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Título: Connecting technology and professionals in digital fraud management from a computer science perspective
Autor(es): GOMES, Renata Faria
Palavras-chave: Fraud management; Cybersecurity; Computer science; Risk management; Digital fraud
Data do documento: 18-Ago-2025
Editor: Universidade Federal de Pernambuco
Citação: GOMES, Renata Faria. Connecting technology and professionals in digital fraud management from a computer science perspective. 2025. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Pernambuco, Recife, 2025.
Abstract: The escalating sophistication and volume of digital fraud demand robust, adaptive man agement. While academic insights exist on detection and tools, a persistent gap remains in comprehensively connecting these technologies with professionals and their practical contexts. Purpose–Thisdissertationaddressesthisgapbyexaminingfraudmanagementfromacom puter science perspective, focusing on software tools, relevant knowledge, and computing expertise. It seeks to answer key questions regarding current tool use and challenges, essential computer science knowledge and its application, and professionals’ perception of collaboration with computing experts. Methodology–Thestudyemploysamixed-methodsapproach, in tegrating a literature review, a software benchmark, and qualitative surveys conducted with Brazilian fraud professionals. Findings–Our findings indicate that technology is essential and multifunctional across all fraud management stages (deterrence to prosecution), but its e!ectiveness is often hindered by human factors, usability issues, and systemic fragmentation. Traditional frameworks struggle to capture real-world operational fluidity, and professionals encounter challenges like technical language barriers, limited integration, and bureaucratic ine"ciencies, particularly in the public sector. Recommendations–Toaddress these, the study advocates for integrated fraud resilience frameworks, improved technical communication to bridge human-technology gaps, legislative modernization for agile law enforcement, and responsible navigation of AI’s ethical and security.
URI: https://repositorio.ufpe.br/handle/123456789/67099
Aparece nas coleções:Dissertações de Mestrado - Ciência da Computação

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