Big data analytics

: an implementation framework for the portuguese financial sector

Abstract

In light of the growing need for data-driven decision-making, this study explores how financial institutions in Portugal can effectively adopt Big Data Analytics (BDA) by developing a structured and actionable framework that addresses the specific challenges and dynamics of the sector. Building upon existing literature on BDA, Dynamic Capabilities (DC), and Technology Acceptance Models (TAM), this research aims to bridge the gap between theory and practice via an integrated model tailored to the Portuguese financial context. Using a qualitative approach grounded in action research, this research proposes an Adaptive Data Insights Framework (ADIF) for the implementation of BDA in the financial sector, based on a combination of academic insights and contributions from an experienced industry expert. The ADIF addresses obstacles such as cultural resistance, lack of digital literacy, outdated infrastructures, and regulatory complexities, offering a structured approach that promotes alignment between analytics initiatives and organizational goals, while also encouraging greater user adoption and strategic adaptability. This dissertation contributes to the field of management by delivering a practical tool that managers can leverage when evaluating and planning BDA initiatives. It also sets a foundation for future empirical research, with potential applications in real-world case studies and broader organizational contexts. In doing so, it provides both academics and practitioners with a grounded and timely contribution to the advancement of data-driven strategies in the financial sector.

Date of Award	7 Jul 2025
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Maria Alice Moreira Trindade (Supervisor)