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Fraud Prevention

Fraud prevention that sees the person behind every account.

Behavioral signals, device data and explainable AI catch account takeover, multi-accounting, bonus and promo abuse and payment fraud as they happen, and show your team why.

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Alert

Login from new device and country

Payout details changed minutes later

Risk score

87/100

Signals that weighed in

  • Account takeover +31
  • Multi-accounting +24
  • Bonus and promo abuse +19
  • Payment fraud and chargebacks +13
High Action Session locked, step-up required

What it detects.

  1. 01 Account takeover A login from a new device or location followed by changes to password, email or payout details.
  2. 02 Multi-accounting Several accounts behind the same person or group, linked by device, network, payment method or behavior.
  3. 03 Bonus and promo abuse Accounts that sign up for the offer, meet the minimum and cash out, campaign after campaign.
  4. 04 Payment fraud and chargebacks Stolen cards, card testing and purchases likely to come back as chargebacks.
  5. 05 Mule accounts Accounts opened, rented or taken over to receive and forward money for someone else.
  6. 06 Bots and automation Activity at a pace or regularity no person keeps, from scripted sign-ups to automated betting.

How it works.

  1. 1

    Collect the signals

    Device, network, session and payment data join the transaction and the customer's history via API.

  2. 2

    Link and score

    The engine links accounts that share traits and scores each event in real time. A pattern that persists over time stands out from a one-off coincidence.

  3. 3

    Act in proportion

    Low risk goes through with no friction. Medium risk gets a step-up check or a review. High risk is blocked or held, and the reason is recorded.

Why this account, and why now

Two accounts sharing a network can be a couple. Six accounts sharing a device, a schedule and a bonus cycle for months are not. Each alert shows the links and signals behind it, so your support and legal teams have an answer that holds up.

Explainable AI & Cases
Audit trail #4821
  1. 14:32:18 · Alert fired Login from new device and country
  2. 14:32:18 · Signals attached Account takeover · Multi-accounting
  3. 14:41:05 · Analyst decision Session locked, step-up required
  4. 14:41:06 · Recorded Internal policy, section 4.2 · M. Souza

Built for high-risk markets

iGaming

Detects multi-accounting, bonus abuse, bots and colluding player networks, the profiles that drain margin in online betting.

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Fintechs

Spots account takeover, borrowed or synthetic identities at onboarding and mule accounts used to move stolen funds.

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Digital Banks

Flags account takeover and authorized push payment scams while the payment is being made, when there is still time to stop it.

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Retail

Stops card testing, payment fraud, promo abuse and refund abuse before they turn into chargebacks.

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Fraud Prevention · Questions

What buyers ask.

How do you detect account takeover?

Each session is compared with the customer's usual device, location and behavior. A login from somewhere new followed by a change to password, email or payout details raises the risk score, and the platform can require a step-up check or hold the transaction.

How does multi-accounting detection work?

Accounts are linked by shared traits such as device, network, payment method and behavior over time. A single overlap does not trigger an alert. The group is flagged when the pattern persists, which keeps couples and shared households from being treated as fraud rings.

Can you stop bonus abuse without hurting real customers?

Yes, that is the point of scoring by risk. Most customers go through with no friction, and only accounts with abuse signals have the bonus or coupon held for review. Each decision comes with its reason, so your team can answer a complaint.

Does it help with chargeback prevention?

It flags payments with fraud signals before they are approved, such as card testing, device data that doesn't match or links to accounts with past disputes. Stopping those payments up front prevents the chargeback instead of fighting it after the fact.

The rest of the platform

Transaction Monitoring Every transaction scored for AML risk, in real time. Behavioral Risk Customers whose behavior shifts toward harm or abuse. Screening & Due Diligence Sanctions, PEP and adverse media, for people and companies. Explainable AI & Cases Every alert shows why. Your analyst decides, on the record.
In English, Portuguese or Spanish

Talk to a specialist about fraud in your operation.

Tell us which fraud patterns cost you the most today. We'll show you how the engine reads them and what your team would see on each alert.

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