What is an
Agent FICO Score?
AI agents are handling real money. But unlike humans, there's no credit bureau that tells you which ones to trust. Until now.
The problem: agents handle money but have no financial identity
In 2026, AI agents are running shopping carts, booking flights, paying invoices, and managing entire supply chains. The average autonomous agent touches thousands of dollars per day. Yet they have no financial history — no credit bureau tracks their behavior, no score tells you whether to trust them.
The result: developers either give agents unlimited spending access (dangerous) or build ad-hoc rate limiters (fragile). Neither approach is sustainable as agent fleets scale past a dozen.
What Agent FICO measures
Agent FICO works exactly like a human FICO score — but built on behavioral data that only AI agents produce. Every transaction, every API call, every spending pattern leaves a footprint. MnemoPay's Merkle-verified memory turns that footprint into a 300-850 score.
Did the agent complete transactions it initiated? Did it honor escrow terms? Did it reverse charges dishonestly? Weighted by recency using EWMA decay.
How close is the agent to its spend limit? Agents that regularly max their limit are penalized — same as a human maxing their credit card.
New agents start at 580 (Fair). Every completed transaction without incident builds history. Ebbinghaus forgetting curves ensure recent behavior weighs more.
Agents that handle varied transaction types (purchases, payouts, escrow) score better than single-purpose agents. Behavioral finance analog to credit mix.
Velocity anomalies, behavioral drift from baseline fingerprint, canary honeypot triggers, and EWMA outliers all reduce score. One confirmed fraud event drops the score 80-120 points.
How it works in 5 lines of code
import { MnemoPay } from '@mnemopay/sdk';
const mp = new MnemoPay({ apiKey: process.env.MNEMO_KEY });
// Before any payment — check the agent's score
const score = await mp.agentFicoScore({ agentId: 'my-agent-001' });
if (score.score < 580) throw new Error('Agent not creditworthy for this amount');
// All transactions feed back into the score automatically
await mp.charge({ agentId: 'my-agent-001', amount: 4999, currency: 'usd' });Scores update after every transaction. The memory is Merkle-verified — tamper-evident and auditable.
What competitors don't have
| Feature | MnemoPay | Mem0 | Skyfire | Kite |
|---|---|---|---|---|
| Agent FICO Score (300-850) | ✓ | ✗ | ✗ | ✗ |
| Behavioral memory (Ebbinghaus) | ✓ | ✓ | ✗ | ✗ |
| Payment rails (Stripe/Paystack/Lightning) | ✓ | ✗ | ✓ | ✓ |
| Merkle-verified audit trail | ✓ | ✗ | ✗ | ✗ |
| Open source (Apache 2.0) | ✓ | ✓ | ✗ | ✗ |
Give your agents a credit history
716+ tests passing. 5 lines of code. Free forever under Apache 2.0.