Develops a Bonus-Malus model for cyber risk insurance to incentivize cybersecurity.
problem Lack of effective insurance strategies to incentivize cybersecurity.
method Proposes a Bonus-Malus model and a mathematical model with a numerical algorithm.
result Demonstrates how a Bonus-Malus system resolves moral hazard and benefits the insurer.
Study on cyber insurance viability using statistical models.
problem Exploring insurability of cyber risk and its factors.
method Regression models (GAMLSS, ordinal regressions) and utility modelling.
result Provides insights into insurability of cyber risk.
The paper models and prices cyber insurance risks, distinguishing idiosyncratic, systematic, and systemic risks.
problem Modeling and pricing cyber insurance policies, especially for systemic risks.
method Distinguishes three types of cyber risks and proposes methods for their valuation.
result Complex methods are needed for systemic cyber risks, including risk-neutral valuation and monetary risk measures.
Paper introduces a framework for managing cyber risk with insurance and cybersecurity models.
problem Pervasive challenges in managing cyber risk, especially for capital allocation.
method Combines insurance frequency-severity models with cybersecurity cascade models for comprehensive cyber risk assessment. Facilitates informed capital allocation through a two-pillar framework.
result Demonstrates the necessity of comprehensive cost-benefit analysis for budget-constrained companies.
This research develops a new model for cyber risk and insurance pricing.
problem Accurate calculation of aggregate losses in cyber insurance pricing.
method A path-based k-generation risk contagion model in a tree-shaped network structure.
result Explicit expressions for mean and variance of local loss on a single path.
Introduces an artificial cyber lab to test and identify cyber resilience measures.
problem Systemic cyber risks and their control methods.
method Classical contagion models and artificial cyber lab simulations.
result Identified two classes of measures: security- and topology-based interventions.
Study quantifies model risk in cyber insurance, affecting premium pricing.
problem Model risk and risk sensitivity in cyber insurance pricing.
method Robust estimators for model parameters and dependence analysis.
result Robust estimation improves tail index and joint loss model accuracy.
This paper aims to optimize incident-specific cyber insurance design.
problem Complexity in determining optimal risk retention and transfer.
method Economic foundation for incident-specific cyber insurance with Pareto optimality.
result Illustrates feasibility of designing incident-specific indemnities for both parties.
Paper models cloud outages for cyber insurance stress-testing.
problem Cyber insurance portfolios' vulnerability to simultaneous cloud outages.
method Modeling and calibrating cloud-outage scenarios, measuring diversification.
result Cloud-outage diversification can protect against accumulation risk.
Paper analyzes cyber risk classifications for forecasting performance.
problem Lack of effective out-of-sample forecasting performance in current cyber risk classifications.
method Rolling window analysis using threshold weighted scoring functions.
result Dynamic and impact-based cyber risk classifiers outperform others in forecasting future cyber risk losses.
Paper introduces a new model for cyber insurance pricing.
problem Inaccurate pricing of cyber insurance due to multiple, contagious losses.
method Developed a bivariate compound dynamic contagion process.
result Analytical expressions for the compound process and its moments.
Study proposes framework for cyber bonds to compensate cyber attack losses.
problem Cyber risk treatment in finance industry.
method Developed a framework, used publicly available data to determine loss distribution parameters, numerically simulated bond price and characteristics, considered two coupon calculation approaches.
result Numerical simulations of cyber bond price, yield, and characteristics.
The paper examines the feasibility of managing aggregate cyber-risk in IoT environments.
problem Determining sustainable conditions for providing aggregate cyber-risk coverage.
method Developed a rigorous general theory and validated it with real data.
result Conditions for sustainable aggregate cyber-risk management under heavy-tailed distributions.
This paper maps the insurability of AI risks across various insurance products.
problem Emerging AI risks and their implications for insurance coverage.
method Coding 55 AI threat classes against 26 insurance products using public carrier materials and threat catalogs.
result Identification of a four-tier insurability frontier: affirmatively insured, silent-AI exposures, actively excluded, and unstructured perils.
Paper models demand and solvency for index insurance, combining traditional and measurable index-based coverage.
problem Reducing protection gaps for emerging risks.
method Develops a model for demand and solvency conditions, combining traditional and index-based insurance.
result Deduces a product that benefits from both traditional and index-based insurance approaches.
Approach for assessing supply chain cyber risks using expert judgment and forecasting.
problem Supply chain managers face challenges in assessing cyber risks affecting business factors.
method Structured expert judgment and forecasting models to assess various attack techniques and impacts.
result Facilitates implementation of risk management activities and decision-making processes.
Enhances cyber risk assessment with entity-specific features.
problem Lack of high-quality public cyber incident data.
method Develops an InsurTech framework to enrich cyber incident data with entity-specific attributes and implements machine learning models.
result InsurTech features improve prediction robustness and provide customized risk profiles.
Model quantifies cyber-attacks' impact on firms and insurers.
problem Impact of cyber-attacks on firms' revenues and insurers' portfolios.
method Stochastic SIR model coupled with granular firm growth model.
result Predicts insurer needs to compensate up to two days of revenue in a 100-day incident.
Study analyzes data breach reporting patterns and frequency across U.S. states, finding increasing trends after 2020.
problem Contradictory conclusions in data breach frequency trends due to inconsistent data collection and reporting standards.
method Joint analysis of state Attorneys General's publications on data breaches across eight states with established notification laws.
result Frequency of data breaches is increasing after 2020, with commonalities and heterogeneities across states.
Study finds stocks with higher cyber risk scores outperform others, indicating a market-wide cyber risk premium.
problem Identifying and quantifying firms' cyber risks and their impact on stock performance.
method Machine learning algorithm to analyze disclosures and a dedicated cyber corpus.
result High cyber risk stocks significantly outperform others, indicating a market-wide cyber risk premium.
Study finds high cyber risk stocks generate significant excess returns.
problem Understanding and quantifying cyber risk's impact on stock returns.
method Machine learning algorithm measuring cyber risk proximity to a corpus.
result High cyber risk stocks generate an excess return of 18.72% p.a.
Study examines cyber losses across sectors, finds high severity and frequency.
problem Understanding the nature of cyber losses and their variability across sectors.
method Analysis of a leading industry dataset of cyber events, focusing on frequency and severity.
result Cyber risks are heavy-tailed, with high probability of extreme losses.
A novel model combines deep learning and extreme value theory for multivariate cyber risk prediction.
problem High dimensionality and heavy tails in multivariate cyber risk patterns.
method Combines deep learning for point predictions and extreme value theory for quantile predictions.
result The model provides satisfactory high quantile predictions and accurate point predictions.
The paper introduces a US crime index to assess financial losses from property and cyber crimes.
problem Lack of indices evaluating crime's financial impact on investments.
method Developed an index-based insurance portfolio using FBI financial losses data.
result Real estate, ransomware, and government impersonation are major risk contributors.
Framework for managing cyber risks in networks.
problem Managing systemic cyber risks in digital networks.
method Three components: acceptable configurations, risk mitigation interventions, and cost function.
result Effective decision-making for network resilience.
The paper shows supply chain features improve cyber risk prediction.
problem Predicting cyber risk from supply chain attributes.
method Machine learning, external supply chain features, AUC improvement.
result Supply chain network features improve AUC by 2.3%.
This paper optimizes cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.
problem Optimizing cybersecurity resource allocation in networks with heterogeneous attacker and defender valuations.
method Combining strategic behavior of players with contagion dynamics, a method is extended to determine optimal resource allocation based on simple network metrics weighted by risk profiles.
result The asymmetry between attacker and defender valuations drives optimal attack and defense strategies, shaping system resilience.
New method assesses financial and cyber risks under uncertainty.
problem Uncertainty in risk assessment for financial and cyber systems.
method Combines stochastic approximation and distorted mix method to compute worst case average value at risk.
result Efficient algorithm for tail uncertainty in multivariate distributions.
Parametric insurance offers better risk-sharing in high-risk settings than traditional indemnity insurance.
problem High-risk environments where traditional indemnity insurance is unaffordable or ineffective.
method Comparison of excess-of-loss indemnity insurance and parametric insurance within a mean-variance framework, considering fixed costs and binding budget constraints.
result Parametric insurance yields higher welfare for risk-averse individuals, especially when indemnity insurance is impractical.
The study examines how formal index insurance compares to informal risk sharing in managing natural disasters.
problem The challenges of natural disasters and the effectiveness of index insurance in risk management.
method A three-strategy evolutionary game model to analyze the competitive relationship between formal index insurance, informal risk sharing, and non-insurance.
result Basis risk and loss ratio significantly impact the adoption rate of index insurance, with different strategies preferred under varying conditions.
Two pension funds mutually insure against longevity risk.
problem Mutual insurance against systematic longevity risk for pension funds.
method Mathematical demonstration and market clearing condition.
result Insurance provides little benefit when fund preferences are similar, but can be beneficial when preferences vary significantly.
Study on systemic risk in European insurance sector, showing insurer connections during stress.
problem Understanding systemic risk connectedness in European insurance sector.
method Common connectedness framework applied to returns, volatility, value-at-risk, and expected shortfall.
result Insurers are a significant component of systemic risk connectedness, especially during stress episodes.
The paper examines how risk reduction and insurance choices interact under convex premium principles.
problem Interaction between self-protection and insurance demand under convex premium principles.
method Investigates optimal prevention efforts and insurance shares using distortion risk measures.
result Self-protection and insurance are complementary, but ex ante moral hazard can turn this into a substitution effect.
The paper calculates bonus values in complex insurance schemes.
problem Calculating bonus payments in multi-state with-profit life insurance.
method Combines financial risk simulation with insurance risk methods.
result Efficient numerical procedures for bonus calculation.
The paper analyzes how to combine self-protection and self-insurance for risk reduction.
problem Combining self-protection and self-insurance for risk reduction when market insurance is absent.
method The approach uses Value-at-Risk and Tail Value-at-Risk to evaluate residual risk and solves the problem using isoquant geometry based on marginal-balance curves.
result The analysis identifies the conditions under which self-protection and self-insurance behave as substitutes or complements.
Network theory assesses systemic risk in the insurance sector.
problem Detecting critical insurance companies in systemic risk.
method Complex network approach with weighted effective resistance centrality.
result Identifies companies with significant influence on network robustness.
This paper discusses adversarial attacks on cyber security systems using machine learning.
problem Adversarial attacks limit the use of machine learning in cyber security.
method Characterizes adversarial attack methods and their applications in cyber security.
result Highlights unique challenges and future research directions for adversarial attacks in cyber security.
Algorithmic insurance tackles financial risks from AI errors, proving CVaR-optimal thresholds reduce tail risk.
problem High-stakes AI errors lead to heterogeneous losses, challenging traditional insurance assumptions.
method Analyzed binary classification performance to tail risk exposure, using CVaR to quantify extreme losses.
result CVaR-optimal thresholds reduce tail risk up to 13-fold compared to accuracy maximization.
Optimal insurance contracts are designed to screen risk preferences and risk types under asymmetric information.
problem Designing optimal insurance contracts under asymmetric information and risk types.
method Constructing a menu of contracts that maximizes mean-variance utilities, subject to truth-telling constraints.
result Equilibrium contracts exhibit nonlinear pricing with decreasing risk loadings, inducing self-selection.
Study proposes a tax-based system to share disaster risk among regions.
problem Systemic risk in catastrophic events and insurer insolvency.
method Public-private partnership with government intervention through taxation.
result Taxation system effectively shares residual claims in case of insurer insolvency.
This study tackles basis risk in weather parametric insurance using Monte Carlo simulations.
problem Mismatch between actual loss and payout in weather parametric insurance leads to loss without payout or payout without loss.
method Empirical research using Monte Carlo simulations to test diversification and hedging strategies.
result Portfolio basis risk and volatility decrease with more contracts, and spatial relationships significantly impact basis risk.
Auto insurers improve risk assessment using t-SNE.
problem Accurate risk estimation for auto insurance policyholders.
method Combining neural network with t-SNE for dimensionality reduction.
result Visual representation of risk as a 2D surface, revealing high vs low risk policyholders.
Reinsurance can help life insurers maintain higher capital guarantees without losing utility.
problem Decreasing capital guarantees in life insurance products.
method Dynamic investment-reinsurance optimization problem with simultaneous Value-at-Risk and no-short-selling constraints. Introduced guarantee-equivalent utility gain for comparison.
result Optimally managed reinsurance allows insurers to offer higher capital guarantees without reducing expected utility.
Study optimal reinsurance for insurers with a reinsurer's default risk.
problem Optimal reinsurance for insurers with a reinsurer's default risk.
method Analytical solution for two types of reinsurance contracts.
result Joint effect of reinsurer's default and background risk on reinsurance demand.
Investment and insurance decisions are studied in a model with nonlinear portfolio frictions and background risk.
problem Investment and insurance decisions under a model with nonlinear portfolio frictions and background risk.
method Dynamic programming approach to find optimality conditions.
result Agent can choose to assume, partially assume, or purchase total insurance against adverse jumps in wealth.
CyPhERS provides real-time event info for CPSs, avoiding downtime.
problem Real-time event identification in CPSs is challenging due to complex interdependencies and rare events.
method CyPhERS integrates cyber and physical components, generating event signatures for known and unknown events.
result Event signatures provide relevant and inferable information on both known and unknown event types.
Novel convex risk measures aggregate multiple uncertain sources for insurance firms.
problem Managing risk from multiple uncertain sources in insurance.
method Proposes convex risk measures based on Fréchet mean.
result Allows for robust risk characterization and closed-form expressions.
Fair insurance contracts are designed to handle default risk using cooperative game theory.
problem Designing fair insurance contracts in the presence of default risk.
method Cooperative game theory to specify premiums and participation in benefit.
result Fair benefit participation emerges as a game outcome involving residual risks.