Research on Financial Risk Prevention and Control Methods based on Big Data
AUTHORS
Sami Mohammed,Department of Computer Science, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia V8W 3P6, Canada
ABSTRACT
Facing the complex and severe risk prevention and control situation, the financial industry is stepping up the formulation of relevant technical standards. To effectively ensure the application of technical standards, this article takes the prominent problems of traditional risk prevention and control systems such as data islands, computing power limitations, and long model iteration cycles as the entry point. Based on emerging technologies such as machine learning, a new design scheme for a smart risk prevention and control platform based on big data is proposed. The platform adopts the design concept of "large and medium platform", and adopts the overall framework and implementation method of "five layers and two domains". The closed-loop of risk prevention and control gives full play to the value of risk prevention and control of financial big data; secondly, the coupling between the layers is low, the dependence is small, and the applications in the layers use distributed architecture, which makes horizontal expansion convenient; at the same time, deployment from production, The two dimensions of business operation have carried out specific implementation and combined application of related functional modules, which maximizes the stability of system operation and the flexibility of business applications. The design scheme and implementation method proposed in this paper can better meet the risk prevention and control needs of commercial banks, thereby supporting the business transformation and high-quality development of commercial banks in the digital economy era.
KEYWORDS
Financial risk, Big data, Risk prevention, Commercial banks
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