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Artificial Intelligence in the Banking Sector: Development of a Framework for Effective Deployment
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| 1.99 MB | Adobe PDF |
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Resumo(s)
This dissertation addresses the integration of Artificial Intelligence (AI) in the banking sector,
with a particular focus on the development of a structured framework to guide the systematic
adoption of AI technologies, offering systematic guidelines to assist the banking sector in
identifying, evaluating, and effectively implementing AI technologies. The research employs
the Design Science Research methodology, starting with an extensive review of existing
literature on AI applications within the banking industry. Following this, the framework was
built based on these findings and refined through the application of the Strategic Alignment
Model (SAM), ensuring that AI implementations are aligned with the strategic objectives of
banking institutions. Subsequently, a survey was conducted with two industry professionals,
distinguished by their level of expertise, to gather insights and feedback, discussing the
limitations and suggestions for future work, and highlighting areas for further refinement and
enhancement of the framework. Despite its strengths, the volatility of the evolution of AI
technology and the absence of multiple use case demonstrations are among the framework's
limitations. Consequently, future research should focus on extending the framework's
adaptability to different banking environments since it could expand the framework's scope
to cover a wider range of banking services, implement it in a real bank for further refinement,
and explore more use case scenarios to demonstrate its applicability and robustnessin diverse
contexts.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
Palavras-chave
Artificial Intelligence Banking Industry Framework Development Innovation Management Technology Adoption SDG 9 - Industry, innovation and infrastructure