Standard daily trade service.

"A condensed survey and forecast of business everywhere."

A bizonytalanságnak és a vevőkör nagyságának együttes hatása az árakra (Investigating how the number of policies effect the optimum insurance premium)

Ebben a cikkben azzal foglalkozom, hogy a kockázat és a vevőkör nagysága együttesen hogyan hat a termék árára. Kétféle piacot hasonlítok össze: egy biztosítási piacot, és egy termékpiacot. A kétféle piac között az a legfontosabb különbség, hogy termékpiac esetében az eladó számára csak ott jelentkezik kockázat, hogy el tudja-e adni a terméket, míg biztosítási piac esetében az eladó a termék értékesítése után is szembesül kockázattal. A cikk során megmutatom, hogy a vevőkör növekedésének ellentétes hatása lehet a termék árára termék- illetve biztosítási piacok esetében. / === / An economic approach for modeling the insurance markets. The study focuses on the monopolistic market, where one insurance company sells a product with predetermined benefits for the customers. An outline of the company and the insureds' behavior with utility functions is given. The study investigates the problem of policy pricing in relation to the number of clients the company acquires. Analytic tools will be used to further clarify the points.

Crop Insurance For Maryland Field Crops And Livestock

Multi-peril crop insurance is a valuable risk management tool which allows you to insure against losses on your farm due to adverse weather conditions, price fluctuations, and unavoidable pests and diseases. It shifts unavoidable production risks to an insurance company for the payment of a fixed amount of premium per acre. This publication assists readers in understanding the basics of the federal crop insurance program.

Marketing to change public opinion on climate change : a case study

Corporate advertisers spend far greater budgets than any social marketing campaign and have great potential to change public opinion on the urgent need for action on climate change. However “green-washing” has become a widespread practice by companies that wish to appear to be socially responsible without a genuine commitment and consumers can be very cynical about green marketing campaigns. Can companies be climate change advocates and still satisfy shareholders? This paper offers a case study on an Australian insurance company that argues it can make money from doing the right thing.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

Business Process Model Merging : An Approach to Business Process Consolidation

This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.

Practice and procedure - Disclosure of documents - application of UCPR r222 to documents referred to in exhibit to affidavit

In Century Drilling Limited v Gerling Australia Insurance Company Pty Limited [2004] QSC 120 Holmes J considered the application of a number of significant rules impacting on the obligation to disclose under the Uniform Civil Procedure Rules 1999

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

Stress during the rebuilding phase influenced mental health following two Queensland flood disasters more than the event itself

It has long been known that disasters can have mental health consequences such as increased rates of PTSD, depression and anxiety. While some research has shown that secondary stressors during the aftermath of a disaster can influence psychological outcomes, this aspect of the disaster experience has not been widely studied. This paper reports on two studies that investigated which aspects of the experience of being flooded were most predictive of mental health outcomes. The first study was a qualitative study of adults whose homes had been inundated in the Mackay flood of 2008 (n=16). Thematic analysis of interviews conducted 18-20 months post-flood found that stressors during the flood aftermath such as difficulties and delays during the rebuilding process and a difficult experience with an insurance company were nominated as the most stressful aspect of the flood by the majority of participants. The second study surveyed Mackay flood survivors three and a half years post-flood, and Brisbane 2011 flood survivors 7-9 months post-flood (n=158). Findings indicated aftermath stress contributed to mental health outcomes over and above the contribution of perceived trauma, objective flood severity, prior mental health, self-efficacy and demographic factors. The implications of these results for the provision of community recovery services following natural disasters are discussed, including the need to provide effective targeting of support services throughout the lengthy rebuilding phase; a possible role for co-ordinating tradespeople; and training for insurance company staff aimed at minimising the incidence of insurance company staff inadvertently adding to disaster victims’ stress.

Factors influencing vulnerability and positive post-disaster response following the Mackay 2008 and Brisbane 2011 floods

This project investigated which aspects of being flooded most affected mental health outcomes. It found that stress in the aftermath of the flood, during the clean-up and rebuilding phase, including stress due to difficulties with insurance companies, was a previously overlooked risk factor, and social support and sense of belonging were the strongest protective factors. Implications for community recovery following disasters include providing effective targeting of support services throughout the lengthy rebuilding phase; the need to co-ordinate tradespeople; and training for insurance company staff aimed at minimising the incidence of insurance company staff inadvertently adding to disaster victims' stress.

Louis Lipsky papers 1898-1976

Consists of speeches, memoranda, correspondence, publications, clippings and ephemera pertaining to the life and career of a prominent American Zionist.

Análise da eficiência técnica das operadoras de planos de saúde com a utilização da análise envoltória de dados

Esta dissertação tem como objetivo a análise da eficiência técnica das operadoras de planos de saúde vis-à-vis a criação da Agência Nacional de Saúde Suplementar - ANS, no período de 2003 a 2008. Para tanto, foi utilizada a Análise Envoltória de Dados nos dados da saúde suplementar para geração das medidas de eficiência das operadoras, agrupadas em cinco modalidades: autogestão, cooperativa médica, filantropia, medicina de grupo e seguradora. Foram propostas quatro diferentes abordagens que pretenderam visualizar as performances das operadoras nas questões econômico-financeiras e assistenciais, bem como a relação do setor de saúde suplementar com o Sistema Único de Saúde - SUS. Além disso, os dados foram desagregados em grandes regiões brasileiras proporcionando a observação das diferenças regionais. Observou-se que existem grandes diferenças entre modalidades e também entre regiões. A comparação entre as medidas de eficiência nas quatro diferentes abordagens e a evolução, ano a ano, dos normativos da ANS, ainda necessita de uma análise mais detalhada, mas indica, ainda que primariamente, que as modalidades tiveram diferentes reações à regulação.

Know your own state : South Carolina

This publication is a booklet published by the Standard Oil Company that serves as a guide to the state of South Carolina, including history, geography, maps, and automobile care information.