Function Extraction Based on CFPS and Digital Financial Index: Data Mining Techniques for Prognosis of Operational Risks of Financial Institutions

Abstract

Financial deregulation, financial globalization, and the increasing variety and technological sophistication of the commodities offered by financial services have made the operations of financial institutions more complex. Compared with credit risk and market risk, financial institutions’ transaction risk management plays an increasingly important role in financial practice. As an emerging technology, big data mining technology has a unique advantage in optimizing the processing and management of large amounts of data. Big data mining technology not only has the common functions of finding, comprehensively managing all kinds of information, collecting and analyzing data, and conducting statistics but also should have the ability to process information that is hidden and useful in the database through data mining technology. Based on CFPS and data mining technology, this paper analyzes the operational risk of financial institutions, analyzes the causes of the operational risk of financial institutions, discusses the measures to avoid the operational risk of financial institutions, and draws corresponding conclusions.