Worked case · Reference condition · 12 figures

Receiver activity review

Investigate receiver behavior

Figure 01 / 12

The population that monitoring actually sees

The population that monitoring actually sees — Receiver activity review. Count; receiver-account events in one day. Exact values are in the figure data below.
Count; receiver-account events in one day

7,448 of 7,600 source items enter this monitoring calculation. The missing 152 items are a coverage gap, not evidence of low risk. Reconcile stable identifiers and amounts where appropriate before interpreting the alert rate.

Figure data and text version
Population stateItems
Included in monitoring7,448
Absent from this run152

A receiving account can collect and forward money for legitimate reasons or as part of a harmful network. The business explanation determines which facts matter.

The reference case starts with the stated population and a functioning evidence path. The owner is risk operations.

All amounts, rates, capacity limits, and outcomes in this case are synthetic. The three conditions are separate assumptions for comparison. A better result in the response condition is not measured proof that the proposed control causes that improvement. The figures expose the calculation and its limits; a real deployment needs its own evidence.

Read the result

The daily source population is 7,600 items, but 152 are outside the completed monitoring run. The included population creates 410 hits and 336 unique cases. With 70 cases already open and capacity for 310, the queue closes at 96. Coverage, duplicate work, and staffing are separate causes; reducing one number does not prove that the overall control improved.

Model inputs and calculated values

Inputs below are the case-specific values. Each figure states the condition-specific assumptions and units used in its calculation. Calculated values are rounded for display.

InputValue
population7,600
alertRate0.055
capacity310
backlog70
Calculated valueResult
population7,600
covered7,448
missing152
raw410
duplicates74
cases336
opening70
resolved310
closing96
capacity310
Figure 02 / 12

From scenario hits to unique cases

From scenario hits to unique cases — Receiver activity review. Count; hit and case units differ. Exact values are in the figure data below.
Count; hit and case units differ

410 raw hits become 336 cases after removing 74 repeated references to the same case under the stated merge rule. Deduplication should reduce duplicate work while retaining the underlying events and reasons. It must not merge unrelated activity merely because values look similar.

Figure data and text version
StageCount
Raw scenario hits410
Duplicate references74
Unique cases336
Figure 03 / 12

The queue balance is an accounting identity

The queue balance is an accounting identity — Receiver activity review. Cases per day. Exact values are in the figure data below.
Cases per day

Opening backlog 70 + arrivals 336 − completed cases 310 = closing backlog 96. Completion is capped by both available work and the stated capacity. This identity is useful even when average handling times are uncertain.

Figure data and text version
MovementCasesDefinition
Opening backlog70Unresolved at window start
New cases336Unique arrivals in this window
Completed310Reached a defined completion state
Closing backlog96Unresolved at window end
Figure 04 / 12

Backlog accumulates across uneven days

Backlog accumulates across uneven days — Receiver activity review. Cases unresolved at day end. Exact values are in the figure data below.
Cases unresolved at day end

This deterministic six-day example applies a stated daily arrival multiplier and a constant completion capacity. Unused capacity does not carry forward as completed work. The series is a workload illustration; it omits variable case durations and specialist routing. Horizontal positions are the labeled observations or scenarios; equal spacing does not imply equal numerical increments.

Figure data and text version
DayClosing backlog
D196
D272
D3165
D4359
D5419
D6344
Figure 05 / 12

Arrivals and completions need separate plots

Arrivals and completions need separate plots — Receiver activity review. Cases per day. Exact values are in the figure data below.
Cases per day

The service line cannot exceed the work available that day. A team can complete more cases than arrive while clearing an opening backlog. Conversely, stable staffing can coexist with a growing queue when arrivals remain higher than capacity. Horizontal positions are the labeled observations or scenarios; equal spacing does not imply equal numerical increments.

Figure data and text version
DayArrivalsCompletions
D1336310
D2286310
D3403310
D4504310
D5370310
D6235310
Figure 06 / 12

An illustrative age profile of open work

An illustrative age profile of open work — Receiver activity review. Cases; constructed snapshot. Exact values are in the figure data below.
Cases; constructed snapshot

The closing backlog is 96 cases. The 50/30/remainder split is an explicit illustrative age allocation, not a distribution inferred from the arrival model. Production age buckets must come from each case’s actual receipt and status history.

Figure data and text version
Age bucketOpen cases
Under one day48
One to three days29
Over three days19
Figure 07 / 12

Completion outcomes are not criminal labels

Completion outcomes are not criminal labels — Receiver activity review. Completed review tasks; synthetic disposition allocation. Exact values are in the figure data below.
Completed review tasks; synthetic disposition allocation

Of 310 completed review tasks, 53 are referred for further assessment, 37 need another evidence action, and 220 close under the stated procedure. These are operational outcomes. None is a probability of money laundering or a substitute for a reporting decision.

Figure data and text version
Review dispositionTasks
Referred for assessment53
Further evidence action37
Closed under procedure220
Figure 08 / 12

Known-event tests assess specific coverage

Known-event tests assess specific coverage — Receiver activity review. Synthetic coverage test. Exact values are in the figure data below.
Synthetic coverage test

The injected test set contains 100 known test events designed to exercise investigate receiver behavior. The system surfaces 92. That 92% detection result measures this constructed test set only; it does not establish population-wide detection of illicit activity.

Figure data and text version
MeasureCountInterpretation
Injected known events100Defined test population
Detected by the scenario92Expected evidence reached the control
Not detected8Investigate data, logic, and delivery
Real-world illicit prevalenceUnknownNot inferred from this test
Figure 09 / 12

Data quality has several independent dimensions

Data quality has several independent dimensions — Receiver activity review. Count; overlapping field checks. Exact values are in the figure data below.
Count; overlapping field checks

Each row is a different field requirement over the same source population. Completeness alone does not establish that values are accurate or current. The case uses explicit illustrative missing counts to show how data quality can affect scenario coverage.

Figure data and text version
Field requirementPresentAbsent
Party reference7,56238
Event time7,52476
Counterparty context7,372228
Figure 10 / 12

Type the relationship before drawing an inference

Type the relationship before drawing an inference — Receiver activity review. Typed evidence relationships. Exact values are in the figure data below.
Typed evidence relationships

This evidence map distinguishes a customer relationship, a transfer, and a case reference. The links support investigate receiver behavior; they do not imply common ownership or intent. A shared data point is a lead whose meaning depends on source, time, and context.

Figure data and text version
FromToRelationship
Receiver activity reviewCounterparty AObserved transfer
Receiver activity reviewProfile recordDeclared business
Counterparty ACase recordEvidence reference
Profile recordCase recordContext for review
Figure 11 / 12

Case clocks start from defined events

Case clocks start from defined events — Receiver activity review. Illustrative internal timing. Exact values are in the figure data below.
Illustrative internal timing

A legal deadline, an internal response target, and an evidence-expiry date can start from different events. The hours here are internal teaching targets only. They are not BSA, sanctions, consumer-protection, or other statutory deadlines.

Figure data and text version
EventRelative timeOperational meaning
Source eventT0Activity occurred
Data arrivalT0 + 2 hoursThe monitoring system learned it
Case createdT0 + 3 hoursWork entered an owned queue
Internal review targetT0 + 27 hoursIllustrative 24-hour target from case creation
DispositionRecorded separatelyUse actual decision and reporting records
Figure 12 / 12

The end-to-end delivery contract

The end-to-end delivery contract — Receiver activity review. Operational control path. Exact values are in the figure data below.
Operational control path

The scenario is incomplete until the intended evidence reaches an owned case. For investigate receiver behavior, verify source coverage, hit creation, queue acceptance, reviewer access, and final disposition separately. A green job status proves only that a job reported completion.

Figure data and text version
BoundaryAcceptance evidence
Source to scenario7448 included source items; 152 missing
Scenario to case410 hits linked to 336 unique cases
Case to reviewerRequired evidence visible under the reviewer role
Reviewer to outcomeDisposition, rationale, and any separate reporting decision retained

Connect the result to the system

Review typed relationships, source records, timing, and alternative explanations.

Check the population, evidence, permitted action, and actual effect together. A balanced calculation can still use the wrong population; a successful response can still leave an unknown financial outcome. The case’s numerical result applies only to its stated assumptions.

Sources and further reading

The chapter sources support the concepts and scope. They do not prescribe the synthetic model rates.

  1. Nacha: 2026 fraud monitoring, Phase 2
  2. FinCEN: deepfake fraud alert