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Explainable AI & Cases

Explainable AI: every alert shows why, and your analyst decides.

No black box. Each alert lists the signals that weighed in, case management organizes the review, and the audit trail records who decided, when and on what grounds, ready for the regulator and the auditor.

Alert

Alert #4821, withdrawal US$ 18,400

Deposit and withdraw, no play

Risk score

87/100

Signals that weighed in

  • Reasons on every alert +31
  • Context next to the alert +24
  • Case management +19
  • Human in the loop +13
High Action Escalated by analyst, grounds logged

What your team gets.

  1. 01 Reasons on every alert The signals that weighed most, in plain language, and how much each one added to the risk score.
  2. 02 Context next to the alert The customer's history, linked accounts and previous cases on the same screen, so the analyst doesn't have to go looking.
  3. 03 Case management Alerts grouped into cases, with assignment, priority, status, notes and attachments in one place.
  4. 04 Human in the loop The AI ranks and explains. The decision to approve, escalate, block or report is made by a person.
  5. 05 Complete audit trail Who saw the alert, who decided, when, on what grounds and with what evidence, all recorded in the case.
  6. 06 Ready for regulators and auditors Any case or period comes with its full history, ready to answer a regulator's request or an audit.

How it works.

  1. 1

    The AI explains

    Each alert arrives with its risk score and the signals behind it, in language the analyst, the legal team and the auditor can all read.

  2. 2

    The analyst decides

    In case management the analyst reviews the context, records the decision and the reasoning, and escalates when needed.

  3. 3

    The platform records

    Every step goes into the audit trail with author, date and grounds. When someone asks, the answer is already written.

Explainability you can defend.

Regulators and courts don't accept "the model said so". What holds up is the record that someone saw the signal, understood it and acted for a reason. The platform keeps that record from the first alert to the final decision.

Audit trail #4821
  1. 14:32:18 · Alert fired Alert #4821, withdrawal US$ 18,400
  2. 14:32:18 · Signals attached Reasons on every alert · Context next to the alert
  3. 14:41:05 · Analyst decision Escalated by analyst, grounds logged
  4. 14:41:06 · Recorded Internal policy, section 4.2 · M. Souza

Explainable AI & Cases · Questions

What buyers ask.

What is explainable AI in fraud and AML?

It is AI that shows the reasons behind each score, not only the score. Every alert lists the signals that weighed most, so an analyst can check them, agree or disagree, and explain the decision later.

Does the AI make decisions on its own?

No. The platform ranks and explains, and the decision on each case stays with your analyst. Real-time controls, such as holding a payment, can run automatically under rules your team approves, but the final call is still made by a person.

What does the audit trail record?

Who opened the alert, who decided, when, which criteria were applied and what evidence supported the decision. The full history stays with the case, ready to show a regulator or an auditor.

What is case management in compliance?

It is where alerts become work: grouped into cases, assigned to analysts, prioritized by risk and closed with a documented decision. It replaces spreadsheets and email threads with a single record of what was reviewed and why.

In English, Portuguese or Spanish

See an alert from start to finish.

Talk to a specialist and see how an alert is explained, reviewed, decided and recorded on the platform, step by step.

Option 1

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