The Playbook to Stop Polymorphic AI Fraud
Understand every alert at a glance
Vera instantly explains why an alert fired and which risk indicators matter most — cutting manual summarization so reviewers decide faster and more consistently.
One button, full context
Vera reads the alert, the review history, and the entity details, then explains why it fired and what matters — so reviewers spend their time deciding, not summarizing.
Know why an alert fired
A single “AI Summary” button explains the triggered rules and the risk signals behind the alert.
Focus on the key risk indicators
Vera reads the alert’s rules, prior review history and notes, and event and entity details to highlight exactly what a reviewer needs.
Faster, more consistent dispositions
Reviewers spend less time summarizing and more time deciding, with summaries that stay under human review.
From alert to disposition, faster
One click pulls the triggered rules, review history, and event details into a concise, cited summary — ready for the reviewer to verify and disposition.
From alert to disposition, faster
Open the Alert Details page.
Click “AI Summary.”
Vera pulls triggered rules, review history and notes, and event and entity details.
It generates a concise summary of why the alert fired and which indicators matter.
The reviewer verifies and dispositions.
The reviewer stays in control
Summaries are assistive and cite the underlying events and signals so they can be verified. Usage is audit-logged and RBAC-scoped, and Vera never decides the alert.
Triage across fraud and AML
Alert triage and disposition across fraud and AML queues, applicable to all alerting scenarios.
60% less investigation time
Summaries stay under human review — faster reviews, with greater consistency across the queue.
Summaries grounded in real case context
Because it’s embedded in Alert Details, Vera grounds every summary in unified real-time case data and DataVisor’s own decisioning, and cites the triggering evidence — context a generic LLM lacks.
Governed, private, and auditable
Like every Vera agent, alert summarization runs on Amazon Bedrock statelessly — prompts and case data are never stored by AWS or used to train foundation models, and are processed in full per-customer isolation.
- Stateless processing on Amazon Bedrock — nothing stored by AWS
- Every summary cites the triggering rules and events
- Usage is audit-logged and RBAC-scoped
- Runs on the same models and published rates as a full seat
- Failed generations don’t consume tokens
Common questions
Does the AI decide the alert?
No. The summary is assistive; reviewers verify against the cited evidence and make the disposition.
What about accuracy?
Summaries cite the underlying events and stay under human review, so reviewers can confirm every point.
Make every review faster
See how Vera turns a raw alert into a clear, cited summary in seconds.