Insurance Policy issued to William Woodruff

Insurance Policy issued by the Columbus Insurance Company of Columbus, Ohio to William Woodruff of St. Davids, Ontario on a detached brick building situated on Lot no. 6 on St. Paul Street, St. Catharines. This is fire policy no. 113, book 1, folio 112, April 11, 1884.

Cogswell, Maria, includes: Application for loan on Real Estate, Insurance Policy, Mortgage Loan Envelope

Cogswell, Maria, includes: Application for loan on Real Estate, Feb. 20, 1882; Insurance Policy no. 2199780 from the Royal Insurance Company of Liverpool, March 17, 1887 and Mortgage Loan Envelope for mortgage no. 1535 from March 1, 1882 – March 1, 1887.

Eventuales manifestaciones del abuso de la posición dominante en el amparo de infidelidad de la póliza global bancaria

En este trabajo se estudian las generalidades del contrato de seguro, las cláusulas abusivas en el contrato de adhesión y particularmente el Amparo de Infidelidad de la Póliza Global Bancaria con el objeto de establecer la posibilidad de que en dicho amparo se presenten conductas abusivas.

The Goss-Udderzook tragedy : being a history of a strange case of deception and murder, including the great life insurance case, and the trial of William E. Udderzook for the murder of W. S. Goss.

Spine title: Trial of Udderzook.

Health physics insurance seminar /

"Report on Health Physics Seminar for Insurance Company Representatives held Feb. 6-10, 1950"--Title page verso.

Pioneers in protection ; the story of a century of fire insurance service, 1853-1953.

Mode of access: Internet.

Manual of group life insurance; rules, regulations and premium rates.

Mode of access: Internet.

Workmen's compensation insurance, State of New York ... : four plans of insurance : 1. State fund, 2. Mutual association, 3. Self-insurance, 4. Stock insurance ... /

Mode of access: Internet.

Ætna guide to fire insurance for the representatives of the Ætna Insurance Co., Hartford, Conn. ... Branch, Cincinnati ...

Mode of access: Internet.

The Story of Standard Insurance in the West.

Cover title.

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.