Equal Pay Auditorsame work, same price, found before the claim

The worked specimen, labelled SPECIMEN

A full audit of a synthetic 50-row extract for a supposed 172-worker EU financial-services employer. No real employment data, no worker identified: the rows are invented for the demonstration, and every figure below is computed from them by the engine you can run free above.

The flagged outcome: 16 of 19 categories flagged, 3 at or above the 5 percent trigger; overall mean gap 8.68%, median gap 16.18% (Art 9(1)(a) and (c), FTE-adjusted basis). Exposure, as the scenario sizes it (each worker lifted to the category median): 13,587.5 a year across the paste.

Reproducing the headline figures from this page: the overall mean gap is computed over the 49 gendered rows pasted (worker-weighted, not an average of the category gaps): average pay men 51243.18, women 46795.37; the median version compares the median pay levels (men 51600, women 43250). The category figures are the Art 9(1)(g) item; the overall figures are the Art 9(1)(a) and (c) items. The rows behind these numbers are in the tool; paste is at the sources note.

The duty row: 150 to 249 workers: By 7 June 2027 and every three years thereafter (Art 9(3)). (pinned by the specimen headcount.)

The same-work screen matches exact title text, level words in; it is a screen of the pasted pay figures, not a job evaluation, and it does not certify legal compliance. Equal value is decided on the four criteria of Art 4(4) through your own job evaluation; the engine never rules that pay is compliant. This page flags potential parity issues; it does not certify legal compliance.

The categories the screen found

Job title (exact match)RowsMinMedianMaxMean gapMedian gapStatus
Senior Compliance Officer266500703507420010.38%10.38%FLAGGED
Loan Operations Officer438000403504700015.82%16.6%FLAGGED
Risk Analyst26222563862.5655005%5%FLAGGED
Underwriter3582005910059400-0.51%-0.51%FLAGGED
Payroll Officer24325044000447503.35%3.35%FLAGGED
Team Leader Collections2520005275053500FLAGGED
Relationship Manager35730057900601004.16%4.16%FLAGGED
Compliance Officer26720067600680001.18%1.18%FLAGGED
Insurance Claims Assessor35080051200515000.1%0.1%FLAGGED
HR Adviser25870058950592000.84%0.84%FLAGGED
Mortgage Underwriter2611006130061500FLAGGED
Customer Service Representative5335003360034100-0.05%0.45%FLAGGED
Data Analyst25480054900550000.36%0.36%FLAGGED
Business Support Assistant3312003130031450-0.08%-0.08%FLAGGED
Call Centre Agent43540035400359000.47%0%FLAGGED
Accounts Payable Clerk2418004180041800NO FLAG
Collections Officer34060040600406000%0%NO FLAG
Financial Controller1885008850088500SINGLE
Claims Handler3448004480045200-0.45%-0.45%FLAGGED

What the buyer does with it

  1. Correct the groupings the machine proposed (merge, mark out, exclude rows, reasons recorded).
  2. Test every flagged category against the Art 4(4) criteria and record the answer.
  3. Prepare the joint pay assessment with the worker representatives for the categories that stay unjustified at or above 5 percent (Art 10(1) and (2)), treating the six-month window as running from the report submission (Art 10(1)(c)).
  4. Keep the run: the file the burden of proof asks you to hold (Art 18(2)).

SPECIMEN: the dataset is synthetic end to end. The figures are deterministic and reproducible from the paste; nothing here is written while a reader waits.