2023
DOI: 10.1155/2023/6531154
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Research on Supply Chain Financial Risk Prevention Based on Machine Learning

Abstract: Artificial intelligence (AI) proves decisive in today’s rapidly developing society and is a motive force for the evolution of financial technology. As a subdivision of artificial intelligence research, machine learning (ML) algorithm is extensively used in all aspects of the daily operation and development of the supply chain. Using data mining, deductive reasoning, and other characteristics of machine learning algorithms can effectively help decision-makers of enterprises to make more scientific and reasonabl… Show more

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Cited by 14 publications
(6 citation statements)
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“…The future trends in supply chain optimization also encompass the application of machine learning for supply chain financial risk prevention (Lei et al, 2023;Lukong et al, 2022). This involves the systematic review and analysis of the necessity and urgency of applying AI technology to identify financial difficulties in supply chains.…”
Section: Future Trends and Developmentsmentioning
confidence: 99%

Reviewing the use of big data in supply chain optimization in the USA

Israel Osejie Okoduwa,
Bankole Ibrahim Ashiwaju,
Jeremiah Olawumi Arowoogun
et al. 2024
World J. Adv. Res. Rev.
“…The future trends in supply chain optimization also encompass the application of machine learning for supply chain financial risk prevention (Lei et al, 2023;Lukong et al, 2022). This involves the systematic review and analysis of the necessity and urgency of applying AI technology to identify financial difficulties in supply chains.…”
Section: Future Trends and Developmentsmentioning
confidence: 99%

Reviewing the use of big data in supply chain optimization in the USA

Israel Osejie Okoduwa,
Bankole Ibrahim Ashiwaju,
Jeremiah Olawumi Arowoogun
et al. 2024
World J. Adv. Res. Rev.
“…This includes the use of complex passwords and multi-factor authentication, regular monitoring of account activity, and security awareness training for employees. At the same time, regulators and fintech companies are developing more sophisticated tools and algorithms that use machine learning and artificial techniques to identify and prevent fraud [7]. Nonetheless, fraudsters continue to evolve their tactics, and the detection and prevention of financial transaction fraud remains an ongoing struggle that requires the concerted efforts and cooperation of society as a whole.…”
Section: Types and Characteristics Of Financial Transaction Fraudmentioning
confidence: 99%
“…To compensate for the defects of a single model, Zhu et al [27] proposed a new integrated machine-learning method to construct an integrated model of random subspace-real AdaBoost to predict the credit risk of SMEs, which was applied to analysis and prediction of multisource data. Under the framework of an integrated learning model, Lei et al [8] constructed the chaotic grasshopper optimization algorithm to extract the financial features of enterprises through the complex data-preprocessing process, then used SVM to classify the data, and finally optimized it using the sticky mushroom algorithm to construct the SCF risk precautionary system. Table 1 presents a comparison of the models, accuracy, and sample sizes proposed by some scholars.…”
Section: Review Of Scf Risk Controlmentioning
confidence: 99%