Reúso de dados na era do Big Data: uma jornada rumo a novos paradigmas no setor financeiro

• Ano de defesa: 2019
• Autor(a) principal: Luvizan, Simone da Silva
• Orientador(a): Diniz, Eduardo Henrique
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Reúso de dados; Ecossistemas de inovação
• Palavras-chave em Inglês: Big data; Analytics; Reuse of data; Multilevel framework; Innovation ecosystem
• Link de acesso: https://hdl.handle.net/10438/27294

Data and technology increasing availability, intensified by Big Data (BD), stimulate expectations for more intelligence and value creation using existing information. In this scenario, it’s becoming more frequent the use of data for new purposes, different than the ones they were generated for. This growing practice, called reuse of data, brings great development opportunities, but also implications that were poorly discussed by academy and society as a whole. To collaborate with this debate, this thesis aims to characterize the reuse of data, identify its challenges and propose a model to explain how the actors are dealing with those challenges in practice. The study was concentrated in finance sector and was done in 3 steps, generating 3 papers. The first one performed a bibliographic review to pounder about the existing literatures and also a meta-analysis of data reuse empirical cases. Considering this meta-analysis, it’s proposed a classification schema based on two dimensions: data source (internal, external public or private) and reuse purpose (repurpose or recontextualization). The discussion about potential challenges of different reuse of data categories indicates they are influenced by the distance between data generation and use, suggesting 3 levels of challenges: direct, intermediate and extreme. The second paper proposes a theoretical model to explore reuse of data cases in practice. Inspired on Multilevel Framework (Pozzebon, Diniz & Jayo, 2009), the model catches elements of contextualism (Pettigrew, 1985), SST (Social Shaping of Technology), process approach (Langley, 1999; Pettigrew, 1997) and reuse of data. At this stage, the model was exercised in an exploratory case at Alpha, a company that offer a tool for credit risk analysis based on behavioral profiles generated over mobile network data. The third research phase investigated 3 cases, representing different reuse of data types: a bank (repurposing and recontextualization of internal data – level of challenge direct), a credit bureau (repurposing of public or private external data – level of challenge intermediate) and fintechs (recontextualization of public or private external data – level of challenge extreme). The cases analysis identified the main themes involved on challenges and allow the discussion of their legal, technological, intrinsic, societal and economical dimensions. The cases disclosed that the process by which the actors are dealing with the reuse of data challenges in practice is based on a cyclic dynamic of adjustment/learning and mobilization. Such process is animated by groups that mobilize resources through a possession or practice approach, like also showed in other case study involving complex collaboration. This work contributes to advance the research about reuse of data bringing concepts and relevant questions, especially in IS field. Its methodological and theoretical choices can inspire other researches that share the challenge of exploring complex phenomena.