The de tection of the four properties Authenticity, Integrity, Usability, and Security (AIUS ) of Electronic Financial Archive Data (EFAD) data involves multiple technical aspects, such as data encryption, integrity verification, and access control. This complexity prevents the static Particle Swarm Algorithm (PSA) from iteratively adapting to the dynamic changes in financial data, leading to high detection deviations and an elevated risk rate for electronic financial archive data. In order to ensur e the reliability of financial data storage, a method for detecting the four properties of electronic financial file data based on a Dynamic Particle Swarm Algorithm ( DPSA) is proposed to promote the standardization of intelligent financial management. The authenticity, integrity, usability and securit y requirements of Electronic Financial File Data (EFFD) are analyzed in depth. The SM2 algorithm in Digital Signature Algorithm (DSA) is used to encrypt and process the initial electronic financial file data to optimize the security of electronic financial file data. The four -property detection index of electronic financial file data is iteratively optimized based on the dynamic particle swarm algorithm, and the Fitness Value (FV) of the four -property detection index of electronic financial file data is cal culated. The abnormality of electronic financial file data is judged based on the fitness value, so as to realize the Four -Property Detection (FPD) of electronic financial file data. Experimental verification shows that this method achieves good results in the four -propertyistic detection of electronic financial file data. The data encryption results are random, effectively improving the security of electronic financial file data. The detection deviation is less than 1%, an d the risk rate of electronic fina ncial file data is less than 1.5%. The detection results can be intuitively displayed on a visual page, proving that this method effectively ensures the quality of electronic financial file data and promotes intelligent managemen t of electronic financial f ile data.

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