math. Econ.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS

Aims and Scopes

The journal 'Insurance Mathematics & Economics' primarily focuses on the intersection of insurance practices and mathematical frameworks, aiming to enhance the understanding and application of economic principles within the insurance domain. It encompasses a wide range of methodologies, including stochastic modeling, game theory, and statistical analysis, to address complex insurance-related challenges.
  1. Stochastic Modeling in Insurance:
    The journal extensively publishes research on stochastic processes and models to analyze various insurance phenomena, such as claim frequency and severity, mortality rates, and investment strategies.
  2. Risk Management Techniques:
    A significant focus is placed on developing and refining methodologies for effective risk management, including reinsurance strategies, optimal investment approaches, and the evaluation of insurance contracts under uncertainty.
  3. Mathematical and Statistical Methods:
    The use of advanced mathematical techniques, including regression models, copulas, and Bayesian methods, is prevalent in the journal, facilitating rigorous analysis and decision-making in insurance economics.
  4. Behavioral Economics in Insurance:
    The journal explores how behavioral aspects influence insurance decisions, such as risk aversion and moral hazard, integrating psychological insights with mathematical modeling to inform policy design.
  5. Innovative Insurance Products:
    Research often revolves around the design and valuation of novel insurance products, including variable annuities and long-term care insurance, addressing contemporary market needs and regulatory challenges.
Recent publications in 'Insurance Mathematics & Economics' indicate a clear trend towards integrating advanced analytical techniques and addressing contemporary issues in the insurance sector. These emerging themes reflect the journal's responsiveness to evolving market needs and technological advancements.
  1. Machine Learning and Data Analytics:
    There is a growing emphasis on the application of machine learning and data analytics in insurance, particularly for claim prediction, risk assessment, and enhancing customer insights, showcasing the industry's shift towards data-driven decision-making.
  2. Longevity Risk and Aging Populations:
    Research focusing on longevity risk management is increasingly prevalent, driven by demographic shifts and the need for sustainable pension systems, highlighting the importance of effective strategies to address the financial implications of aging populations.
  3. Behavioral Insights in Insurance Decisions:
    Emerging studies are exploring the behavioral aspects influencing insurance decisions, such as risk perception and decision-making biases, which are critical for designing more effective insurance products and marketing strategies.
  4. Cyber Risk and Insurance Solutions:
    With the rise of digital threats, there is an increasing focus on cyber risk modeling and insurance solutions tailored to address the unique challenges posed by cybersecurity, reflecting the growing importance of this area in the insurance landscape.
  5. Regulatory and Economic Impacts on Insurance Markets:
    Research is increasingly examining the effects of regulatory changes and economic conditions on insurance markets, emphasizing the need for adaptable strategies that align with evolving legal and economic frameworks.

Declining or Waning

While the journal continues to evolve, certain themes have shown a decline in prominence over recent years. These waning areas indicate shifts in research focus or a saturation of exploration in previously popular topics.
  1. Traditional Life Insurance Models:
    There has been a noticeable decrease in studies focused on traditional life insurance models, as researchers increasingly favor more complex and adaptable frameworks that incorporate stochastic elements and behavioral factors.
  2. Static Risk Assessment Models:
    Static models that do not account for dynamic changes in risk factors are becoming less frequently published, as the field moves towards more robust, time-consistent approaches that incorporate real-time data and evolving market conditions.
  3. Generalized Linear Models (GLMs):
    The use of generalized linear models for insurance claims analysis has decreased, likely due to the emergence of more sophisticated machine learning techniques that provide greater flexibility and predictive power.
  4. Deterministic Approaches to Pricing:
    Deterministic pricing models are seeing reduced interest as the focus shifts to stochastic and dynamic pricing strategies that better reflect market volatility and uncertainty.

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