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// Features

See how an examination runs from hypothesis to report.

ExaminerWorkbenchTM carries the examiner from suspected fraud schemes to the data, the tests, resolved exceptions, and a defensible report. These screens show a sample case built from demo data.

Buy nowBrowse fraud schemes
Case overview with selected fraud schemes, loaded data sets, automated test readiness and highest-risk entities
Case overviewSchemes, data sets, test readiness and highest-risk entities at a glance.

// Step 1

Start with the matter, not the data.

Open a case with its type, period, team, and confidentiality flags such as a protective order. Case parameters such as approval limits and thresholds belong to the case, so tests never rely on hard-coded values.

Case list showing active cases with selected schemes, data request progress and open exceptions
Case listStatus, selected schemes, data request progress and open exceptions for every case.
Case setup with case properties and parameters such as approval limits and thresholds
Case setupCase properties and the parameters the tests use.

// Step 2

Choose the schemes you suspect or want to rule out.

Browse 31 fraud schemes with their red flags, the tests that apply, and a running preview of the data your selection will require. Start from a pack for a common engagement, then add or remove schemes.

Scope screen listing fraud schemes with checkboxes and a detail panel of red flags for the selected scheme
Scheme scopeSelect fraud schemes and review the red flags for each.

// Step 3

Ask the client for exactly what the tests need.

The data request is generated from your selection: a letter, an Excel specification and a tracking checklist. Adding a scheme later produces a request for only the new fields, and follow-up requests chase what is still missing.

Data request tracking checklist showing requested data sets and their load status
Data requestChecklist of requested data sets and what has been loaded.

// Step 4

Data reliability comes before analysis.

Files are hashed and preserved as received, then mapped to a common data model. Account classification is suggested automatically and confirmed by the examiner. Control totals and tie-outs run before any test, and every loaded row links back to its source file and row.

Import wizard mapping source file columns to common data model fields
Import mappingMapping source columns to the common data model.
Evidence files with SHA-256 hashes and control totals compared with client-reported figures
Evidence totalsEvidence file hashes and control totals checked against the client.
Read-only data viewer showing journal entry lines with column filters, grouping, a column chooser and Excel export
Data viewerRead-only view of a loaded data set with filters, grouping and Excel export; each row shows the file and row it came from.

// Step 5

Every test is Ready, Partial or Blocked.

Run 60+ automated tests across payroll, expense reimbursement, purchasing cards, journal entries, financial statements and data reliability. Readiness is shown per test from the data actually loaded, and each run records the application version, test versions, parameters and input file hashes so it can be reproduced.

Test library showing each automated test as Ready, Partial or Blocked
Test readinessEach automated test shown as Ready, Partial or Blocked from the data loaded.
Tests screen for a journal entry testing case, listing each test with its state and exception count
Journal entry testsJournal entry and financial statement tests with their state and exception counts.

// Step 6

Resolve every exception, and say why.

Review is three panes: the list, the exceptions, and the evidence with its disposition. Group the list by entity, ranked by risk, or by test. Results roll up into a 0–100 entity risk score from a published weight table, with related tests counted once. Drill down to the source rows, then disposition each exception as Cleared, Follow-up, or Referred, with notes.

Exception review grouped by entity with risk score, test results and disposition controls
Entity reviewExceptions ranked by entity, with dispositions recorded.
Review of a Benford first-digit test result for a vendor
Benford reviewFirst-digit review of invoice amounts for a vendor.
Payroll review of a ghost employee scheme with exceptions and source records
Payroll reviewGhost employee scheme: exceptions and source records.
Three-pane review grouped by entity with risk scores, exceptions, and evidence with disposition controls
Three-pane reviewEntities ranked by risk, the exceptions behind a score, and the evidence with disposition controls.

// Step 7

Dashboards you can explain to your client.

The Analysis step offers DevExpress dashboards and pivot tables: exceptions by test, disposition progress, and entities by test. Charts appear in context, so a Benford chart opens when you select a Benford exception. Risk scores are transparent weighted sums, with no opaque models.

Analysis dashboard with exceptions by test, disposition chart and entities flagged
DashboardExceptions by test, disposition progress and entities flagged.

// Step 8

Deliverables built from the work you recorded.

Produce a findings report with a methodology appendix, a data reliability report with file hashes and tie-outs, the data request letter with tracking and follow-up requests, and exception workpapers in Excel.

Reports screen listing the findings report, data reliability report and exception workpapers
ReportsFindings report, data reliability report and exception workpapers.

// Step 9

Reports you can hand to your client.

Each report records what was received, what was tested and how, so the work can be explained and defended.

First page of the findings report
Findings, page 1Findings report, opening page.
Third page of the findings report with results by test
Findings, page 3Findings report, results by test.
Fifth page of the findings report with the methodology appendix
Findings, page 5Findings report, methodology appendix.
First page of the data reliability report
Reliability, page 1Data reliability report, opening page.
Third page of the data reliability report with validation results
Reliability, page 3Data reliability report, validation results.

// Local-first by design

Your case data stays with you.

ExaminerWorkbenchTM is a local-first Windows desktop application: case data stays on your machine, and no vendor-hosted service relays it. A Server edition for teams and firm-wide deployment is coming soon.

Buy now

// By the numbers

A larger test library, built to scale.

The library has grown from a first set of vendor and payables checks to coverage across the main occupational fraud and financial reporting risks.

60+

Automated tests across fraud analytics and data reliability

31

Fraud schemes in the catalog, organized by branch and category

6

Starter packs that preselect schemes for common engagements

1M+

Rows per data set tested, with load times under 20 seconds

// Test library

Six areas of tests, each tied to the schemes it detects.

Every test states what it reads, what it flags and the common false positives, and every exception links to the source rows behind it.

Payroll

Ghost employees, falsified hours and falsified pay rates.

Expense reimbursement

Duplicate, inflated and fictitious expense claims.

Purchasing cards

Card misuse and personal purchases.

Journal entries

Management override: unusual timing, users, accounts and amounts.

Financial statements

Trends, ratios, the Beneish M-Score, reserves and understated earnings.

Data reliability

Control totals, GL and subledger reconciliation, and completeness.

// Workspace

A workspace that follows the examination.

A left workflow rail (Overview, Scope, Request, Data, Tests, Review, Analysis, Report, Audit log) gives each step its own screen, with no page scrolling.

Three-pane Review

List, exceptions, and evidence with disposition, side by side. Group the list by entity, ranked by risk, or by test.

0–100 entity risk score

A published weight table drives the score, and related tests are counted once so one pattern is not counted twice.

Linked entities

The risk ranking links related entities, for example a vendor that shares an address or bank account with an employee.

Analysis step

DevExpress dashboards and pivot tables, with charts in context. Select a Benford exception and the Benford chart opens.

Reports

A findings report and a data reliability report, plus the data request letter, tracking and follow-up requests.

// Data and evidence

Built for repeat engagements and defensible evidence.

Read-only data viewer

Browse every loaded data set with filters, grouping and Excel export. Each exception links to the source rows behind it.

Roll-forward and comparison

Roll a case forward and compare period over period for repeat engagements.

Account classification

Accounts are classified automatically as a suggestion, and you confirm or change each one.

Case settings export and import

Export test parameters from one case and import them into the next to keep your approach consistent.

Evidence handling

Every file is hashed (SHA-256) and logged in the chain of custody. Sensitive identifiers are hashed and shown only as the last four digits.

// Integrations

Connect it to the systems you already use.

Bring data in, push results out, and keep case data on your own machines.

Desktop Advanced and Server

REST API

Create cases, push data, run tests, read exceptions and risk rankings, write dispositions back, and download reports. Works with ETL jobs, scripts, Power Automate, and GRC or case-management systems. In the desktop edition it is off by default, listens only on the local machine, and requires API keys.

Coming soon · Desktop Advanced and Server

Source-system connectors

Extract data directly from the client’s accounting system, read-only. Each extraction is saved as evidence and checked against the system’s own trial balance. First: QuickBooks Online. Next: Microsoft Dynamics 365 Business Central and NetSuite. Later: SAP S/4HANA.

Local-first

No vendor-hosted service relays case data or holds connector credentials.