Tackling Insurance Fraud: Law and Practice
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Notice bibliographique
Résumé
Tackling Insurance Fraud: Law and Practice, by Dexter Morse and Lynne Skajaa, Informa Professional, London, UK. This volume bills itself as one of a series of Practical Insurance Guides, along with others such as Insurance Disputes, Good Faith and Insurance, and Marine Insurance all with an emphasis on law. Informa Professional is the publisher of a London insurance daily Insurance Day and a purveyor of conferences (Reinsurance Summit 2006), training courses (none listed yet), and distance learning (masters degrees in various law fields, such as EU law, food law and employment law, and with various universities) as shown on their Website (www.informalaw.com). Informa's interests appear to be principally legal (247 products, 27 in insurance and banking, and 73 in maritime law). This volume fits into the insurance and banking law category. The authors are both accomplished lawyers in the UK, Dexter Morse with a reinsurer and Lynne Skajaa with several law firms dealing with maritime issues and with the University of Southampton. As you would suspect the book deals with insurance fraud with a decidedly legalistic point of view. Although the fraud coverage is primarily from a UK perspective, the authors present some universal concepts such as What is insurance fraud? and Who is the typical fraudster? and contrast the UK experience with the United States, Canada, Australia, New Zealand, South Africa, and European efforts in some 34 of the book's 158 pages. You will not find theoretical models of behavior, with underlying subjective probabilistic models of outcomes favorable to the fraudsters, but you will find a discussion of both the problem of insurance fraud and details about the means of detection, deterrence, and prosecution, all in a readable and well sequenced set of chapters. Chapter 1 begins by exposing a worldwide problem for combating insurance fraud found also in the UK, namely, the absence of specific statutes that deal explicitly with insurance fraud. The authors cite relevant sections of the Theft Act of 1968, and subsequent case law that cover deception and dishonesty in obtaining property (claim settlement), in gaining a pecuniary advantage (policy coverage) and in falsifying accounts (large scale fraud). The Theft Act, updated in 1996 to include banking but not insurance transactions, provides the analogs to the use in the United States of larceny and mail fraud statutes to prosecute insurance fraud prior to recent state-by-state adoption of laws, some by line of insurance, specifying penalties for insurance fraud per se. case law and the Perjury Act of 1911 are also cited for their usefulness in rounding out the legal environment in the UK. Typical fraudsters are categorized in Chapter 2 into three categories: The average insured succumbing to what we call opportunistic the full or part-time criminal, and organized gangs, all motivated by greed, financial difficulty, or a sense of recovering premiums not paid out in claims. There does not seem to be a category that covers professional providers such as doctors and lawyers who facilitate fraud in the guise of legitimate claims2 or a category for those who create phony insurers or loot existing companies of their assets. Thus the focus of the book is the retail aspect of application and claim fraud. Chapter 3 reviews so-called fraud indicators, those yes-no objective and subjective statements about the circumstances surrounding the filing of a claim such as 'The insured is very knowledgeable about insurance terms and claims procedures. Such indicators may be specific to line of business, especially property or motor lines.3 Chapter 4 confronts the problem of separating criminal fraud from civil fraud, the latter being unethical practices, at least in someone's eyes, known colloquially as soft fraud. The authors properly view the distinction in terms of contract law and resolution of contract disputes. Chapters 5 and 6 apply the general legal analysis to their specific interests in marine and reinsurance lines of insurance. …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle