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How Monnai works

How Monnai’s risk intelligence works, from a phone number to a clear answer.

Monnai reads the signals around a person, turns them into insights and returns a decision your rules can act on, with its reasons, in one API call.

  1. Why now
  2. Three layers
  3. Global patterns, local models
  4. Better together
  5. Products

AI-powered fraud is rising. Legacy data can’t keep up.

Generative AI builds convincing fake identities in minutes. Agentic AI now signs up, shops and applies for credit on people’s behalf. Static, fragmented data can’t tell who’s real. The answer is depth: more signals, and risk models trained on patterns from every market.

Business leaders worldwide, in 2025

73%were hit by cyber-enabled fraud, directly or through someone they know.

  • Fraudnow outranks ransomware as CEOs’ top cyber concern.
  • 94%expect AI to be the most consequential force in cybersecurity in 2026.

Source: World Economic Forum, Global Cybersecurity Outlook 2026 (opens in a new tab) · 804 leaders in 92 countries

Credit
Good customers declined.
AI-led lenders approve the thin-file customers a legacy stack rejects.
Market share lost to faster competitors.
Fraud
Synthetic identities approved.
On static records, identities built by AI look just like real customers.
Losses that scale at machine speed.
Verification
Real customers dropped.
Deepfakes force heavier checks, which add friction for the honest and still miss the fake.
Conversion lost, fraud still through.
AI agents
Agents you can’t tell apart.
A legacy stack can’t tell a customer’s agent from a bot behind a made-up identity.
Good agents blocked, bad ones let in.
Agent Pass (KYA)

Every transaction, qualified at two levels.

First the AI agent, if one is acting. Then the person or business behind it. The same AI risk engine runs both, in real time.

  1. Foundation

    One AI risk engine under both.

    AI checks and refreshes 200+ data sources, machine learning links them into identities, and explainable models score each request: good signals as well as red flags.

    Real time · phone and email in a few hundred milliseconds

  2. 2 · Identity

    The person or business on the other side.

    Known or not, good or bad: KYC, KYB, fraud and credit risk, for every sign-up, payment and loan.

  3. 1 · Agent Pass

    The AI agent acting.

    Agent or not, good or bad, and the person or business it acts for: Agent Pass reads each session and checks the agent every time it acts.

    Explore Agent Pass

Global risk patterns, local risk models.

  1. 01

    Learn globally

    Fraud rings, synthetic identities and risk signals seen across every market.

  2. 02

    Tune locally

    Each model is calibrated on local outcomes and local signals.

  3. 03

    Decide in real time

    One answer per request, explained, in every market you serve.

Combine the products, feed your own model.

One call checks the details against each other, and returns fields your decision engine can use.

  • Better togetherPhone, email, IP and name are checked against each other: does the IP match the phone’s country, do phone and email belong to one person?
  • One integration, your mixAny mix of products, per country, through one API and one format. You set the timeout on each request.
  • Built for your model500+ fields ready for your own decision engine, with reasons in plain words.
  • Fast at scalePhone and email answers in a few hundred milliseconds; ~200 ms and 500+ requests a second where customers needed it.
  • Plain answers, not a black boxEvery red flag and good signal says what it found. Add Risk Score when you want one number.

Identity verification, risk intelligence and KYB: three questions, one API.

Test Monnai’s AI risk engine on your own customers.

5 business days to your full report. We commit to it.