Getting Good Data and Samples

1. Getting Good Data and Samples Session X10 Cleaning up tax and accounting data 07 | MAY | 2003

2. I. Why Getting Good Data is Difficult I. Why Getting Good Data is Difficult I. Why Getting Good Data is Difficult This section discusses generic causes

3. Taxability Determinations Need a Lot of Data • Exemption or Resale Certificate • Customer or Vendor Master • Billing address vs. shipping address • Legal entity or d/b/a (“doing business as”) • Contract • Purchase order • Original invoice (and any revisions) • Receiving report • Transfers • Proof of payment (check, wire, or EFT) • Adjusting journal entries • Bad debts, reclasses, etc.

4. Data Input Incorrectly • High turnover in data entry function • Performance measured by quantity processed • Insufficient time to train people involved with data entry and data verification • Data quality reviews not effective • Insufficient time to train people involved with data entry and data verification • Head count reduction prevents timely and effective reviews of data • Centralization and shared services • Elimination of people close to operations

5. Extracting Data for Audits is Difficult • Legacy systems not maintained • No one available who remembers how legacy system worked • Poor record retention practices • Purging of old data • To improve current system performance, many IT managers purge inactive vendors and customers • Retrieving old data may not be convenient • IT specialist not available • Backlog of other IT projects, such as bankruptcy and reorganization

6. Adjusting Entries Mixed with Original Data • Many types of adjustments • Correction of coding errors • Reclassification • Checks voided, stopped, reissued • Difficult to link adjustments and original • May not find convenient document locators to link original purchase or sale with adjusting entries • Adjustments not clearly documented • Adjustments run through A/P or A/R • Adjustments not clearly distinguished from original purchases and sales

7. Multiple Purposes for Accounting System • Sales and use tax audit • Want purchases and sales with outside parties • Prefer to exclude adjusting journal entries • Operations and budgeting • Some managers manipulate reported numbers to meet the budget or incentive plan • Financial accounting • Focus on ending balances in accounts, after adjustments and reclasses • Accrual and timing differences

8. II. Specific Transaction Types Specific transaction types of which to be aware

9. Legal Entities • One accounting system for many legal entities • Sales and use tax audits care about separate legal entities, but corporate financial accounting might not • Shared services and warehouses not clearly and consistently allocated to separate legal entities

10. Sales Data • Progress billings • Deposits prior to final delivery • Common in custom construction projects • Sales tax liability not occur until final delivery • Installment sales • Payments spread out after final delivery • Adjustments • Pricing • Returns • Watch for sales tax accrual errors • Failure to adjust sales tax when adjust the sales amount

11. Asset Acquisitions • Progress billings • Installation • Maintenance versus new construction • Capitalization policy • Driven by thresholds, such as $10,000 • Can be avoided by invoicing as separate items under the threshold

12. Expense Purchases • Sales tax errors by seller will have related impact on purchaser • Tax-only invoices • On progress billings and other complex transactions, the seller may issue a “tax-only” invoice after the final delivery • Tax only invoice may be recorded in a month subsequent to the original sale • Adjusting use tax accruals for purchase adjustments • When a purchase is returned or adjusted, the related use tax might not be adjusted

13. Transfers • Withdrawals from inventory for internal use • Might not be documented clearly • What value should be used for determining sales and use tax liability on the withdrawal? • Adjustment in local tax liability • Transfers between locations • Might not be documented clearly

14. Paperless Transactions • Convince auditor that electronic records are valid • Link the electronic purchase orders to the electronic receiving reports • “If the description is not in an electronic file, there is no paper document or human memory to explain it.”

15. III. Verifying Completeness Verifying that the detail files are complete by comparing to general ledger or other reports

16. Methods of Verifying Completeness • Reconciliation • Reconcile from total of transaction detail through adjusting entries to general ledger total • Tracing from top down • For selected accounts and months, trace from monthly G/L total to detail transaction file • Tracing from bottom up • From detail to G/L • Trend analysis • Month-by-month comparison • Ratio analysis • Expense to revenue, location comparison, etc. • Review of extraction procedure • Show nothing was excluded

17. Reconciling Tax Accruals to Tax Returns • Obtain tax accrual detail from Vertex transaction files • Obtain copies of tax returns as originally filed and all amended tax returns • Compare tax accrual detail to tax returns by month • Identify and resolve differences • Timing differences • Reclasses between entities • Credits taken against tax liability

18. IV. Sampling Plan Some general guidance on sampling

19. When To Sample? • Sampling is appropriate when • Cannot readily identify particular accounts, vendors, or other causes for tax errors • Auditor agrees to allow sampling • Taxpayer wants a quick review to identify exposure • Sampling is NOT appropriate when • Cost of extracting particular accounts, vendors, or others is relatively low • Auditor will not accept sampling

20. Negotiating the Sampling Plan • Meet the state’s Computer Audit Specialist (CAS) • Explain problems with obtaining data • Understand concerns of CAS • Understand relationship of CAS and field auditor • Who better understands your data issues? • Who makes the final decisions? • Who is easier to get along with? • Delay releasing data to CAS until general agreement on sampling plan • Might be more difficult to negotiate issues after the CAS has the data

21. Expanding Sample Size • Taxpayer should reserve right to expand sample • Send a letter to auditor, audit supervisor, and CAS reserving right to expand the sample in any stratum “if it appears the results are not representative.” • Do not waive rights to protest sampling plan • Do not sign any letters that imply taxpayer has agreed to sampling plan • Judges may prevent taxpayer from protesting sampling plan in trial court if you sign the notification of sampling

22. V. Emerging Issues Tax policy initiatives that may influence data analysis and sampling for sales and use tax audits

23. Managed Compliance Agreements • Managed compliance is also known as optional reporting of use tax on a percentage basis • Estimate percentage of taxable purchases from a sample drawn during a base period • Apply these percentages to subsequent years • Adjust percentages as needed • Notify state revenue department if major changes occur in operations, accounting, or taxability • May need to draw new sample and compute revised percentages

24. Streamlined Sales Tax (SST) • SST will result in numerous changes in tax law by different states • Compliance errors may occur in months following tax law change • Certification of tax software for compliance with SST • Testing and certification procedures under development by SST audit technology task force • Will be many challenges in implementation • Proposal for multi-state audits • Taxpayer may request one multi-state audit by one lead state on behalf of several states

25. Reduction in Experienced Auditors • States are reducing the head count in revenue departments • Loss of experienced auditors and supervisors • Reduction in training and mentoring for new auditors • Computer audit programs growing • Will the states have enough experienced specialists to deal with the large number of audits that need these skills? • Taxpayers should be pro-active • Taxpayers or their consultants should analyze the population data and recommend solutions

26. References • Data Mining • willyancey.com/data-mining.htm • Sampling • willyancey.com/sampling.htm • Statistics • willyancey.com/statistics.htm