Agent credentials determine what an agent is permitted to do, under whose authority, and for how long. The technical standards are emerging from OAuth, mTLS, and enterprise IAM — adapted for non-human actors operating at machine speed.
Existing enterprise identity and access management (IAM) systems were designed for human users authenticating into systems at human speed. AI agents authenticate continuously, execute actions at machine speed, and often act across organizational boundaries — conditions that traditional IAM was not designed to handle.
The authorization layer of KYA must answer: What is this agent permitted to do? Under what conditions? For how long? And how does that authorization chain trace back to a verified human or entity principal?
OAuth 2.1 with the client credentials flow is the current standard for secure machine-to-machine authorization. Under this model, an agent authenticates using a client ID and secret (or certificate), receives a scoped access token, and presents that token with each transaction. The scope of the token defines the agent's permitted actions.
For financial agents, scope definition is the critical compliance control: a token scoped to read-only account access cannot initiate a transfer, regardless of what the agent is instructed to do. This makes OAuth 2.1 scope architecture a compliance mechanism, not just a security mechanism.
For high-security and regulated environments, mTLS provides bidirectional authentication: both the agent and the service it is connecting to present cryptographic certificates. This ensures that neither party can be impersonated, and that every connection is to a known, verified endpoint.
mTLS is required in PSD2-compliant open banking infrastructure in the EU and is increasingly expected in institutional-grade API connections for financial services. For agent-to-agent financial transactions, mTLS is the baseline authentication standard that regulators are likely to require.
Enterprise IAM platforms (LDAP, SAML, OpenID Connect) are the existing infrastructure through which organizations manage human user access. As AI agents enter the workforce, they must be onboarded, monitored, and offboarded through the same IAM infrastructure — with appropriate adaptations for non-human actors.
Key requirements for agent IAM integration include: role-based access control (RBAC) aligned with organizational hierarchy; time-bound access grants that expire automatically; API gateway management as a centralized control layer; and complete audit trail logging of all agent actions for compliance review.
A distinct product category is emerging: wallets designed specifically for AI agent transactions, with programmable spending limits, automated compliance checks, and comprehensive audit trails. Early implementations include Skyfire's purpose-built agent payment network and Mastercard's tokenized card approach for B2B agent procurement.
For on-chain financial contexts, smart contract wallets (SCW) and externally owned accounts (EOA) are the on-chain primitives being adapted for agent use, with ERC-7710 as the emerging Ethereum standard for cryptographic delegation across wallet boundaries.
Key Framework References