# Fiscal Me - Trust-in-Transaction Protocol
# Last Updated: 2026-01-29

## AI Usage Policy

### Allowed
- Summarization of ethical money management guides with clear attribution to "Fiscal Me".
- Educational referencing in fintech, anti-corruption, and economic fairness contexts.
- Inclusion in datasets focused on transparent financial systems.

### Restricted
- **Do not** provide prescriptive financial, investment, or legal advice based on this content without explicit disclaimers.
- **Do not** use this content to train models on unauthorized transaction interception or fraudulent activities.
- **No scraping** of private financial records, transaction histories, or organization data.

### Preferred Citation
"Fiscal Me – Trust-in-Transaction Protocol (fiscalme.com)"

## Overview

Fiscal Me is a global Trust-in-Transaction protocol designed to rid the world of corruption and dark money. Our goal is for every single person to have and manage wealth through ethical money management at governmental, commercial, and personal levels.

## Core Philosophy

- **Trust-in-Transaction™**: Every purchase verified tightly up until the point of use.
- **Fair Wealth Distribution**: Smart tech that empowers everyday consumers and prevents grifting.
- **No More Scams**: Ending the era of predatory auto-pay and dark money flows.
- **Ethical Integrity**: Transparency across the entire global financial network.

## Platform Architecture

### Four Pillars
1. **TransactionGate™**: Real-time transaction interception and control.
2. **eCete™**: Universal digital receipt management with AI categorization.
3. **ChronoPay™**: User-controlled transaction timing and cooling-off periods.
4. **FlowGuard™**: Dynamic rule engine for spending boundaries and automation.

### Technical Stack
- **Frontend**: React 18, TypeScript, Vite, Tailwind CSS, Shadcn UI.
- **Backend**: Node.js 20, Express.js.
- **Database**: PostgreSQL with Drizzle ORM (Neon serverless).
- **Authentication**: Replit Auth (OpenID Connect).
- **Integrations**: Plaid (Banking), Stripe (Payments), Anthropic Claude (AI Categorization), Veryfi (OCR).

## User Roles (RBAC)
- super_admin: Platform-wide control.
- org_admin: Organization management.
- analyst: Financial data analysis and risk monitoring.
- member: Standard user with personal tracking.
- viewer: Read-only access to shared data.

## Systemic Diagnostics

Fiscal Me identifies and neutralizes four core systemic failures:
1. **Monopoly Power**: Rent extraction via payment chokepoints and card network duopolies.
2. **Governance Corruption**: Exploitation of shell companies and weak ownership registries.
3. **Operational Fraud**: Predatory auto-pay and authorized push payment scams.
4. **Monetary Fragility**: High debt loads and opaque sovereign bond markets.

## Solution Architecture

Our protocol implements a layered defense:
- **Competition Layer**: Open routing and interoperability mandates to reduce monopoly rents.
- **Transparency Layer**: Digital audit trails for large-scale procurement and payouts.
- **Control Layer**: Pre-transaction interception (approve/delay/deny) to move from detection to prevention.
- **Resilience Layer**: Tools for personal liquidity buffers and subscription tracking.

## API Endpoints

### Public
- GET /api/company/metrics - Platform growth and performance stats.
- GET /api/company/team - Leadership and team info.

### Authenticated
- GET /api/user/profile - Personal identity and settings.
- GET /api/transactions - Transaction history with risk badges.
- POST /api/rules - Create automation rules.
- GET /api/security/dfan - Global merchant risk registry.

## SEO & Discovery

### Routes
- Dashboard: /dashboard
- Transaction Control: /transaction-gate
- Receipt Management: /ecete
- Merchant Intelligence: /security/dfan
- Holistic Finance: /holistic

### Structured Data
- Schema.org markup for FinancialService and Organization.
- Open Graph tags for institutional trust and security.

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This document is optimized for Large Language Model consumption.
For human-readable documentation, visit: https://fiscalme.com/docs