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Access to knowledge resources

  • Basic Search

    You can do a basic search for a topic using the ‘Search Documents’ field to the right. Use AND to narrow down your search.

    Radar reports from 2001 and 2006 are provided as a free sample, along with selected reports from 2011. Register for a visitor password.

    Visitors can search the Radar database to test its scope, but only subscribers to this service can obtain the reports in full.

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Recent Articles

Proof of principle – epidemiology based modelling for liability exposure

Dec 18, 2018
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Vibration White Finger A modelling case study An epidemiology-based approach to liability ENID modelling has been developed and applied[1]. While based on the same concepts, in practice each scenario-specific ENID model is mathematically unique. This note describes the approach using the example of vibration white finger (VWF[2]). The results agree, within tolerance, with official data.   Brief background Long term exposure to high intensity vibrations leads to a predisposition to episodes of finger blanching. In severe cases there is loss of dexterity. Cause and severity of VWF are both cumulative in nature. A typical presentation is illustrated below: The cause of these symptoms is an autonomic[3] constriction of the blood vessels supplying parts of the hands[4]. Episodes of finger blanching may be provoked by vibration, cold weather and wetting with water. A similar effect is seen in Raynaud’s’ phenomenon (RP) which is of constitutional origin. This initially gave rise to uncer
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processed meat and liability for cancer

Nov 30, 2018
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Processed meat and colorectal cancer claims – Yes, No, How Big? Summary It has been proposed that processed meat consumption causes colorectal cancer. Since there have been no UK insurance claims for this, and the proposal has not been put to proof at common law, it is described as a potential liability ENID[1], or, emerging liability risk. The background is briefly described below. As part of the necessary[2] evaluation response, a software model of the potential UK personal injury liability exposure has been developed. The model allows the user to test various technical and legal “what ifs” and to perform sensitivity analyses. A generic causation assessment tool is included in the software and is based on UK legal precedents. The normal medical response to colorectal cancer includes surgery. Such surgery entails a risk of serious infection and the consequential need for antibiotics. Given the increased rates of antimicrobial resistance (AMR) some bowel surgery cases will die as a res
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De minimis – a practical step towards objectivity

Nov 06, 2018
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De minimis – a practical step In a nut shell I propose that the explicit recognition of a two stage test of de minimis may lead to clarity of fact finding in difficult cases such as marginal noise induced hearing loss, and minor neck sprain. Further, by focusing on the first stage test, the significance of marginal exposures to risk can be resolved objectively. The conventional two-stage test The concept of de minimis is fairly straightforward to assess in cases of broken limbs, burns and other ‘impact’ events. Indeed it is so straightforward that the assessor and opposing parties may not make explicit that they are using a two stage test. In general when assessing injury: The first stage is to assess whether the state of the claimant after the event was/is ‘probably different’ to their state immediately prior to the event. Has anything changed? ‘Probably different’, is properly assessed on the balance of probabilities. If yes, the second stage is to assess whether the difference is su
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Artificial intelligence – a problem for liability insurance

Sep 14, 2018
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Artificial intelligence and liability insurance. After a brief introduction to AI, some of the liability issues are introduced in this brief report. AI simulations Essentially AI systems are structured in the following way. The computer is supplied with digital information, coded with a set of statistical tools and a set of purposes that the customer would like to work with. Once data, methods and purposes are properly coded, the AI generates useful simulations of the data and can be used to identify the degree to which new situations meet the set of purposes. Missing data is effectively imputed from the overall model. As a very much simplified example. An example helps set the scene for the discussion of legal liability. Intended purpose: A liability claims manager wants to identify claims which are suited to making an immediate offer, and those which are best examined more closely. Process: Having coded ten thousand claims of the relevant sort, AI generates a statistically weighted s
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Can mobile phone radiation cause cancer?

Aug 29, 2018
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Does mobile phone radiation cause cancer? Principle findings Following detailed lab experiments, researchers at the US National Toxicity Program (NTP[1]) have published[2] data which provides evidence of a statistically significant association between high exposure to radio frequency emfs (RF emfs) and malignant schwannoma of the heart in male rats. The evidence revealed thus far is consistent with a causal explanation. Extrapolating to human disease is however unclear; as this depends on the mechanism behind this association. It is hoped that in the final report, NTP will be as specific about this mechanism as they can be. As it is, there are signs in the data that the mechanism may be unusual, so much so that a new challenge could be made to the norms of cancer compensation. The final NTP report is due before the winter of 2018. As a draft for peer review, the NTP report may not be quoted. A challenge to the norms of cancer compensation The courts, and therefore insurers, nearly alwa
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Managing Liability ENIDS using the Radar Service

Aug 11, 2018
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  Managing liability ENIDs using Radar Radar The Radar service provides an expert view of science-based changes to liability insurance exposure and provides quantitative estimates of that exposure. Some examples from the Radar database are appended here: American football and brain disease, LED lights and eye injury, wood dust and nasal cancer and, 3D printing. History The Radar service was first developed under contract to ABI[1] as a collective work on emerging liability risks. Radar was then commercialised by Re: Liability (Oxford) Ltd[2]. As ABI evolved, the service was passed to liability insurers to take up individually. Liability emerging risks are now more often referred to as liability ENIDs[3], for example in Solvency II guidance. Aim The aim is to inform judgement of factors that could drive changes to liability insurance exposure and to estimate the resulting size of that change. Method This follows the familiar method of identify, evaluate and take action. Identificat
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