511 resultados para Fraud offfender


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Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

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The present Work Project (WP) is the result of Sonae’s concern with fraud risk, seeking to implement a method that formally describes and evaluates it in its various forms. In a context of limited human, capital, time and tools’ resources, the Internal Audit (IA) department of the company developed a framework to raise the awareness of top management and identify which processes of its value chain present a higher level of exposure to fraud, with the purpose of redirecting attention to those and prioritizing the creation of new mechanisms to monitor its KPIs’ dynamics.

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Our objective is to analyse fraud as an operational risk for the insurance company. We study the effect of a fraud detection policy on the insurer's results account, quantifying the loss risk from the perspective of claims auditing. From the point of view of operational risk, the study aims to analyse the effect of failing to detect fraudulent claims after investigation. We have chosen VAR as the risk measure with a non-parametric estimation of the loss risk involved in the detection or non-detection of fraudulent claims. The most relevant conclusion is that auditing claims reduces loss risk in the insurance company.

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Fraud is as old as Mankind. There are an enormous number of historical documents which show the interaction between truth and untruth; therefore it is not really surprising that the prevalence of publication discrepancies is increasing. More surprising is that new cases especially in the medical field generate such a huge astonishment. In financial mathematics a statistical tool for detection of fraud is known which uses the knowledge of Newcomb and Benford regarding the distribution of natural numbers. This distribution is not equal and lower numbers are more likely to be detected compared to higher ones. In this investigation all numbers contained in the blinded abstracts of the 2009 annual meeting of the Swiss Society of Anesthesia and Resuscitation (SGAR) were recorded and analyzed regarding the distribution. A manipulated abstract was also included in the investigation. The χ(2)-test was used to determine statistical differences between expected and observed counts of numbers. There was also a faked abstract integrated in the investigation. A p<0.05 was considered significant. The distribution of the 1,800 numbers in the 77 submitted abstracts followed Benford's law. The manipulated abstract was detected by statistical means (difference in expected versus observed p<0.05). Statistics cannot prove whether the content is true or not but can give some serious hints to look into the details in such conspicuous material. These are the first results of a test for the distribution of numbers presented in medical research.

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The Public Health Agency is required by law to protect the public funds it administers. This A4 sheet provides information on the National Fraud Initiative.

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The Public Health Agency (PHA) is required by law to protect the public funds it administers. This A4 sheet provides information on the National Fraud Initiative.