Repeated Alert Suppression Guide

Repeated alert suppression cuts the repeat noise that ongoing monitoring creates. When a profile stays on monitoring, Minerva compares each new screening result with earlier results for the same profile and decides whether the result is a fresh alert or the same finding again. It is a Screening feature that works on profiles. The profile is the persistent reference for the screened subject, so the first onboarding screen and every later screening run are compared against the same record. It does not apply to one-off searches through the API, which leave no profile to compare against. Access: Requires the Admin role or above. Go to Administration > Configuration, then open Repeated Alert Suppression under Screening Behaviours.

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Before you begin

• Confirm your screening is managed in Minerva with profiles, not only as one-off searches through the API.
• Confirm the profiles in scope are part of your ongoing monitoring workflow and carry a monitored status.
• Confirm you have the Admin role or above.
• Read the Screening Guide if you need a refresher on profile and alert review workflows.

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How repeated alert suppression works

Suppression is built for repeated monitoring on the same profile.

1. Minerva uses the profile as the persistent reference for the screened subject.
2. It compares a new monitoring result with prior matched results for that profile.
3. It evaluates the configured rules for name, date of birth, location, adverse media article similarity, and source changes.
4. It decides whether the new result stays visible as a fresh alert or counts as repeat noise.

Because the comparison needs a history to compare against, suppression is most useful after onboarding or the first screening event. Once a profile exists, later screening results are measured against that profile’s monitoring history.

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The configuration page

The Repeated Alert Suppression page keeps four things in one place:

• The global on or off state for suppression
• The built-in or organization preset that sets the baseline
• The rule controls that tune repeat detection
• The change review, history, and rollback tools

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Suppression state and preset

At the top of the page, Minerva shows:

• Repeated Alert Suppression Enabled: turns live suppression on or off for the organization
• Ruleset preset: selects the preset that provides the current baseline
• Current display state: shows whether the draft still matches a saved preset or has drifted to Custom

Tuning individual controls can switch the display state to Custom, even while the draft stays anchored to the preset it started from for comparison. Most organizations see Repeated Alert Suppression Enabled with Built-in: Balanced selected.

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Presets

A preset is a named starting point for the whole rule set. Minerva includes three built-in presets, and each workspace can keep its own reusable presets as well. Built-in presets stay fixed. Balanced is the default preset. Use the other presets only when you have a clear reason to move away from that baseline.

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Conservative

Use Conservative when your team prefers broader analyst visibility and wants to suppress only the clearest repeats.

• Stricter name and location matching, so only stronger repeats are grouped
• Date-of-birth matching stays tight and still expects an exact month and day when both records include them
• More corroborating identity evidence required before suppression is allowed
• Narrower name-only repeat behavior, with a more limited focus on PEP noise
• More sensitive adverse media handling: any new article counts as alert-worthy, and a shared location is required when both records include one

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Balanced

Use Balanced for the default Minerva posture on repeated sanctions, PEP, and adverse media monitoring noise.

• Moderate name and location matching that reduces repeat noise without grouping too aggressively
• Date-of-birth checks stay tight when that information is present
• Meaningful corroborating identity evidence required before suppression
• Name-only repeat behavior applies across Sanctions, PEP, and News
• Adverse media stays visible when an article appears materially different, while closer repeat coverage is suppressed

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Aggressive

Use Aggressive when recurring monitoring results create significant repeat noise and you want broader suppression.

• Broader name and location matching, so more recurring noise is grouped as repeat activity
• More date-of-birth flexibility than the other built-in presets
• Corroborating identity evidence is still expected, but suppression is more willing once that evidence is present
• Broader name-only repeat behavior across Sanctions, PEP, and News
• The most aggressive adverse media handling: additional article churn is suppressed after the same subject has been established

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Shared defaults across the built-in presets

All three built-in presets start with:

• A recent-history lookback window for repeat comparison
• Sanctions new-source alert turned off
• PEP new-source alert turned off

Turn the new-source alerts on only when you want Minerva to re-surface same-identity sanctions or PEP matches after genuinely new source labels appear. See Sanctions and PEP Policy for what each source set covers.

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Workspace presets

Each workspace can also maintain its own reusable presets. A workspace preset lets you:

• Save a custom draft as a reusable preset
• Rename a preset and update its description
• Overwrite a preset with the current draft values
• Delete a preset from the library without deleting the live suppression configuration

Use preset names and descriptions to capture the operational context:

• The risk posture the preset supports
• The business unit or review workflow it was designed for
• The reason the preset exists

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How similarity algorithms and scores work

Most similarity rules use a normalized score from 0.00 to 1.00.

• A score closer to 1.00 means the two values look more similar
• A higher threshold is usually stricter, so fewer borderline repeats are suppressed
• A lower threshold is usually broader, so more repeated noise may be grouped together

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Algorithm guidance

Scores from these algorithms feed the thresholds below. For how Minerva scores a potential match in the first place, see the Match Scoring Guide.

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How to read higher and lower values

• Similarity thresholds: higher is stricter matching, and usually fewer suppressions
• History window: higher looks farther back and can suppress more recurring noise
• Date-of-birth year window: higher tolerates more year drift
• Minimum corroborating signals: higher requires stronger identity evidence before suppression
• Minimum matching locations: higher requires more location corroboration
• New-source minimums: higher requires more new sources before a fresh sanctions or PEP alert appears

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Rule-by-rule controls

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History window

Previous searches to scan controls how far back Minerva looks for prior matched monitoring results.

• Range: 1 to 10 previous searches
• Higher values usually suppress more recurring alerts
• Lower values keep older prior results from influencing the decision

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Name similarity

Algorithm and Similarity threshold decide how closely a new result name or alias must resemble a prior one before Minerva treats it as the same repeat.

• Threshold range: 0.00 to 1.00
• Higher threshold: stricter name matching
• Lower threshold: broader name grouping

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Date of birth

Use these controls when date-of-birth evidence matters to your review process:

• Allowed DOB window (+/- years): range 0 to 10
• Require exact month/day when both are present: adds a stricter check whenever both records include month and day detail

Use tighter settings when date of birth is usually complete and reliable. Use looser settings only when the data sources often carry partial or slightly inconsistent DOB information.

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Location similarity

Use the location controls when geography helps distinguish repeated results for the same subject.

• Algorithm
• Location similarity threshold: range 0.00 to 1.00
• Minimum matching locations: range 1 to 5

Raise the threshold or the minimum count when you want more geographic corroboration before suppression.

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Strong identity

Minimum corroborating signals controls how many strong identity signals must align before Minerva allows suppression.

• Range: 1 to 3 corroborating signals
• Higher values make suppression more conservative
• Lower values make suppression easier to trigger

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Name-only repeat

Use this rule to suppress repeated name-only noise even when date-of-birth or location evidence is limited.

• Name-only repeat threshold: range 0.00 to 1.00
• Feeds: choose from Sanctions, PEP, and News

For what each feed covers, see Data Feeds. If no feeds are selected, Minerva does not apply the name-only repeat rule until at least one feed is chosen.

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Adverse media

Adverse media has the richest set of controls, because Minerva decides two things: whether the subject looks like the same person or organization, and whether the article looks like the same story. For how Minerva sources and classifies articles, see Adverse Media and Adverse Media Categories. Controls:

• Article treatment
• Subject algorithm
• Subject similarity threshold
• Article algorithm
• Article similarity threshold
• Require a shared location when both records include one

Article treatment options:

• Any new articles alert: every new adverse media article still appears for review
• Only dissimilar articles alert: near-duplicate coverage is usually suppressed, but materially different stories stay visible
• No new articles alert: repeated article churn is heavily suppressed once Minerva has established the same subject

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Sanctions new-source alert

Use this control when the same monitored identity should alert again only if additional sanctions source labels appear.

• Status toggle: on or off
• Minimum new sanctions sources: range 1 to 10

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PEP new-source alert

Use this control when the same monitored identity should alert again only if additional PEP source labels appear.

• Status toggle: on or off
• Minimum new PEP sources: range 1 to 10

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Reviewing and confirming changes

Review changes does not save immediately. It opens a grouped confirmation view so you can verify what is about to change. The review dialog shows:

• The number of changes and sections affected
• A grouped summary for each rule family
• The current value and the new value side by side
• A short tone label such as Will update, Will enable, or Will disable
• An optional Change Description field

Use the change description to capture the business reason for the update. That description is available later in configuration history.

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Deployment history and rollback

A History preview on the page covers recent deployments without leaving configuration:

• See the current live deployment first
• Review older deployments as rollback candidates
• Preview an older deployment in the current page before committing to it
• Jump to the full audit history page

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How rollback works

Rollback is a controlled restore flow, not a destructive undo.

1. Minerva previews that historical configuration in the current page.
2. The page remains in preview mode until you cancel or continue.
3. If you continue, Minerva shows the grouped rollback review before anything is applied.
4. When you confirm, Minerva writes a new rollback history entry and makes that restored configuration live.

Important behavior:

• Rolling back does not delete prior history entries.
• The rollback itself becomes part of the audit trail.
• Minerva blocks a rollback when the selected history entry already matches the current live configuration.

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Full audit history table

Use the full history page when you need the complete audit record, not just the recent quick-compare list. The table includes:

• Changed: when the configuration was saved or rolled back
• Action: whether the event was an update or a rollback
• Summary: the key rule or preset changes from that deployment
• Changed by: the user who performed the action
• Actions: rollback entry points for older deployments

You can also:

• Filter by actor name or email
• Filter by All changes, Updates, or Rollbacks
• Sort by changed time, action, or actor
• Page through the full history set

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Recommended tuning approach

If you are configuring repeated alert suppression for the first time:

1. Begin with the Balanced baseline
2. Change one rule family at a time so the effect is easier to understand
3. Add a clear change description whenever you save
4. Use history and rollback if a tuning pass proves too broad or too strict

This usually produces a cleaner operating model than moving directly to the most aggressive settings.

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Related guides

• Screening Guide
• Profiles
• Workspaces Guide
• Bulk Actions Guide