How MindBridge generates samples

Summary

You can use risk-stratified and random sampling methods to have MindBridge generate samples for you. These samples will be added to the Audit Plan as tasks.

• Risk-stratified: Uses risk scores to stratify the data currently displayed in the data table (i.e., entries or transactions, and any applied filters). This method is unique to MindBridge and favors high-risk and medium-risk entries/transactions when creating the sample.
• Random: Creates a truly random sample from the data currently displayed in the data table (i.e., entries or transactions, and any applied filters). Each entry/transaction has an equal chance of being selected, regardless of risk level.

Learn about risk-stratified sampling and random sampling in MindBridge below, and learn how to create a sample.

Note: Any entries or transactions that have been added to the audit plan will be excluded automatically from sampling.

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Risk stratification and the 60/40 split

When you create a risk-stratified sample, MindBridge selects all high-risk scores available to be sampled (within the scope of the filters applied to the dashboard), and the rest of the sample is split to contain 60% medium-risk transactions and 40% low-risk.

For example, 100 transactions were selected for the sample size. The financial data table contains:

• 6 high-risk transactions
• 56 medium-risk transactions
• 38 low-risk transactions

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Random sampling

When you create a random sample, the items currently displayed in the data table (i.e.; entries or transactions that have not yet been added to the audit plan, and any applied filters) are shuffled, assigned a number by a pseudo-random number generator (PRNG), and then selected based on that randomized number.

You can choose whether the random sample pulls from:

• The full filtered list of items on the data table, including previously sampled entries or transactions, or

• A list that excludes previously sampled items

For example, if the sample size is set to 100, the resulting sample may contain any combination of high-, medium-, or low-risk transactions, depending on the data table contents and selected sampling option.

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Technical details

1. The PRNG is configured with a random seed based on system time and other variables;
2. A random number is generated for each item using the PRNG;
3. The items are sorted by their generated numbers.
4. The lowest "n" (sample size) items are returned as the sample.

For risk-stratified sampling, the above process runs 3 times, for high, medium, and low risk transactions.

For random sampling, the above process runs once across the whole population.

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