EdEconomy Fraud Operations Dashboard

OPS

Work Items Received

12,480

+4.4% vs 7-day average

OPS

Work Items Completed

12,210

+1.9% vs 7-day average

OPS

Net Inventory Change

+270

Current EOD minus prior EOD

OPS

EOD Open Inventory

8,640

+3.2% day over day

OPS

First Action SLO

96.6%

Target ≥95%

OPS

Open Items Past SLO

328

3.8% of open inventory

Daily Queue Performance

T+1 operating results by major queue.

Sep 30, 2026 • T+1

Queue	Received	Completed	Net Change	Throughput Ratio	EOD Open	SLO Met	Past SLO	Past SLO %
Card Fraud	5,120	5,080	+40	99.2%	3,200	97.8%	78	2.4%
ATO	2,180	2,050	+130	94.0%	1,720	94.1%	101	5.9%
ACH / Payments	1,860	1,810	+50	97.3%	1,280	96.3%	59	4.6%
Scam / Social Eng.	1,120	1,030	+90	92.0%	1,040	92.8%	74	7.1%
Deposit / Check	2,200	2,240	−40	101.8%	1,400	98.6%	16	1.1%

7-Day Intake vs Completion

Daily work items for Sep 24–30, 2026.

ReceivedCompleted

7D Avg Received

11,950

7D Avg Completed

11,987

7D Throughput Ratio

100.3%

Open Inventory Aging

0–50% SLO

6,250

50–80% SLO

1,320

80–100% SLO

742

>100% SLO

328

Days of Work on Hand

0.72

Open >3 Days

346

Open >7 Days

88

7-Day First Action SLO

Daily attainment for Sep 24–30, 2026.

SLO Attainment95% Target

7D Daily Mean

96.0%

Sep 30

96.6%

Lowest Day

95.2%

Unassigned Open

612

P90 Time to Final Disposition

3.8h

Escalation Rate

8.4%

Transfer Rate

5.1%

Days of Work on Hand

0.72

Reg Deadline Breaches

0

Source Loads

All Complete

Data Quality

99.98%

OPS

EOD Open Inventory

8,640

+270 vs prior day

OPS

80–100% SLO

742

8.6% of open inventory

OPS

Past SLO

328

3.8% of open inventory

OPS

Open >3 Days

346

4.0% of open inventory

OPS

Open >7 Days

88

1.0% of open inventory

OPS

Days of Work on Hand

0.72

EOD open / 7D avg completed

Open Inventory Aging Detail

Queue	Open	0–50%	50–80%	80–100%	>100%	>3 Days	Work on Hand
Card Fraud	3,200	2,510	430	182	78	74	0.63d
ATO	1,720	1,070	340	209	101	102	0.84d
ACH / Payments	1,280	920	180	121	59	61	0.71d
Scam / Social Eng.	1,040	610	190	166	74	83	1.01d
Deposit / Check	1,400	1,140	180	64	16	26	0.63d

Open Inventory by Status

In Review

4,510

Pending Member

1,320

Pending Internal

1,118

Other / Hold

1,080

Unassigned

612

Daily Inventory Reconciliation

Simplified bridge shown; production version should include reopened items, transfers, and approved adjustments when applicable.

Starting Open

8,370

+ Received

12,480

− Completed

12,210

Net Change

+270

Ending Open

8,640

7D Avg Open

8,636

Disposition Mix

Cleared / No Fraud

68%

Confirmed Fraud

20%

Escalated / Referred

8%

Other

4%

OPS

Daily Throughput Ratio

97.8%

7D rolling 100.3%

OPS

EOD Open Inventory

8,640

-2.9% vs 7 days ago

OPS

Open Items Past SLO

328

3.8% of open inventory

OPS

First Action SLO

96.6%

Target ≥95%

OPS

P90 Time to Final Disposition

3.8h

Sep 30, 2026

REG

Reg Deadline Breaches

0

23 cases in warning window

Executive Queue Summary

Queue	Received	Completed	Net Change	Throughput Ratio	EOD Open	SLO Met	Past SLO %
Card Fraud	5,120	5,080	+40	99.2%	3,200	97.8%	2.4%
ATO	2,180	2,050	+130	94.0%	1,720	94.1%	5.9%
ACH / Payments	1,860	1,810	+50	97.3%	1,280	96.3%	4.6%
Scam / Social Eng.	1,120	1,030	+90	92.0%	1,040	92.8%	7.1%
Deposit / Check	2,200	2,240	−40	101.8%	1,400	98.6%	1.1%

7-Day EOD Open Inventory

End-of-day unresolved work for Sep 24–30, 2026.

EOD Open Inventory7D Average

Core Operational Ratios

7D Throughput Ratio

100.3%

Past SLO %

3.8%

Unassigned %

7.1%

Escalation Rate

8.4%

Transfer Rate

5.1%

Work on Hand

0.72d

Illustrative compliance indicators only. No legal deadline engine, access controls or compliance certification. “Restricted” is a sample label, not enforced access protection.

Regulation E

0 Breaches

Cases in warning window18

Deadline breaches0

Provisional credit timeliness99.9%

Notification timeliness99.7%

Regulation Z

0 Breaches

Cases in warning window5

Deadline breaches0

Acknowledgment timeliness99.8%

Resolution timeliness99.6%

BSA / Fraud Referral

4 Near Deadline

Pending referrals23

Near internal deadline4

Referral timeliness99.3%

AccessRestricted

Identity Theft / Red Flags

2 Unresolved

Unresolved alerts2

Response within target98.9%

Program review currentYes

Open exceptions1

Consumer Impact

+12% Trend

Fraud-related complaints MTD27

30-day trend+12%

Repeat complaints3

False-positive related6

Data Readiness

12 / 12 Loads

Expected source loads12 / 12

Batch completed6:15 AM CT

Data-quality pass rate99.98%

Material data exceptions0

Metric Definitions & Calculations

Standard definitions for the Fraud Operations Daily Review. Figures are synthetic examples. Production metrics require validated event data and end-of-day snapshots; this HTML does not connect to Snowflake or calculate from case-level records.

Reporting date: Sep 30, 2026

Metric	Definition	Calculation	Interpretation / Notes
Work Items Received	Distinct work items entering an in-scope Fraud Operations queue during the reporting date.	COUNT(DISTINCT work_item_id) where received_date = reporting_date	Measures daily operational demand. Reopened items should follow one approved counting rule.
Work Items Completed	Distinct work items reaching an approved final operational disposition during the reporting date.	COUNT(DISTINCT work_item_id) where final_disposition_date = reporting_date	Measures daily completed production, regardless of the date the work item was originally received.
Net Inventory Change	Actual change in open inventory between consecutive end-of-day snapshots.	Current EOD Open Inventory − Prior EOD Open Inventory	Positive = inventory grew. Negative = inventory was worked down. Snapshot-based calculation avoids distortion from transfers, reopened work, and approved adjustments.
Throughput Ratio	Completed work relative to new work received during the same reporting period. This ratio is intentionally not capped at 100%.	Work Items Completed ÷ Work Items Received × 100	Above 100% means completions exceeded receipts. Confirm inventory movement with the reconciliation bridge; transfers, reopens and adjustments can change the result. Not a fraud detection rate.
EOD Open Inventory	All in-scope work items not in a final disposition as of the daily reporting cutoff.	Point-in-time count of open work at reporting cutoff	Open inventory is not inherently overdue; aging and SLO metrics identify unhealthy inventory.
Inventory Reconciliation	Bridge from prior EOD open inventory to current EOD open inventory.	Prior EOD Open + Received + Reopened + Transfers In − Completed − Transfers Out ± Approved Adjustments = Current EOD Open	Use this bridge when source systems contain transfers, reopens, or nonstandard adjustments. The headline Net Inventory Change remains current EOD minus prior EOD.
First Action SLO	Share of work items whose applicable First Action SLO deadline fell on the reporting date and that received the defined first meaningful operational action on or before that deadline.	Items acted by SLO deadline ÷ Items with SLO deadline on reporting date × 100	Using deadline-date cohorts avoids bias from late-day arrivals that have not yet had their full SLO window. “Meaningful action” and SLO duration must be approved by queue/process owners.
Open Items Past SLO	Open work items whose applicable operational SLO has expired as of the end-of-day snapshot.	COUNT(open work_item_id where SLO_due_ts < reporting_cutoff_ts)	Point-in-time exception count; should be viewed with Past SLO %.
Past SLO %	Share of current open inventory that is already past the applicable operational SLO.	Open Items Past SLO ÷ EOD Open Inventory × 100	Allows meaningful comparison across queues of different sizes.
P90 Time to Final Disposition	Elapsed time within which 90% of completed work items reached final operational disposition.	PERCENTILE_CONT(0.90) of (final_disposition_ts − received_ts) for items completed in period	Complements First Action SLO by measuring end-to-end operational resolution time.
Unassigned Open	Open inventory with no valid active owner or assignment at the reporting cutoff.	COUNT(open work_item_id where active_assignment is null)	Use the actual assignment model: individual, team, or queue, depending on the operating process.
Escalation Rate	Share of completed work items that required an approved escalation or referral step.	Completed items with escalation ÷ Work Items Completed × 100	Trend by queue; changes may reflect complexity, policy, or routing.
Transfer Rate	Share of completed work items transferred between in-scope queues or teams at least once.	Completed items with ≥1 qualifying transfer ÷ Work Items Completed × 100	Can indicate routing friction when elevated. Exclude expected workflow handoffs if appropriate.
Days of Work on Hand	Approximate number of average production days represented by current open inventory.	EOD Open Inventory ÷ trailing 7 data-day average Work Items Completed	Provides scale context for open inventory; it is not a forecast of the exact time required to eliminate open inventory.
Open Inventory Aging	Distribution of open work according to the percentage of its applicable SLO already consumed.	(reporting_cutoff_ts − SLO_start_ts) ÷ allowed_SLO_duration	Use nonoverlapping buckets: 0–50% inclusive, >50–80%, >80–100%, and >100%. Apply approved clock and pause rules.
Open Inventory by Status	Point-in-time distribution of open work by standardized workflow status.	COUNT(open work_item_id) grouped by normalized_status	Status normalization should be governed so queues use comparable categories.
Disposition Mix	Distribution of work completed during the reporting period by final disposition.	Completed items by final_disposition ÷ Work Items Completed × 100	Final categories should map consistently across source systems and sum to 100%.
Reg Deadline Breaches	Applicable work items that exceeded an externally required regulatory due date as of the reporting cutoff.	COUNT(applicable items where regulatory_due_ts < reporting_cutoff_ts and requirement not satisfied)	Population, due-date logic, exceptions, and requirements must be approved by Compliance/Legal.
Source Loads	Status of required source-data loads for the reporting cycle.	Completed expected loads ÷ total expected loads	Dashboard should not be treated as complete until all required loads pass.
Data Quality	Share of records/controls passing the approved data completeness and validity checks.	Passed data-quality checks ÷ total applicable checks × 100	Define exact checks in the data-control inventory; material exceptions should be separately surfaced.