Multi-Layered Security Framework for Financial AI Solutions - PISA

Generative Artificial Intelligence (GenAI) is rapidly transforming organizations, enabling intelligent customer interactions, automated analysis, and agentic decision workflows. At the same time, GenAI introduces a new class of probabilistic and semantic vulnerabilities like prompt manipulation, hallucinations, sensitive-information leakage, and unauthorized agentic actions, that traditional cybersecurity controls are not designed to mitigate. These risks are particularly acute in financial services, a sector widely recognized as part of national critical infrastructure, where security failures can trigger immediate financial loss, regulatory non-compliance, and systemic instability. This paper introduces PISA, a four-layer security framework designed specifically to protect GenAI applications in financial institutions. PISA integrates prompt-layer defense, information-boundary controls, semantic verification, and agent-authorization safeguards into a unified defense-in-depth model. We present a reference architecture implementing PISA, along with an adversarial evaluation across high-risk financial use cases. The results demonstrate substantial reductions in prompt-injection success, hallucination rates, and unauthorized action attempts compared to baseline GenAI systems. This research provides financial institutions with a practical and sector-aligned methodology for deploying secure, trustworthy, and regulation-aware GenAI systems.