After the visions of Industry 5.0 and Society 5.0 were presented, a proliferation of artificial intelligence technologies have been applied to the financial field because AI develops fast, especially intelligent analysis methods for alternative financial data. However, the organic integration of the financial industry and the Internet of Things lacks relevant standards, and there is no appropriate work summary to coordinate the formulation of these standards. This work aims to effectively improve the reliability of information acquisition and the accuracy of data processing in the financial industry. In addition, this work also investigates papers and standards related to financial intelligence technology in recent years and statistically analyzes the evaluation indicators of AI research papers. Then, a standard evaluation framework is proposed for financial intelligence technology, which is evaluated for performance verification. The comparative experiments demonstrate that the prediction accuracy of the financial intelligence standard model reaches 95.44%, and the prediction error is substantially smaller than that of the other model algorithms. The financial intelligence standard model can make accurate predictions on alternative financial data and has high reliability and validity. The model can provide an experimental reference for intellectual development in the financial field and enable participants to improve work efficiency and standards throughout the process of developing intelligent financial technology.

在工业 5.0 和社会 5.0 的愿景提出后，由于人工智能发展迅速，尤其是针对替代金融数据的智能分析方法，人工智能技术已大量应用于金融领域。但金融业与物联网的有机融合缺乏相关标准，也没有适当的工作总结来协调这些标准的制定。本工作旨在有效提高金融行业信息获取的可靠性和数据处理的准确性。此外，本工作还调查了近年来金融智能技术相关的论文和标准，并对人工智能研究论文的评价指标进行了统计分析。然后，提出了金融智能技术的标准评估框架，对其进行评估以进行性能验证。对比实验表明，金融智能标准模型的预测准确率达到95.44%，预测误差远小于其他模型算法。金融情报标准模型可以对替代金融数据进行准确预测，具有较高的信度和效度。该模型可为金融领域的智力开发提供实验参考，使参与者能够在开发智能金融技术的整个过程中提高工作效率和标准。对比实验表明，金融智能标准模型的预测准确率达到95.44%，预测误差远小于其他模型算法。金融情报标准模型可以对替代金融数据进行准确预测，具有较高的信度和效度。该模型可为金融领域的智力开发提供实验参考，使参与者能够在开发智能金融技术的整个过程中提高工作效率和标准。对比实验表明，金融智能标准模型的预测准确率达到95.44%，预测误差远小于其他模型算法。金融情报标准模型可以对替代金融数据进行准确预测，具有较高的信度和效度。该模型可为金融领域的智力开发提供实验参考，使参与者能够在开发智能金融技术的整个过程中提高工作效率和标准。金融情报标准模型可以对替代金融数据进行准确预测，具有较高的信度和效度。该模型可为金融领域的智力开发提供实验参考，使参与者能够在开发智能金融技术的整个过程中提高工作效率和标准。金融情报标准模型可以对替代金融数据进行准确预测，具有较高的信度和效度。该模型可为金融领域的智力开发提供实验参考，使参与者能够在开发智能金融技术的整个过程中提高工作效率和标准。