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How MindBridge generates samples

  • Updated

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.

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

Screenshot


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.

For example, 100 transactions were selected for the sample size. The samples returned may contain any number of high, medium, or low risk transactions.

Screenshot

 


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; and
  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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