Data governance frameworks are critical to reducing operational costs and risks in the financial industry. Corporate data managers face challenges when implementing data governance frameworks. The purpose of this multiple case study was to explore the strategies that successful corporate data managers in some banks in the United States used to implement data governance frameworks to reduce operational costs and risks. The participants were 7 corporate data managers from 3 banks in North Carolina and New York. Servant leadership theory provided the conceptual framework for the study. Methodological triangulation involved assessment of nonconfidential bank documentation on the data governance framework, Basel Committee on Banking Supervision's standard 239 compliance documents, and semistructured interview transcripts. Data were analyzed using Yin's 5-step thematic data analysis technique. Five major themes emerged: leadership role in data governance frameworks to reduce risk and cost, data governance strategies and procedures, accuracy and security of data, establishment of a data office, and leadership commitment at the organizational level. The results of the study may lead to positive social change by supporting approaches to help banks maintain reliable and accurate data as well as reduce data breaches and misuse of consumer data. The availability of accurate data may enable corporate bank managers to make informed lending decisions to benefit consumers.

Digital transformation has been a focus of public and private sectors to both improve and sustain business value by leveraging rapidly evolving technology. Digital technology is ubiquitous and inter-connected, changing the face of business, government and society through the creation of new industries, with automation replacing two thirds of existing jobs. The challenge is that most digital transformation efforts fail, mainly due to inadequate leadership and management as well as failure to accept that it is a multi-disciplinary problem. Another challenge is to distinguish between digital transformation (DT) and digitization where the former is based on a customer-centric value proposition and the latter focuses on cost-cutting and operational excellence. This difference also highlights the business/technology divide where the former is mainly DT and the latter is mainly digitization. The challenge addressed in this thesis is how to obtain management acceptance that digital transformation is multi-disciplinary and to make recommendations with respect to how best to achieve DT goals. The research methods followed is a blend of participatory action research (PAR), case study analysis and literature analysis. The principal research findings are that there is no single, management methodology that can increase the chances of DT success but that a modified form of enterprise architecture (EA) that collaboratively interacts with the other management frameworks can likely provide a solid foundation to effectively achieve DT. The thesis consists of an assessment of the current methodologies, four articles that each discuss an area to support effective DT, followed by a request for change (RFC) to up-date the TOGAF 9 EA framework standard. TOGAF was selected due to its pervasive usage globally (80% of Fortune 50 and 60% of Fortune 500). The RFC accommodated both the concepts raised in the articles and other innovations highlighted in the literature review and assessment. The thesis concludes that enterprise architecture is a key business technique that al-lows the sharing of core decision support information across the enterprise, enabling all management frameworks, especially those on the technology-management divide, to collaboratively realize digital transformation.