Construction of Mobile Internet Financial Risk Cautioning Framework Based on BP Neural Network

Abstract

With the emergence of the 21st-century global economy, the international financial system faces economic risks. A competitive cautioning model for financial management is required to mitigate risks and losses in the financial sector. The financial losses of the banking industry have been categorized and analyzed using the Internet of Things (IoT) and big data technologies to minimize the economic risk of commercial banks in mobile internet finance (MIF). This article proposes a new financial risk cautioning framework (FRCF) based on the IoT, big data, and back propagation-neural network (BP-NN) to ensure steady growth of MIF in the long term. In this article, a big data technology-based approach for data recognition and mining has been suggested. A BP-NN-based method for risk identification and assessment in MIF is also presented. The BP-NN technique calculates each neural network (NN) layer’s node count, transfer functions, learning rate, and other characteristics. The proposed FRCF has been developed through the proper construction, analysis, and testing of many information samples. A conceptual understanding of the use of IoT, big data, and artificial intelligence (AI) technologies through NN models in the financial industry has been described in the article. The proposed FRCF can predict the MIF risks associated with the MIF lending infrastructure with a 98.2% accuracy.

Machine learning in internet financial risk management: A systematic literature review

“…As shown in Table 2 , this section presents the annual regional distribution of all the references in this paper. It’s quite evident that out of the 17 documents, 11 of them are based on Chinese Internet financial data [ 14 , 27 ]. Chinese scholars or researchers using Chinese data for machine learning algorithms in Internet financial risk analysis stand out as the driving force behind research on this topic.…”

“…Although Internet financial is an emerging financial service model, it has not altered the fundamental nature of financial services. Risk prevention remains a crucial and central aspect [ 27 , 28 ]. Consequently, Chinese scholars and professionals in the financial industry have shown a great deal of concern about Internet financial risk.…”

“…A total of 14 documents fall into this category. The other category of literature centers on designing or innovating Internet financial risk systems, applying relevant data to construct appropriate risk identification or risk prediction systems [ 27 , 28 , 36 ]. Although these two categories of literature emphasize slightly different core points, their ultimate goals are risk reduction and enhancing operational stability.…”

“…The application of this approach to internet financial risk warning and risk management research began as early as 2019 [ 15 ], gradually gaining momentum alongside technological development [ 11 , 19 , 25 ]. The primary focus of these studies lies in the selection of model methodologies [ 17 , 20 , 26 ] and the construction of risk systems [ 1 , 27 , 28 ]. However, to date, there has been no comprehensive review article or study systematically outlining the state of this emerging yet critical research field.…”

“…Using a systematic literature review approach, a comprehensive analysis of relevant literature in this field is conducted. Currently, there are only a limited number of articles on this topic [ 11 , 25 , 27 ], and our study addresses the following three main questions through analysis, clarifying the current state of research advancement and literature gaps in this field, as well as the differences between various internet financial risk identification and warning methods.…”