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2006 UPHLC National Education Seminar March 6 – 9, 2006 Sampling for Unclaimed Property

2006 UPHLC National Education Seminar March 6 – 9, 2006 Sampling for Unclaimed Property Dr. Will Yancey, CPA Independent Consultant, Dallas, Texas (972) 387-8558 will@willyancey.com. Sampling for internal purposes. Sampling to analyze UP exposure:

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2006 UPHLC National Education Seminar March 6 – 9, 2006 Sampling for Unclaimed Property

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  1. 2006 UPHLC National Education Seminar March 6 – 9, 2006 Sampling for Unclaimed Property Dr. Will Yancey, CPA Independent Consultant, Dallas, Texas (972) 387-8558 will@willyancey.com

  2. Sampling for internal purposes Sampling to analyze UP exposure: • Exploratory sampling to identify internal control weaknesses. • Plan what further work is needed. • Estimate UP reserve for financial statements.

  3. Sampling for UP audit and VDAs If periods where no transaction-level documentation can be retrieved, estimate a UP-to-revenue ratio from available records and project onto revenue for period without available records. Sampling usually not allowed where $ can be identified for true owners. If high-volume of transactions below the threshold for reporting owner name, state UP auditor might allow sampling.

  4. Triage the data download EXCLUDE: areas of extremely low error rate, dormancy not expired, items with very low $. DETAIL (EXAMINE ALL): items with high $ amounts, areas of extremely high error rate, specific legal issues. SAMPLE: items not Excluded or Detailed

  5. Sampling Plan Trade-offs in sample size • Costly to increase sample size • Benefit of larger sample size is more accuracy. Some costs and benefits are readily quantified, and some are not. What determines sample size?

  6. Parable of Footballs and Fish 1. You are asked to determine the weight of 1,000 footballs. You know they are identical in weight. You can weigh only one ball at a time. How many must you weigh? 2. You are asked to determine the weight of 1,000 different fish taken from a lake. They are highly variable in weight. You can weigh only one fish at a time. How many must you weigh?

  7. Variability drives sample size The variability in the population drives sample size. Reducing variability within a group reduces required sample size. Suppose we can group and count the fish before we weigh them. What can we do so that we do not need to weigh so many?

  8. Grouping data for UP sampling What attributes are most likely to change the frequency of UP? • Customer type (commercial, residential) • Employee type (hourly, salaried) • Length of time outstanding • Accounting system change • Others?

  9. Stratifying Within a Group Most accounting line item data files have lots of small transactions and relatively few large items. Stratified Random Sampling example: Above $1,000: detail exam $100 to $1,000: sample stratum $10 to $100: sample stratum $1 to $10: sample stratum 0 to $1: exclude

  10. Minimum sample size per stratum No universally accepted policy on sample size. A simple rule for determining sample size: • What is the minimum number of errors required for projection? • How low an error rate do you want to detect? Sample size per stratum = Minimum number of errors ÷ Minimum detectable error rate 3 ÷ .01 = 300 3 ÷ .05 = 60 3 ÷ .10 = 30

  11. Sampling Risk Sampling risk is the chance that the result from a sample differs from the result from examining every item in a population. Every sample has some sampling risk. A well-designed sample has less sampling risk. Sampling risk would be eliminated if every item in the population were examined.

  12. Statistical Sampling In statistical sampling, sampling risk is estimated quantitatively based on statistical theory. Examples: • 95% confidence the population total is in the range $160,000 to $240,000 ( = $200,000 ± 20%) • 90% confidence the population total is in the range $180,000 to $220,000 ( = $200,000 ± 10%) In statistical sampling every item in the population has some known positive probability of selection. That probability may differ between strata.

  13. Nonstatistical sampling Nonstatistical sampling does not quantify sampling risk based on statistical theory. The sampling risk and acceptability of the sample depend on the auditor’s judgment. If a stratified random sample is taken, but no statistical quantification of sampling risk is presented, then it is nonstatistical sampling.

  14. Nonsampling Risk Nonsampling risk includes every other risk that the sample results are not representative. Measurement error, such as the auditor incorrectly interprets facts or law. Selection bias, such as selecting too many items from beginning or end of audit period. Projection bias, such as the period being projected onto is not similar to the period that was sampled.

  15. Avoiding Sampling Disputes • Invest time in analyzing the population. • Take a preliminary sample to verify availability of records. • Discuss the sampling plan with all parties and make changes. • Document sample selection method. • Ask a sampling expert to review the method.

  16. References willyancey.com/statistics.htm willyancey.com/sampling-financial.htm willyancey.com/unclaimed.htm Yancey, Statistical Sampling in Sales and Use Tax Audits, onlinestore.cch.com Guy et al, Practitioner's Guide to Audit Sampling, (Wiley, 1998).

  17. Questions

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