AI & Agentic Infrastructure

Agentic Payments Authorization Model

The authorization model defines how issuers compose policy rules and evaluate agent transactions. This guide covers rule types, evaluation order, risk signals, and decision output.

In This Guide

Authorization Decision Structure · Rule Types · Policy Composition · Decision Output · Evaluation Order

Trust Signals & Evidence

Author: AffixIO (Kris & Becca Richens). See What is AffixIO.

Method: Authorization is evaluated as a deterministic rules pipeline (hard/soft rules, fixed evaluation order) so verifiers can return a consistent binary decision plus actionable reason codes.

Privacy: Stateless verification by design; no PII stored. See Privacy Policy.

Last updated: March 18, 2026

Further reading: verified AI agent payments, consent framework, OWASP API Security.

Authorization Checklist (Rules to Evaluate)

To produce a reliable binary decision, issuers should evaluate rules in a fixed, auditable pipeline:

Hard rules — signature validity, schema/structure correctness, scope match, expiry, and anti-replay (fail fast).
Soft rules — risk-weighted checks like velocity anomalies, geographic inconsistencies, or agent reputation signals.
Policy composition — combine base, category (merchant), agent-tier, and user policy additively.
Evaluation order — use deterministic ordering so reason codes are stable.
Decision output — return decision, a human-readable reason, and a structured set of checks plus proof/audit evidence.

See also: issuer authorization for the end-to-end flow.

Authorization Model Graph

This diagram shows how hard/soft rules and policy composition turn an agent request into a deterministic YES/NO decision:

Rule evaluation chain

Hard Rules Soft Rules Policy Composition Deterministic Evaluation Order Reason + Proof Output YES / NO

Authorization Failure Modes

Rule gap	What the verifier rejects	Typical reason code
Hard rule fails	Immediate decline	HARD_RULE_FAILED
Soft rule triggers risk/compliance reject	Decision declines (or requests step-up, depending on design)	RISK_OR_POLICY_REJECT
Policy composition misconfigured	Required rules not applied correctly	POLICY_CONFIG_ERROR
Non-deterministic evaluation order	Unstable reason codes / inconsistent evidence	EVALUATION_ORDER_UNSTABLE

For how these checks fit into the full chain, see how issuers verify AI agents during authorization.

Authorization Decision Structure

Authorization is a layered decision. The verifier evaluates rules in sequence, short-circuiting on the first failure:

Authorization decision pipeline

IdentityConsentScopeConstraintsPolicyRiskDecision

Rule Types

Hard Rules

Binary pass/fail. Examples: signature valid, scope match, amount within limit, nonce not replayed. Failure = immediate decline.

Soft Rules

Risk-weighted. Examples: velocity check, geographic anomaly, agent reputation. May trigger step-up verification or flag for review.

Policy Composition

Issuers compose policies from rule sets:

Base policy — Default rules applied to all agent transactions (identity check, consent check)
Category policy — Rules specific to merchant category (higher limits for travel, lower for gambling)
Agent policy — Rules specific to agent reputation tier
User policy — Custom rules set by the delegating user

Policies compose additively: all applicable rules must pass.

Decision Output

The authorization result contains:

decision — YES or NO
reason — Human-readable explanation (e.g., "Amount exceeds max_amount")
checks — Detailed check results (signature_valid, scope_valid, constraints_valid, etc.)
proof — Cryptographic proof object for audit trail

Evaluation Order

Checks are evaluated in a fixed order for predictability:

Schema version
Structure validity
Signature authenticity
Expiry
Issuance sanity
Time window
Scope match
Endpoint / merchant match
Amount / currency
Replay protection
Offline freshness
Policy rules
Risk evaluation

See verified agent payments for the full pipeline.

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Frequently Asked Questions

How are authorization decisions structured?

As a sequential pipeline of checks. Identity, consent, scope, constraints, policy, and risk rules are evaluated in order. First failure causes immediate decline.

What is the difference between hard and soft rules?

Hard rules are binary (pass/fail) and cause immediate decline. Soft rules are risk-weighted and may trigger review or step-up verification.

How do policies compose?

Additively. All applicable rules (base, category, agent, user) must pass. Any failure causes decline.