Nos derniers articles

"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 planner. We characterize the adoption gap between decentralized (Nash) and centralized blockchain consortium."

"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, it was determined that these models can be a useful tool for insurance companies when dealing with extreme risks. This includes their exposure and solvency. Additionally, the study explores issues related to climate change"

"... 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 a high threshold, and the asymptotic probability of such events follow the so-called “one large jump” principle..."

"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 using the tool to solve practical problems of operational financial risk estimation."

"We propose here an analysis of the database of the cyber complaints filed at the Gendarmerie Nationale.We perform this analysis with a new algorithm developed for non-negative asymmetric heavy-tailed data, which could become a handy tool in applied fields. This method gives a good estimation of the full distribution including the tail. Our study confirms the finiteness of the loss expectation, necessary condition for insurability."

"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. "

"... 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 by the insurer."

"… this article introduces decision models and shows that the optimal title insurance evolves as market and property-specific conditions change. "

"... our findings question whether insurance rates can play a useful role in steering climate adaptation and whether households will have continued access to insurance."

"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."