The effect of artificial intelligence algorithm onrisk of international business supply chain services

As the process of global economic integration deepens, financial services in the supply chain ofinternational trade have also flourished. International business supply chain financial services haveplayed an important role in solving supply chain organizational financing. As far as the energy industryis concerned, international trade supply chain finance services can provide sufficient credit support forenergy companies. This will solve the financing problem of small and medium-sized energy companiesin import and export business, and it can also improve the capital turnover rate of large energycompanies. However, since international trade supply chain financial services still face the impact ofrisks such as company credit risk, bank operational risk, and supply chain company informationtransmission risk, its performance in financing has not been fully applied. Early warning and control ofrisks in international trade supply chain financial services can play the role of international trade supplychain financial services in promoting the development of the energy industry. Therefore, this paper usedthree artificial intelligence (AI) algorithms including artificial neural network, genetic algorithm andparticle swarm algorithm to analyze the risk of financial services in the international trade supply chainof the energy industry. An early warning model of risk was built on the financial services supply chainof international trade of the energy industry, and an empirical study was conducted on the early warningmodel of risk. The research showed that the early warning model of risk based on artificial intelligencealgorithm enables banks to improve the accuracy of credit assessment of companies by ۷.۴۳% and theaccuracy of information collection by ۵.۶۱%. It improved the accuracy of forecasting externalenvironmental risks by ۳.۵۲% and reduced the bank's operational risk by ۶.۵۸% and legal and regulatoryrisk by ۷.۰۶% .