Online-reinsurance

Рассмотрены потребительскую ценность, преимущества и недостатки онлайн-перестрахование. Выявлено влияние работы системы менеджмента качества поставщика ИТ-услуг электронной биржи перестрахования и ее пользователей на эффективность их бизнес-процессов. Проанализированы отдельные аспекты и перспективы развития четырех международных сервисов онлайн-перестрахование.Consumer value, the advantages and disadvantages of online reinsurance. The effect of the operation of the quality management system of supplier of it-services of electronic exchange of reinsurance and its users on the effectiveness of their business processes. We have analyzed some aspects and prospects of development of four international services, online reinsurance.Розглянуто споживчу цінність, переваги та недоліки онлайн-перестрахування. Виявлено вплив роботи системи менеджменту якості постачальника ІТ послуг електронної біржі перестрахування та її користувачів на ефективність їх бізнес-процесів. Проаналізовано окремі аспекти й перспективи розвитку чотирьох міжнародних сервісів онлайн-перестрахування

Excess of loss reinsurance under joint survival optimality

Explicit expressions for the probability of joint survival up to time x of the cedent and the reinsurer, under an excess of loss reinsurance contract with a limiting and a retention level are obtained, under the reasonably general assumptions of any non-decreasing premium income function, Poisson claim arrivals and continuous claim amounts, modelled by any joint distribution. By stating appropriate optimality problems, we show that these results can be used to set the limiting and the retention levels in an optimal way with respect to the probability of joint survival. Alternatively, for fixed retention and limiting levels, the results yield an optimal split of the total premium income between the two parties in the excess of loss contract. This methodology is illustrated numerically on several examples of independent and dependent claim severities. The latter are modelled by a copula function. The effect of varying its dependence parameter and the marginals, on the solutions of the optimality problems and the joint survival probability, has also been explored

Premium Risk net of Reinsurance: from short-term to medium term assessment

Solvency II requirements introduced new issues for actuarial risk management in non-life insurance, challenging the market to have a consciousness of its own risk profile, and also investigating the sensitivity of the solvency ratio depending on the insurance risks and technical results on either a short-term and medium-term perspective. For this aim, in the present paper, a partial internal model for premium risk is developed for three multi-line non-life insurers, and the impact of some different business mixes is analyzed. Furthermore, the risk-mitigation and profitability impact of reinsurance in the premium risk model are introduced, and a global framework for a feasible application of this model consistent with a medium-term analysis is provided. Numerical results are also figured out with evidence of various effects for several portfolios and reinsurance arrangements, pointing out the main reasons for these differences

Insurance with multiple insurers: A game-theoretic approach

This paper studies the set of Pareto optimal insurance contracts and the core of an insurance game. Our setting allows multiple insurers with translation invariant preferences. We characterise the Pareto optimal contracts, which determines the shape of the indemnities. Closed-form and numerical solutions are found for various preferences that the insurance players might have. Determining associated premiums with any given optimal Pareto contract is another problem for which economic-based arguments are further discussed. We also explain how one may link the recent fast growing literature on risk-based optimality criteria to the Pareto optimality criterion and we show that the latter is much more general than the former one, which according to our knowledge, has not been pointed out by now. Further, we extend some of our results when model risk is included, i.e. there is some uncertainty with the risk model and/or the insurance players make decisions based on divergent beliefs about the underlying risk. These robust optimal contracts are investigated and we show how one may find robust and Pareto efficient contracts, which is a key decision-making problem under uncertainty

Toward a Social Practice Theory of Relational Competing

This paper brings together the competitive dynamics and strategy-aspractice literatures to investigate relational competition. Drawing on a global ethnography of the reinsurance market, we develop the concept of micro-competitions, which are the focus of competitors’ everyday competitive practices. We find variation in relational or rivalrous competition by individual competitors across the phases of a micro-competition, between competitors within a micro-competition, and across multiple micro-competitions. These variations arise from the interplay between the unfolding competitive arena and the implementation of each firm’s strategic portfolio. We develop a conceptual framework that makes four contributions to: relational competition; reconceptualizing action and response; elaborating on the awareness-motivation-capability framework within competitive dynamics; and the recursive dynamic by which implementing strategy inside firms shapes, and is shaped by, the competitive arena

The Urban Institute's Microsimulation Model for Reinsurance: Model Construction and State-Specific Application

Describes the Urban Institute's model for simulating the effects of using state-funded reinsurance to subsidize primary insurance premiums. Details the process of building state-specific baseline databases and modeling reinsurance policy options

QuPARA: Query-Driven Large-Scale Portfolio Aggregate Risk Analysis on MapReduce

Stochastic simulation techniques are used for portfolio risk analysis. Risk portfolios may consist of thousands of reinsurance contracts covering millions of insured locations. To quantify risk each portfolio must be evaluated in up to a million simulation trials, each capturing a different possible sequence of catastrophic events over the course of a contractual year. In this paper, we explore the design of a flexible framework for portfolio risk analysis that facilitates answering a rich variety of catastrophic risk queries. Rather than aggregating simulation data in order to produce a small set of high-level risk metrics efficiently (as is often done in production risk management systems), the focus here is on allowing the user to pose queries on unaggregated or partially aggregated data. The goal is to provide a flexible framework that can be used by analysts to answer a wide variety of unanticipated but natural ad hoc queries. Such detailed queries can help actuaries or underwriters to better understand the multiple dimensions (e.g., spatial correlation, seasonality, peril features, construction features, and financial terms) that can impact portfolio risk. We implemented a prototype system, called QuPARA (Query-Driven Large-Scale Portfolio Aggregate Risk Analysis), using Hadoop, which is Apache's implementation of the MapReduce paradigm. This allows the user to take advantage of large parallel compute servers in order to answer ad hoc risk analysis queries efficiently even on very large data sets typically encountered in practice. We describe the design and implementation of QuPARA and present experimental results that demonstrate its feasibility. A full portfolio risk analysis run consisting of a 1,000,000 trial simulation, with 1,000 events per trial, and 3,200 risk transfer contracts can be completed on a 16-node Hadoop cluster in just over 20 minutes.Comment: 9 pages, IEEE International Conference on Big Data (BigData), Santa Clara, USA, 201

Economic Analysis of the Standard Reinsurance Agreement

The paper presents an economic analysis of the Standard Reinsurance Agreement (SRA), the contract that governs the relationship between the Federal Crop Insurance Corporation and the private insurance companies that deliver crop insurance products to farmers. The paper outlines provisions of the SRA and describes the modeling methodology behind the SRA simulator, a computer program developed to assist crop insurers and policymakers in assessing the economic impact of the Agreement. The simulator is then used to analyze how the SRA affects returns from underwriting crop insurance at various levels of aggregation.Risk and Uncertainty,