Data AnalysisFraud screening

Run a Benford's Law check on transaction amounts

Use to screen a column of financial amounts for digit-distribution anomalies that may signal manipulation.

The prompt
prompt.txt
Act as a forensic data analyst.

I have a column of {{amount_column}} values from {{dataset_description}}.

Walk me through a Benford's Law first-digit analysis:
1. State the expected first-digit frequencies under Benford's Law.
2. Give me {{tool}} code (pandas or pure SQL) to compute the observed first-digit distribution.
3. Compute a chi-square goodness-of-fit statistic and a mean absolute deviation (MAD) score.
4. Interpret the MAD against standard conformity thresholds.
5. List concrete reasons a real dataset might fail Benford's Law without being fraudulent.

Keep the verdict cautious: flag for review, never accuse.

Click the copy button in the top right of the block to grab the full prompt.

Variables

Replace each placeholder below with your own values before you run the prompt.

  • {{amount_column}}
  • {{dataset_description}}
  • {{tool}}
Recommended models
Claude Opus 4.8GPT-5Gemini 2.5 Pro
Tags
#fraud#statistics#benford#audit

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