Connecting state and local government leaders
COMMENTARY | Governments can be unaware of whether they are receiving the correct revenues from cannabis sales. But there are options available to help agencies root out noncompliance, improve forecasts, and potentially up collections.
Small tax revenue differences can have big impacts on the people state and local agencies serve. When states identify tax noncompliance it can result in a few million dollars in additional revenue that can benefit residents. For example, recouped revenue could mean hiring more teachers in an underserved locality or more frontline workers to help vulnerable populations.
This is especially relevant when it comes to tax revenues from marijuana sales.
A significant benefit of legalizing marijuana is the tax revenue it produces. However, many agencies don’t know whether they’re collecting all the marijuana tax revenues they should be. That means they could be leaving money on the table. It also means they can’t demonstrate to legislatures and voters that marijuana legalization is delivering on its intended advantages.
What agencies need is an effective strategy for identifying noncompliance, rooting out fraud and forecasting tax revenues for marijuana sales. Fortunately, solutions and best practices already exist that can enable them to do that.
Cannabis Tax Revenue Challenges
As of February 2022, 37 states, three territories and the District of Columbia had legalized medicinal cannabis products. As of November 2022, 21 states, two territories and D.C. had enacted measures to regulate recreational cannabis use.
In many states, marijuana tax revenue generates funding for social programs. One way to ensure states are collecting the correct amount of tax revenue so that these programs have the necessary funds to operate is to identify tax noncompliance and enforce compliance. They also need to forecast marijuana sales tax revenues and budget social programs accordingly.
That’s easier said than done for two reasons. First, states need a flexible technology solution that maps to their taxation requirements. Second, states need a data governance solution that allows them to share information across agencies. In some states, marijuana cultivators and distributors share seed-to-sale information with one agency and sales data with a different organization. This information should be shared and cross-checked.
In Colorado, for example, the department of revenue manages marijuana licensing and taxation. But in Arizona, licensing is handled by the department of health, while taxation is under the purview of the department of revenue.
In addition, Colorado levies an excise tax when cannabis is transferred from grower to retailer, plus a sales tax at the point of retail sale. Arizona also has excise and sales taxes, but both are applied at the point of sale.
Many states use seed-to-sale tracking programs to help with cannabis compliance. They give states visibility into the cannabis supply chain to prevent criminal activity. But many of these systems aren’t designed to ensure sales tax is being collected, and they usually don’t integrate with state integrated tax systems.
Available Technology and Best Practices
Given the pressure to collect taxes and the complexity of regulations, how can states enforce compliance and predict revenues from marijuana sales? By leveraging existing solutions that enable agencies to capture data, perform predictive analytics and root out fraud.
States can apply this strategy and available technology to marijuana sales. Combining data streams and employing advanced analytics can enable agencies to flag probable cases of fraud for further investigation. It can also allow them to better predict tax revenues from marijuana sales that can benefit resident-focused programs.
What types of data sources could agencies use? They could compare historical sales, employment, and tax data from similar retail businesses to those of cannabis dispensaries. Other data points agencies could use to detect fraud include noticing:
- Multiple dispensaries in the same geographic area reporting similar revenue but paying very different taxes.
- Dispensaries with numerous employees, which would indicate a high-volume business, reporting very low sales.
- Dispensaries reporting low sales but making high deductions using the same accounting firm.
In other words, states can synthesize data from multiple agencies and systems to eliminate data silos. They can take advantage of data they’re already generating to identify anomalies, uncover coincidences and gain new insights that indicate possible fraud.
Once they achieve that holistic view, agencies can make better predictions and gain better budget certainty to fund programs that benefit residents.
Dr. Peter Arena, SVP at GCOM, has nearly 20 years of experience working in the fields of data mining and machine learning—with particular expertise in the application of intelligent algorithms for identity theft and fraud detection. Jen Galbreath is a senior consultant at GCOM working primarily on fraud detection and mitigation in personal income tax.
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