The dollar to zero rapid migration to cloud-hosted financial infrastructure poses challenges to secure, scalable, and compliant data protection of the multi-tenant environment. Secure architecture should be able to withstand illegal access and still be able to exercise fine grained control of data. Which is the integration of the latest additions like the AI inference unit, blockchain validator modules, the attribute-based Encryption (ABE) engines can provide a powerful solution. AI enables dynamic detection of anomalies as well as adaptive access control, blockchain ensures that transactional logs are hard to tamper with and auditable, and ABE establishes flexible cryptographic implementation of access policies. A combination of these tools forms a hierarchical defense system that is tailored towards safe sharing of financial data in multi-tenant clouds. This paper introduces a new type of hybrid security system which uses AI, blockchain and ABE to increase confidentiality, integrity, and access accountability of financial data in a shared cloud environment. In the methodology, architectural modeling, mathematical representation of data flow, simulation through MATLAB with synthesized financial data, and performance assessment against latency, throughput, and encryption/decryption time as well as CPU usage are applied. The framework is built out of two models: the first comprises blockchain and ABE integration exclusively, and the second one is enriched with dynamic access policies implemented via AI. According to the comparative analysis, the measures of data security and reduction of performance overhead demonstrate significant improvements. Moreover, predictive mitigation of threats comes with the ability to detect unusual access patterns better with the help of intelligent access control done via AI. The simulation employs the embedded data structures in MATLAB without any externed files as well as reproducibility. The hardware architecture features a multi-core processor system, virtual node interaction and evaluation of security core parameters. The findings indicate that the suggested system is effective when it comes to the protection of confidential money information in multi-tenant cloud implementations.