Tax agencies have a limited amount of resources to pursue tax compliance activities (collections and audit). Because of this resource limitation, they are required to build criteria to determine which individuals and businesses to select for audit and which collection cases to focus their efforts on. Typically, this selection is based on experience that informs agency leaders on the types of businesses that generate productive audit leads and collection cases. While the selection process typically utilizes available data, cases are primarily selected based on experience, intuition and business rules, rather than using predictive, mathematically generated analytical models.
Tax Compliance – Why Use Analytical Models at Tax Agencies?
Predictive, analytical models produce better outputs over experienced based “expert” models by increasing the accuracy of the model. . This results in more productive workloads and outcomes. Analytic models can:
· Increase customer service by minimizing interventions on cases that don’t need tax agency staff to achieve collections;
· Increase staff productivity by assigning them to better cases where their expertise and effort is more likely to result in additional dollars collected;
· Reduce wasted efforts by reducing the no-change audit rate, and reducing the time a collector spends on cases where their intervention does not affect the collection rate; and
· Increase long-term voluntary compliance by maximizing current collections and affecting long-term behaviors that increase future collections.
Tax Compliance – Predictive Analytical Models. Three Types
There are many different types of analytical models which a tax agency could use, including:
· Similarity Models. These look for taxpayers that are statistically similar to cases that had a specific behavior in the past (compliant or non-compliant).
· Outlier Models. These models look for taxpayers that are statistically anomalous. While this doesn’t mean they are non-compliant, they can merit a review to determine why they are different from their peers.
· Prescriptive Models. Prescriptive models are different from the prior Predictive models, because prescriptive models look more holistically for the best overall set of decisions, rather than identifying individual cases which may be productive. A prescriptive model also helps allocate resources between workloads, taking into account your constraints to identify the best set of strategies to maximize your overall result.
The remainder of this document will talk to the specific areas of a tax department that can benefit from analytical models.
Tax Compliance – Tax Analytics Opportunities for Audit
Auditors tend to be the highest paid and most specialized resources within a tax agency. Agencies have a limited number of auditors, and therefore must be careful with allocating these resources. Analytical models provide an opportunity to increase both revenues during the current fiscal year as well as future voluntary compliance.
Analytical models can identify audit candidates that have a statistical similarity to past productive audits. These models can score for dollars assessed, dollars collected, or even dollars generated per audit hour, allowing the agency to maximise their return. They can also be used to minimize the impact to compliant taxpayers, trying to reduce audits that result in no or limited changes.
Tax Compliance – Tax Analytics Opportunities for Collections
Collections is another area with many opportunities for analytical models. Collection management invariably has more inventory than staff available to work cases. Therefore, they must determine which cases to assign for treatment and when to assign the case. Typically, cases are assigned based on dollar amount owed, but , predictive models can also help determine who will self-cure and who needs more attention.
Models can also help determine who to contact, when to contact them and what message to deliver. . By combining analytical models with behavioral science (varying notice texts) you can vary your notices by taxpayer, using the language most likely to result in success for each taxpayer communication.
Finally, analytics can predict which taxpayers are most likely to need the most aggressive collection techniques. While the Government must provide due process to all debtors, if a segment of taxpayers are unlikely to pay through billing, then the analytics can help the agency move these cases through to enhanced collections faster, without expending significant staff time on phone calls that are unlikely to result in collections.
Tax Compliance – Tax Analytics Opportunities for Customer Service
Tax agencies also have limited resources to provide proactive customer service. Analytics can act almost like a crystal ball to predict which taxpayers are likely to encounter future tax issues. For example, if statistics show that a new business in a specific industry is more prone to under-reporting or not registering for specific tax types, the tax agency can proactively send letters, make phone calls or organize industry workshops for businesses that meet that profile, helping them understand their upcoming tax obligation before they encounter an issue. The taxpayer will better understand their obligation and they will know the government is paying attention, which will lead to higher voluntary compliance before encountering problems.
Tax agencies can also use analytics to measure the impact of their customer service, the effectiveness of different channels (e.g., in-person meeting, phone call, or letter campaign), and the effectiveness of different messages. These can help shape future interventions by testing different strategies and utilizing the most effective one.
In conclusion, tax agencies are under continued pressure from their legislatures to do more with less. Innovations in deploying analytical models provide the opportunity to enhance customer service, revenues collected, and achieve greater compliance, not by working harder, but by working smarter.
Enjoyed this blog? Why not read some more on the topic of tax and analytics:
Improving Tax Office Data-Matching
Tax Evasion: Have We Learned the Panama Papers Lesson?
Identifying Tax Fraud through Social Network Analysis
Tax Agency Optimization – What Are the Benefits?
FICO Survey: APAC Banks Expect Rise in Tax Evasion