Predictors of Fraudulent Monday Effect Workers Compensation Claims Filing

Monday Effect Claims refer to workers compensation claims filed on Mondays for easy to conceal injuries such as strains, sprains, and back injuries. Researchers and industry experts have long believed that there is an element of fraud in these claims, resulting from individuals who were injured during the weekend, while not at work, looking to take advantage of the medical benefits available through workers compensation insurance. Fraudulent Monday Effect Claims (FMEC), as presented in this study, specifically refer to workers compensation claims filed for injuries that occurred while an individual was not at work, presumably during the weekend. A study of 507 adult survey participants examines how injury type, level of financial exposure, as determined by medical and accident insurance coverage status, along with an individual’s job satisfaction level and acceptance of fraud, can predict the extent to which an individual would be likely to file a Fraudulent Monday Effect Claim (FMEC). The findings of this research indicate that while injury type and level of fraud acceptance may predict the likelihood of a Fraudulent Monday Effect Claim filing, financial exposure and job satisfaction may not

FIGHTING FINANCIAL CRIME IN THE DIGITAL AGE With special regard to cyber-enabled money laundering

In order to effectively combat money laundering and terrorist financing carried out by means of cryptocurrencies and cryptoassets, certain conditions must be met. First, there must be a sufficient and appropriate regulatory framework within which the necessary counter measures can be taken. Several examples show that this legal framework is not only formed by national and supranational state bodies, but also by rules created in the private sector through self-regulation. Both regulatory systems are equally limited in their mechanisms of action by data protection law. Money laundering manipulations predominantly, if not as a rule, involve data of the persons concerned, and counter-measures will consequently also have to take these data into account. The question of how to resolve this conflict between the interest of the business sector and society in combating a specific form of financial crime and the interest in protecting individual privacy is, as illustrated by a few examples, being addressed not only by state and private regulators but also by the courts. On the other hand, it should be noted that legally relevant rules must and can be applied regardless of their character. Despite the existing relatively extensive legal framework, users sometimes have problems from a practical point of view in fulfilling the obligations imposed on them. This concerns financial service providers who need concrete assistance, especially in the context of risk management. It is therefore recommended that this should be offered to them on various points by their trade associations through self-regulation. Especially in the case of non-transparent cyber-enabled criminal processes, the appropriate organisational structures and technical possibilities must be available to identify them as violations of the law. Only when the criminal structures, i.e. the technical ossibilities for abuse and the currently practiced manipulations, are known, can crimes be countered preventively and with repressive means. This concerns not only the financial institutions, but also the administrative or law enforcement authorities and the courts, where often a lack of expertise can be identified. This aspect is not only dealt with in part of this paper, but also in detail in the larger part of the publications compiled in the last section

Process Mining Workshops

This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 28 papers included in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops: 2nd International Workshop on Event Data and Behavioral Analytics (EDBA) 2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy, and Security in Process Analytics (TPSA) One survey paper on the results of the XES 2.0 Workshop is included

Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers’ compensation fraud

The development of new data analytical methods remains a crucial factor in the combat against insurance fraud. Methods rooted in the research field of anomaly detection are considered as promising candidates for this purpose. Commonly, a fraud data set contains both numeric and nominal attributes, where, due to the ease of expressiveness, the latter often encodes valuable expert knowledge. For this reason, an anomaly detection method should be able to handle a mixture of different data types, returning an anomaly score meaningful in the context of the business application. We propose the iForestCAD approach that computes conditional anomaly scores, useful for fraud detection. More specifically, anomaly detection is performed conditionally on well-defined data partitions that are created on the basis of selected numeric attributes and distinct combinations of values of selected nominal attributes. In this way, the resulting anomaly scores are computed with respect to a reference group of interest, thus representing a meaningful score for domain experts. Given that anomaly detection is performed conditionally, this approach allows detecting anomalies that would otherwise remain undiscovered in unconditional anomaly detection. Moreover, we present a case study in which we demonstrate the usefulness of our proposed approach on real-world workers’ compensation claims received from a large European insurance organization. As a result, the iForestCAD approach is greatly accepted by domain experts for its effective detection of fraudulent claims.</p

CPA\u27s handbook of fraud and commercial crime prevention

https://egrove.olemiss.edu/aicpa_guides/1823/thumbnail.jp

Process Mining Workshops

This open access book constitutes revised selected papers from the International Workshops held at the Third International Conference on Process Mining, ICPM 2021, which took place in Eindhoven, The Netherlands, during October 31–November 4, 2021. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 28 papers included in this volume were carefully reviewed and selected from 65 submissions. They stem from the following workshops: 2nd International Workshop on Event Data and Behavioral Analytics (EDBA) 2nd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 2nd International Workshop on Streaming Analytics for Process Mining (SA4PM) 6th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 4th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 2nd International Workshop on Trust, Privacy, and Security in Process Analytics (TPSA) One survey paper on the results of the XES 2.0 Workshop is included

Cyber defensive capacity and capability::A perspective from the financial sector of a small state

This thesis explores ways in which the financial sectors of small states are able todefend themselves against ever-growing cyber threats, as well as ways these states can improve their cyber defense capability in order to withstand current andfuture attacks. To date, the context of small states in general is understudied. This study presents the challenges faced by financial sectors in small states with regard to withstanding cyberattacks. This study applies a mixed method approach through the use of various surveys, brainstorming sessions with financial sector focus groups, interviews with critical infrastructure stakeholders, a literature review, a comparative analysis of secondary data and a theoretical narrative review. The findings suggest that, for the Aruban financial sector, compliance is important, as with minimal drivers, precautionary behavior is significant. Countermeasures of formal, informal, and technical controls need to be in place. This study indicates the view that defending a small state such as Aruba is challenging, yet enough economic indicators indicate it not being outside the realm of possibility. On a theoretical level, this thesis proposes a conceptual “whole-of-cyber” model inspired by military science and the VSM (Viable Systems Model). The concept of fighting power components and governance S4 function form cyber defensive capacity’s shield and capability. The “whole-of-cyber” approach may be a good way to compensate for the lack of resources of small states. Collaboration may be an only out, as the fastest-growing need will be for advanced IT skillsets

The medicalization of deviance in China

亞洲犯罪學學會Conference Theme: Asian Innovations in Criminology and Criminal JusticePart 5: Juvenile Delinquency and JusticeConrad and Schneider’s now classical work on the historical transformation of definitions of deviance from “badness” to “sickness” is relevant for the situation in China today, although with some modifications. The weakly founded medical/psychiatric profession and the strong political/ideological discourse in China leads to a strange combination of medicalization and moralization, even criminalization of deviance. The “sick” is often combined with the “bad”, and “sickness” is often seen as a secondary sign of “badness”. The pan-moralist tradition of ancient China seems to be closely combined with the Communist era’s strong belief in political-ideological correctness, and its strong belief in social engineering. It is interesting to note that my research on crime and deviance in China in the 1980s and 1990s seems to be confirmed by today’s discourse, although there are new moral panics and new forms of medical-moralistic definitions of deviance in China today. Still, the categories of deviance are very much socially constructed entities closely related to the moral-political order of present day China. I will use three cases to underline my argument. First, the type of deviance I call “majority deviance”, related to the case of the prejudice and dangers associated with the only-child. My second example has to do with what I term the “wayward girl” and the moral panics concerning so-called zaolian – or “premature love” among young girls. The third example is the new panic surrounding “internet addiction disorder” or IAD. While the “disco” and the “dance hall” were the sites of disorder in the 1980s and 90s, the wangba – or “internet bar” is now seen as the most dangerous site of crime and deviance.postprin