Blockchain Adoption and Optimal Reinsurance Design

“We study blockchain adoption in insurance-reinsurance markets. Operating costs decrease with the adoption rate, since verification and storage costs are shared. We quantify how the equilibrium adoption decisions depend on contract characteristics, risk aversions, potential losses and cost structure. The reinsurance firm internalizes the benefits of adoption on other insurance firms, acting as a central […]

Analysis of New Models of Emerging Risk for Insurance Companies: The Climate Risk

“We aim to analyze strategies for assessing and managing new risks that affect the insurance industry, considering the regulatory requirements that the company must follow. To this end, the open-source software Climada was examined. This software uses stochastic forecasting models such as ARCH, GARCH, and ARIMA. Through real data obtained during an internship at E&Y, […]

Aggregating heavy-tailed random vectors: from finite sums to Lévy processes

“… we study the behavior of the asymptotic tail distribution of independent sums of heavy-tailed random vectors under the paradigm of multivariate regular variation. Assessment of such tail probabilities are of interest in risk management for many finance, insurance, queueing, and environmental applications. Multidimensional tail events are often characterized by at least one variable exceeding […]

The Bayesian approach to analysis of financial operational risk

“The article provides a short overview of methods for constructing mathematical models in the form of Bayesian Networks for modeling operational risks under conditions of uncertainty. Let’s provide the sequence of actions necessary for creating a model in the form of the network, methods for computing a probabilistic output in BN, and give examples of […]

Financing Constraints and Risk Management: Evidence From Micro-Level Insurance Data

“Using data on credit scores matched with unique information on firm level commercial insurance purchases, we find that financing constraints lead to higher insurance spending. We adopt a regression discontinuity design and show that financially constrained firms spend 5–14% more on insurance than otherwise similar unconstrained firms. “ Lire

Prediction of Auto Insurance Risk Based on t-SNE Dimensionality Reduction

“… we develop a framework based on a combination of a neural network together with a dimensionality reduction technique t-SNE (t-distributed stochastic neighbour embedding)… The obtained results, which are based on real insurance data, reveal a clear contrast between the high and low risk policy holders, and indeed improve upon the actual risk estimation performed […]

The Government Behind Insurance Governance: Lessons for Ransomware

“This paper analyzes how governments support insurance markets to maintain insurability and limit risks to society. We propose a new conceptual framework grouping government interventions into three dimensions: regulation of risky activity, public investment in risk reduction, and co-insurance.” Lire

Assessing the difference between integrated quantiles and integrated cumulative distribution functions

“When developing large-sample statistical inference for quantiles, also known as Values-at-Risk in finance and insurance, the usual approach is to convert the task into sums of random variables. The conversion procedure requires that the underlying cumulative distribution function (cdf) would have a probability density function (pdf), plus some minor additional assumptions on the pdf. In […]

Insurance and Enterprise: Cyber Insurance for Ransomware

“As businesses improved their resilience, cybercriminals adapted and ransoms escalated, calling insurability into question. Yet there remains little appetite for imposing restrictive conditionality in this highly competitive market. Instead, insurers have turned to governments to contain criminal threats and cushion catastrophic losses.” Lire

Multivariate Poisson Model Adjusting for Unidirectional Covariate Misrepresentation

“Insurance fraud has been a long-lasting issue in actuarial modeling. Policyholders are prone to hide their true status in their best interest when disclosing their information for insurance pricing purposes. However, from the insurers’ point of view, it is either time-consuming or laborious to verify the true status of such risk factors. There is thus a strong […]

Can We Nudge Insurance Demand by Bundling Natural Disaster Risks with Other Risks?

“Our findings show that demand is overall higher to insure separate risks than to cover all risks together in a bundled insurance policy in the UK, whereas no significant difference is found between demand for bundled insurance and single policy insurance in the Netherlands. This difference in preference across the two countries is partly associated […]

Regulatory Capital and Asset Risk Transfer

“… most modified coinsurance is purchased from reinsurers located in countries with lower regulatory capital requirements and within the same insurance holding group. Our findings expose how insurers use reinsurance to obfuscate their asset risk.” Lire

Flood Risk Insurance: A Micro-Economic Foundation

“… we characterize Pareto-optimal risk-sharing contracts in a market with multiple policyholders and one representative insurer. With minimal assumptions on the risk measures of the parties involved, we characterize Pareto optimality in terms of the minimization of a sum of the agents’ risk positions, and we relate it to both the core and coalitional stability of an associated market game. […]

Modeling and Pricing Cyber Insurance — A Survey

“We distinguish three main types of cyber risks: idiosyncratic, systematic, and systemic cyber risks. While for idiosyncratic and systematic cyber risks, classical actuarial and financial mathematics appear to be well-suited, systemic cyber risks require more sophisticated approaches that capture both network and strategic interactions.” Lire