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SPECIFICATION.md

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AI-Fin Stack: Master Technical Specification

Standardizing the Intersection of Agentic AI and Financial Infrastructure

1. Introduction

The AI-Fin Stack is a reference architecture for deploying autonomous AI agents within regulated financial environments. Its primary objective is to manage the "Determinism Gap"—the discrepancy between the probabilistic nature of LLMs and the binary, deterministic requirements of banking compliance and transaction execution.

1.1 Core Objectives

  • Risk Mitigation: Prevent runaway spending, fraudulent redirections, and logic-based exploits.
  • Regulatory Parity: Map existing financial laws (e.g., MAS, GDPR) into executable code.
  • Operational Transparency: Ensure every autonomous decision has a verifiable audit trail.

1.2 Mandates vs. Guardrails: Technical Definitions

In the context of the AI-Fin Stack, we distinguish between two critical safety concepts:

Concept Nature Enforced By Function
Mandate Deterministic FAGF-FS Validator Non-negotiable financial laws (e.g., spending limits, category blocks). Same input always produces the same outcome.
Guardrail Probabilistic LLM Gateway / Filter Behavioral and environmental safety (e.g., content filtering, politeness, prompt shielding).

Key Principle: Use Guardrails to ensure the AI says the right thing; use Mandates to ensure the AI does the legal thing.

2. The Master Relationship Diagram

The following diagram illustrates the relationship between the core reasoning engine, the FAGF-FS governance shield, and the domain-specific financial modules.

graph TD
    subgraph "Core Agent Architecture"
        Agent[Autonomous Agent / LLM] -->|1. Proposes Intent| Env(Governance Envelope)
        Agent -->|2. Internal Monologue| Audit(Reasoning Audit Bridge)
    end

    subgraph "Governance Layer (FAGF-FS)"
        Env --> Validator{Deterministic Validator}
        Validator -->|3. Validate Mandates| Stack[Mandate Stack]
        Stack -->|Auth/Spend/Velo/Safety| Validator
    end

    subgraph "Financial Sector Modules"
        Validator -->|4. Approved| Modules{Sector Modules}
        Modules -->|Payment| ISO[LLM-ISO20022 Bridge]
        Modules -->|Banking| Core[Core Banking AI Adapter]
        Modules -->|CapMarkets| Trade[Trade Compliance Gatekeeper]
    end

    subgraph "Settlement & Reporting"
        ISO --> Pay(Final Settlement)
        Core --> Ledger(Internal Ledger)
        Trade --> Order(Market Order)
        Validator -->|Blocked| RegTech[AI-Driven SAR Generator]
    end

    Audit -.->|Explainability| RegTech
    RegTech -->|Report| Regulator(Audit/Compliance)
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3. Core Architectural Principles

  1. Decoupled Reasoning: AI logic must be isolated from execution logic.
  2. Deterministic Enforcement: Final "Allowed/Blocked" decisions must be made by non-probabilistic code (FAGF-FS).
  3. Semantic Visibility: The agent must provide a structured reasoning "Envelope" for every action to enable intent-based governance.
  4. A-IAM (Agent Identity): All actions must be cryptographically signed by a unique agent identity bound to an organizational audit trail.