For the complete documentation index, see llms.txt. This page is also available as Markdown.

Compliance

Fair Math Payments is designed to deliver privacy without breaking compliance.

Unlike “black box” privacy tools that obscure all activity, Fair Math Payments introduces a structured and auditable privacy layer. This allows companies, financial institutions, and DAOs to implement confidentiality while still meeting regulatory, accounting, and reporting standards.

Key Principles

  • Auditable Encryption: All encrypted transactions remain traceable and can be decrypted by authorized parties (e.g. internal auditors or compliance officers).

  • Selective Disclosure: Privacy rules can be set so that certain information remains private to the public, but can still be selectively revealed for audits or legal requirements.

  • Regulatory Alignment: The framework is designed to support requirements like KYC/AML reporting, tax filings, and financial auditswithout forcing public exposure of all business operations.

  • Enterprise‑ready Policies: Different departments or workflows can have different privacy levels — e.g., payroll might be fully private, while vendor payments are semi‑transparent for tax reporting.


In short: Fair Math Payments is not just a privacy layer — it’s a compliance‑aligned privacy framework, ensuring that businesses can protect sensitive data and meet all legal, accounting, and regulatory obligations.

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