2,011 research outputs found

    Corporate Ethical Training: An Answer to White-Collar Crimes

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    The modern business corporation is a culturally significant component of American Society. It is facing a cultural invasion of the highest order. The categorical imperative, an unconditional principle that rational individuals must follow despite natural desires or inclinations to do otherwise, is today being called into question. This is most likely the result of grounding moral values upon information that is transient and unstable rather than upon established data. The social contract, which governs the formation and maintenance of individual morals, is a requirement in organizations that demands collective agency – employees acting together to set forth moral rules of behavior and eschew pernicious leanings and tendencies. From that perspective, ethical training becomes a key leveraging point in the disconnect between cultural expectations and individual behaviors in corporate America

    A semantic rule based digital fraud detection

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    Digital fraud has immensely affected ordinary consumers and the finance industry. Our dependence on internet banking has made digital fraud a substantial problem. Financial institutions across the globe are trying to improve their digital fraud detection and deterrence capabilities. Fraud detection is a reactive process, and it usually incurs a cost to save the system from an ongoing malicious activity. Fraud deterrence is the capability of a system to withstand any fraudulent attempts. Fraud deterrence is a challenging task and researchers across the globe are proposing new solutions to improve deterrence capabilities. In this work, we focus on the very important problem of fraud deterrence. Our proposed work uses an Intimation Rule Based (IRB) alert generation algorithm. These IRB alerts are classified based on severity levels. Our proposed solution uses a richer domain knowledge base and rule-based reasoning. In this work, we propose an ontology-based financial fraud detection and deterrence model

    Нові тенденції розвитку термінознавства : здобутки міжнародної наукової групи Р. Теммерман

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    Комплексно проаналізовано здобутки міжнародної наукової групи під керівництвом Р. Теммерман: розглянуто основні положення соціокогнітивного термінознавства, питання сутності терміна, фахової мови, фахової комунікації, динаміки терміна, розуміння терміна людиною за різних умов фахового спілкування, оперування великими масивами термінологічних даних, терміноонтографії й терміноонтології, інженерії знань та галузевих онтологій.The paper comprehensively analyses the achievements of the international research group led by R. Temmerman: it examines the main thesis of sociocognitive terminology, questions of the essence of a term, professional language, professional communication, dynamics of a term, understanding of a term by person under various conditions of professional communication, handling large corpora of terminological data, terminoontography and terminoontology, knowledge engineering and specialized ontologies

    The Generic Ecosystem and Innovation Patterns of the Digital Transformation in the Financial Industry

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    The emergence of financial technology companies (Fintechs) through the easy access of digital technologies is transforming the entire financial industry, heralding a new era of business models. With digital technologies like mobile payments, robo advisors, and distributed ledgers or blockchain, Fintechs are challenging the prevailing position of traditional financial institutions. However, literature does not provide a structured overview of the digital transformation in the financial industry, including inter- organizational innovation patterns. By analyzing 792 Fintechs, this paper visualizes the 22 generic roles and value streams within the financial ecosystem using the e3- value method. Moreover, we identify and discuss seven inter-organizational innovation patterns of the digital transformation in the financial industry. We contribute to literature by examining digital transformation in the financial industry from an inter- organizational perspective. Practitioners may apply the model to position themselves and to identify disruptive actors or potential business opportunities. We also analyze the influence of blockchain technology

    Extraction of ontology and semantic web information from online business reports

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    CAINES, Content Analysis and INformation Extraction System, employs an information extraction (IE) methodology to extract unstructured text from the Web. It can create an ontology and a Semantic Web. This research is different from traditional IE systems in that CAINES examines the syntactic and semantic relationships within unstructured text of online business reports. Using CAINES provides more relevant results than manual searching or standard keyword searching. Over most extraction systems, CAINES extensively uses information extraction from natural language, Key Words in Context (KWIC), and semantic analysis. A total of 21 online business reports, averaging about 100 pages long, were used in this study. Based on financial expert opinions, extraction rules were created to extract information, an ontology, and a Semantic Web of data from financial reports. Using CAINES, one can extract information about global and domestic market conditions, market condition impacts, and information about the business outlook. A Semantic Web was created from Merrill Lynch reports, 107,533 rows of data, and displays information regarding mergers, acquisitions, and business segment news between 2007 and 2009. User testing of CAINES resulted in recall of 85.91%, precision of 87.16%, and an F-measure of 86.46%. Speed with CAINES was also greater than manually extracting information. Users agree that CAINES quickly and easily extracts unstructured information from financial reports on the EDGAR database

    Decision Support Systems for Financial Market Surveillance

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    Entscheidungsunterstützungssysteme in der Finanzwirtschaft sind nicht nur für die Wis-senschaft, sondern auch für die Praxis von großem Interesse. Um die Finanzmarktüber-wachung zu gewährleisten, sehen sich die Finanzaufsichtsbehörden auf der einen Seite, mit der steigenden Anzahl von onlineverfügbaren Informationen, wie z.B. den Finanz-Blogs und -Nachrichten konfrontiert. Auf der anderen Seite stellen schnell aufkommen-de Trends, wie z.B. die stetig wachsende Menge an online verfügbaren Daten sowie die Entwicklung von Data-Mining-Methoden, Herausforderungen für die Wissenschaft dar. Entscheidungsunterstützungssysteme in der Finanzwirtschaft bieten die Möglichkeit rechtzeitig relevante Informationen für Finanzaufsichtsbehörden und Compliance-Beauftragte von Finanzinstituten zur Verfügung zu stellen. In dieser Arbeit werden IT-Artefakte vorgestellt, welche die Entscheidungsfindung der Finanzmarktüberwachung unterstützen. Darüber hinaus wird eine erklärende Designtheorie vorgestellt, welche die Anforderungen der Regulierungsbehörden und der Compliance-Beauftragten in Finan-zinstituten aufgreift
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