Pisoni, Galena ORCID: https://orcid.org/0000-0002-3266-1773, Molnár, Bálint and Tarcsi, Ádám (2023) Knowledge Management and Data Analysis Techniques for Data-Driven Financial Companies. Journal of the Knowledge Economy, 15 (3). pp. 13374-13393.

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Abstract

In today’s fast-paced financial industry, knowledge management and data-driven decision making have become essential for the success of financial technology (FinTech) companies. Big data (BD) is a prevalent phenomenon that can be found across many industries, including finance. Despite its complexity and difficulty to comprehend, big data is a critical component of financial services enterprises and technology architectures. We examine BD from various aspects, considering data science (DS) techniques and methodologies that can be applied during the operation of an enterprise. Our aim is to provide an overview of knowledge management (KM) practices and data analysis (DA) strategies and techniques in the daily operations of financial companies. We address the role of knowledge management, data analytics in a financial institution. The paper demonstrates financial institutions’ enablement for new services resulting from technological advancements.

Item Type:	Article
Status:	Published
DOI:	10.1007/s13132-023-01607-z
School/Department:	York Business School
URI:	https://ray.yorksj.ac.uk/id/eprint/9088

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