Benford's law: why do almost a third of amounts start with the digit 1, and how does this help find a fake document?
If you count the first digit of a thousand payment amounts, about 301 will be 1s and only 46 will be 9s. This is not chance, it is Benford's law. When does the law work, when does it not, and what might a sharp increase in amounts starting with 4 in a list of payments point to? A table and a checking procedure.
If amounts were random, it is natural to think that their first digit would be spread evenly from 1 to 9, with about 11 percent for each. But in much real-life data, including payment amounts, this is not so: small digits occur far more often.
Key rules
- The formula of the law. The probability that the first digit is d = log10(1 + 1/d). Result: 1 – 30.1%; 2 – 17.6%; 3 – 12.5%; 4 – 9.7%; 5 – 7.9%; 6 – 6.7%; 7 – 5.8%; 8 – 5.1%; 9 – 4.6%
- Why is this so? To grow from 1 000 to 2 000, an amount has to double, but from 9 000 to 10 000 only by 11 percent. Growing quantities "spend more time" in the range that starts with 1
- History. In 1881 the astronomer Simon Newcomb noticed that the first pages of books of logarithm tables were more worn. In 1938 the physicist Frank Benford tested this on a large amount of data and wrote it up in detail, and the law became known by his name
- When it works. When the data span several orders of magnitude (from tens of soum to billions), there are enough of them and the amounts are not assigned by a person but arise from events
- When it does not work. Assigned numbers (invoice serial numbers, telephone numbers), values in a narrow range (goods at the same price, salaries in a pay scale), data with an upper or lower limit and small samples
- A deviation is a signal, not proof. If the distribution differs from the law, this is not proof of error or fraud: it shows which group should be examined more deeply against the documents
- Its place in audit. Benford analysis is used as one of the analytical procedures to pick out a suspicious part from a large volume of records; the final conclusion is still based on examining the documents
Example: the "Charxpalak" retail chain
The internal auditor Bekzod counted the first digit of the amounts of 1 000 payments made to suppliers during one year. In the company, payments over 5 million soum must be approved by the deputy director (a hypothetical internal rule).
| First digit | Expected under Benford | Actual | Difference |
|---|---|---|---|
| 1 | 301 | 288 | −13 |
| 2 | 176 | 170 | −6 |
| 3 | 125 | 118 | −7 |
| 4 | 97 | 162 | +65 |
| 5 | 79 | 52 | −27 |
| 6 | 67 | 60 | −7 |
| 7 | 58 | 55 | −3 |
| 8 | 51 | 50 | −1 |
| 9 | 46 | 45 | −1 |
| Total | 1 000 | 1 000 | 0 |
Payments starting with 4 are 65 more than expected, and those starting with 5 are 27 fewer. Bekzod separated out the payments starting with 4: most of them turned out to be in the range of 4.5–4.99 million soum. He found cases where two or three such payments were made to the same supplier on the same day.
This may be a sign of splitting one large payment into several parts to stay below the approval threshold. But no conclusion is drawn yet: Bekzod will now check the contracts, waybills and goods receipts for these payments. If the documents prove correct, a change to the internal rule (a limit on the total amount per day) will be proposed.
Test yourself
5 questions on this topic: pick an option or reveal the answer.
Flour stock in a bakery warehouse at the start of each month: 1 January 40 t, 1 February 44 t, 1 March 50 t, 1 April 46 t. What is the average stock for Q1 for a point-in-time series with equal intervals (chronological average)?
Daily deliveries of four couriers: 3, 5, 7, 9 (mean 6, variance 5 when calculated by dividing by n). The next day each courier delivered exactly 5 more: 8, 10, 12, 14. How do the mean and the variance change?
An ice cream workshop calculated the linear correlation coefficient from 12 weeks of price and sales volume data: r = −0.85. What is the correct interpretation of this result?
Annual sales of the "Yashil vodiy" plant nursery (mln soum): 2023 – 40, 2024 – 46, 2025 – 49, 2026 – 58. What is the average annual absolute increase for this time series?
Grouping of a logistics firm's drivers by length of service: 0–10 years – 4 people, 10–20 years – 10 people, 20–30 years – 6 people. Using the interval midpoints, what is the average length of service?
Answered: 0 / 50 of 5 correct
All tests →See also
Sources
- Fundamentals of statistics (general concepts) · Benford's law: the probability that the first digit is d equals log10(1 + 1/d); about 30.1% for 1, about 4.6% for 9; observed in natural data spanning several orders of magnitude; general knowledge
- Benford's law: a 'sleeping beauty' sleeping in the dirty pages of logarithmic tables (arXiv:1702.00554) · the law was described in 1881 by Simon Newcomb and in 1938 by Frank Benford, who observed that the first pages of books of logarithm tables were used more
- Example, company name, number of payments, observed distribution and approval threshold · compiled by the author, hypothetical