With the advent of the digital and intelligent finance era, in recent years, criminals have frequently utilized artificial intelligence technology to forge and tamper with financial data. Additionally, incidents of financial data and personal privacy breaches have occurred frequently during cross-organizational data sharing through financial sharing systems. To address this issue, this paper proposes a data encryption method for financial approval workflows based on spiking neural networks (SNN). This method establishes a new data encryption system by integrating a data exchange center, hierarchical permission management, differentiated encryption management, and SNN encryption. Leveraging the high complexity and randomness of SNN, it converts financial approval workflow data into difficult-to-decipher pulse sequences, thereby achieving financial data encryption.