Platform
Risk Signals
Turn detection results into a view of your threat surface — patterns rather than single incidents. Available on request.
- Attack heatmaps by channel, team, and workflow — on request
- Week-over-week trend tracking, not single alerts
- Spot campaigns before they become losses
See where attacks concentrate
Aggregated across your checks, the same evidence shows which channels, teams, and workflows attract the most synthetic-media activity — so you can put defenses where attackers actually go. Set up with our team rather than self-serve.
Trends, not noise
Attack techniques change weekly. The same result stream can be tracked over time to show how the threat mix shifts — new generation tools, new targets, new hours of attack.
Close the loop
Signals are worth more fed back than filed. Use them to tune your own thresholds and route the riskiest sessions to review, so what you learn on Monday hardens your defenses by Tuesday.
/ROI
What this is worth
- One AI engine for every surface — add modules without adding vendors, contracts, or review queues.
- Evidence-backed results drop straight into your decisioning: auto-decline, step-up, or route to review.
- Live in a day: one REST API call in, a scored result out — no model training, no data-science team required.
Common questions
What are risk signals in fraud detection?
Risk signals are the structured evidence a detection system produces alongside each result — which manipulation indicators fired, on which channel, in which workflow, and when. Individually they explain one decision; aggregated, they describe your threat surface. ScamAI can roll your result telemetry up into heatmaps and trends — where synthetic-media activity concentrates, how the attack mix shifts week over week, and where the same forged template keeps reappearing. It is arranged with our team rather than switched on in the dashboard, which reports one verdict per check.
How do teams monitor deepfake attack trends?
The raw material is result telemetry: every detection check records what fired, where, and when. Trend monitoring aggregates that stream by channel, team, and workflow, so shifts become visible — a new generation tool in onboarding, injection attempts concentrating on one product, attack volume moving to off-hours. Effective teams review trends on a fixed cadence with a named owner, then respond through policy: tightening thresholds on workflows under pressure or routing the riskiest sessions to human review.
Can detection thresholds be tuned based on analytics?
Yes — that feedback loop is the point of trend data. ScamAI results are probabilistic confidence scores rather than fixed yes/no answers, so thresholds are yours to set, and trends tell you when to move them. If trend data shows a campaign concentrating on one workflow, lower that workflow's auto-decline threshold or widen its human-review band — a policy change, not a redeploy. Best practice: decide in advance which patterns trigger which changes, so tuning is documented policy.
See ScamAI on Risk Signals
15 minutes, on your own media. Pick a slot and leave with a result.