Transcript of "Leveraging data analytics to pursue recovery of overpaid transaction taxes"
Leveraging data analytics topursue recovery of overpaidtransaction taxes
According to the U.S. Census Bureau, state and local affect taxability, and customer tax-exemption requests, governments collected more than $1.2 trillion in which may further contribute to potential overpayments. transaction taxes — sales taxes, use taxes, gross receipts Vendors have the burden of collecting the appropriate taxes, fuels taxes, and other excise taxes — from 2007 amount of tax at the point of sale, and may inadvertently to 2010. collect too much — leaving to their customers the task of attempting to recover relevant overpayments. The complex administrative burden of collecting these taxes on millions of daily transactions may result in some Recovering overpaid transaction taxes is easier said than vendors collecting tax on items not subject to or exempt done. Traditional methods have involved creating a from the relevant state and local transaction tax. sampling methodology that state tax auditors will accept, digging through archives of stored records to find old invoices to document the overpayments, and spendingFactors to consider and a process to follow when deploying data analytics for a thousands of hours to build the case. Multiply this effortsales and use tax or other transaction tax review: by over 7,000 different taxing rates and state and local55 Access and ability to analyze a substantial percentage of relevant jurisdictions that impose transaction taxes, and businesses have to wonder … isn’t there a more effective way to transactional data (not just a sample) in disparate systems and identify and reclaim what is rightfully theirs? locations55 Maintain data privacy and security standards while handling data The answer is, yes. By applying state-of-the-art techniques,55 Navigate complex data extraction challenges, with established secure practices, and technology tools to conduct transactional data transfer protocols, from a variety of systems and sources — data mining and data analytics, the process of identifying Oracle, SAP, JD Edwards, Peoplesoft, and custom systems and recovering erroneously paid state and local taxes can be much more effective than traditional methods.55 Target the right population of data for increased tax recovery and Moreover, the recovery process may be leveraged to help compliance fund enhancements to the systems and processes that can55 Assess accuracy of data used for analysis reduce future erroneous payments from reoccurring.55 Consider supplemental, third-party data for the analysis55 Customize data analysis for specific business scenarios The power of Data Analytics55 Leverage industry and tax-jurisdiction-specific knowledge Data analytics applies the power of information technology (IT) to comb through terabytes of transactional data to55 Apply historic trends to predict potential future tax overpayments identify patterns and tendencies that organizations can use55 Apply historic trends to predict tax overpayments to better understand information about their organization — from customer behavior to spending patterns, to forensic methods used for fraud, waste, and abuse. This Consider a scenario in which 5 percent of transaction technology can be used to help an organization become taxes were collected and paid in error. From a purchaser’s better informed and equipped regarding the details of their perspective, from 2007 to 2010 that error rate would have relevant business transactions. The power of data analytics amounted to $60 billion of overpaid transaction taxes that also allows companies to repurpose data requests to are potentially subject to recovery. While many businesses address multiple criteria — for example, double payments, have controls and processes in place to manage their improper payments, and for transaction taxes that may payment of these taxes, leakage in the form of erroneously have been otherwise overpaid. paid taxes still occurs. Applying data analytics to the review for overpaid From a seller’s perspective with respect to the scenario transaction taxes expands the traditional analysis beyond above, significant potential administrative and practical manual reviews of an accounts payable data set. For business considerations arise with respect to multi- example, consider a situation where historic capital project jurisdictional sales and use tax compliance requirements costs are captured in disparate systems and not necessarily and audits by state and local tax authorities, often resulting in the accounts payable system. Determining whether in penalties, interest, and other unreimbursed costs for tax was paid on these purchases or subsequently accrued failing to collect and pay the appropriate amount of could be very difficult, if not impossible. However, applying tax due. The result can be significantly increased and a broad data analytics platform to this scenario could create unreimbursed costs and a negative impact on the provide visibility into the entire spectrum of the transaction. company. This process would involve producing data from the project work order system, linking up to source invoices, Easier said than done and further identifying trends and “soft links” to be able Transaction taxes are executed at the operational level of to connect to invoices and legacy use tax accrual systems. the business. Determining the proper tax amount for a The end result is further identification of whether use taxes nationwide business involves thousands of rates, a variety were accrued on the same transactions. of transaction types with dissimilar characteristics that 2
Getting smarter The concept of predictive analytics allows taxpayers toA significant challenge when building a case to recover handle this challenge in an efficient manner. Identifyingoverpayments of transaction taxes involves extracting and patterns from previous tax-recovery reviews mayorganizing the appropriate tax information from the large substantially reduce the effort required. Recognizingvolume of data that most companies collect and maintain. vendors, vendor categories, and types of purchases that are prone to tax overpayments helps to effectively narrowIn many companies, this information resides deep within down the population for potential recovery. Industrydisparate information systems that support purchasing, and jurisdiction-specific exemptions, along with trendssales, and relevant transaction taxability decisions. It in relevant lines of business, provide better visibility intobecomes very challenging to bring together multiple the situation and the potential transaction tax recoverydata sets to create a consolidated view of taxable and process. This may help taxpayers to predict, with improvednontaxable transactions in order to produce meaningful accuracy, occurrences of tax overpayments.information. Using Data Analytics to pursue tax recoveryMoreover, the decentralized IT infrastructure that is Companies that may have overpaid transaction taxes cancommon in many organizations can contribute to process leverage advanced data analytics techniques to:breakdowns and system integration issues that can cause • Identify and pursue recovery of tax overpayments;leakage resulting in tax overpayments. • Address the potential for prospective tax overpayments; andCompanies invest significant amounts of time conducting • Improve visibility into transaction tax processes andtax recovery reviews to identify overpayments and prepare taxes paid to vendors.appropriate refund claims. The complexity of this processis compounded by the need to compile and organize As shown in the Exhibit 1, the relevant stages in datadocumentation in order to support the claims with relevant mining for tax recovery include data collection, datafacts and figures. validation, data analysis, and outcomes.Exhibit 1: Steps in tax recovery process• Collect internal transaction • Determine the integrity of • Start with a preliminary • Integrate data analytics or data via standard data data sets analysis to identify tax-recovery similar approach into process request forms • Confirm appropriate data potential and systems• Enrich internal data with tax elements are included • Examine a relatively high • Create profiles for specific rates and other external data • Analyze data quality and percentage of transactional historical tax overpayments• Follow data privacy standards integrity of the data sets data, not just a sample to alert management to to protect personally • Look for patterns of over potential tax overpayments identifiable information (PII) payment by vendor, employee, before they may occur again and other variables in similar future transactions • Result is faster than traditional, labor-intensive methods 3