Budget cuts and a decreasing workforce have weakened the government's ability to serve taxpayers, process payments, and enforce tax laws – yet, tax filings and call center traffic continue to rise. Tax agencies need to leverage efficient methods to manage growing workloads with reduced human capital.
By deploying best practices in data optimization and enrichment, Dun & Bradstreet enables tax and revenue agencies to prioritize collections and audits based on non-complying, high revenue businesses – while improving overall operational efficiency.
Improved Collections Through Data Optimization
In addition to fighting fraudulent activities, tax and revenue agencies are also faced with extreme budgetary pressures – shrinking receipts from taxes, permits, fees, fines, and tickets are causing a decrease in revenue and an increase in man-hours devoted to collections. Thus, the need to "thin the haystack" in order to prioritize audit and collection cases is a necessary, yet cumbersome and manual effort.
By leveraging tools and metrics such as the Dun & Bradstreet Viability Rating, tax agencies are able to focus efforts on those businesses most likely to result in successful collections – gaining insights from industry and regional trends, and pre-empting business failure before formal bankruptcy filings.
Tax agencies must stay ahead of entities seeking to "game the system" by misdirecting auditors with business identity theft, complex organizational structures that obfuscate beneficial ownership, offshore tax havens, and assets hidden through intricate networks of shell and shelf companies.
Dun & Bradstreet can help agencies curb abuses and keep operating costs down by implementing multi-layered fraud detection and prevention solutions. Leveraging the world's largest database of global businesses and executives, rigorously maintained through our patented data quality process, public sector agencies can access the deep insights needed to mitigate fraudulent activity.
Tax Information Verified with Third-Party Data
Taxpayer registration systems cannot provide all the information required to flag non-filers and under-filers. The lack of third-party data stunts the government's ability to verify and obtain insight into self-reported information – exposing agencies to outdated and unreliable data. To obtain a complete view of the tax gap, agencies must combine self-reported information with business data provided by objective third parties in order to fill the information gaps.
Further, the agency-wide optimization of data quality is essential for effective interagency data connectivity, productive participation in multilateral Tax Information Exchange Agreements, and to unlock the power of advanced analytics.