The Challenge of Tax Collection
Governments provide services. These services require funds. Yet, these funds are subject to tax collections. We are all familiar with the global issue that is tax evasion. At the same time, we are all familiar with the fact that many perceive taxes as being unnecessarily steep, even in countries where they are not. So, what can a government do? How can it try to collect if not all it is owned, at least parts of it?
All governments around the world have tax collections units, conducting research into debtors, sending payment requests, offering settlements and so on. This process is costly and time-consuming and operators that would be much more useful going after actual tax evaders or black funds are constrained to do repetitive, boring jobs.
Automation Through AI
What if the everyday process could be automated? What if a system could send payment reminders, draft settlement offers, scan the surface web for indications of potential evasion? That is something artificial intelligence can do, as long as it is fine-tuned.
ASSA aims at fine-tuning existing large models to deliver the absolute best result to automate those tedious operations. ASSA is dedicated to training its models to: send out payment reminders, offer payment options, draft settlement agreements, and scanning the web for indications of mall-practice. ASSA’s strategy is simple: cooperate with governmental entities to provide a boutique service and result, by re-training the models on the client’s specific successful stories, to draft settlement agreements on the client’s previous experiences.
Strategic Solutions
Yet, ASSA is not simply approaching the client with a request of cooperation; no ASSA designed three clear strategies to match the necessities of different types of governmental entities. Each one has a clear objective and represents a solid solution for that specific government.
The first strategy is to train an on-premises model. These models are always available, but only on authorized networks. While they may not always be at one’s fingertips, they are safe from most external threats. This strategy is the apex for those governmental institutions concerned with citizens’ private information, while retaining a low energy consumption.
The second strategy is to train an on-cloud model. This solution is always at one’s disposal and is constantly screening the World Wide Web. Not only that, but cloud-based solutions are scalable beyond imaginable. This strategy is most suitable for countries that expect to trace and record an increasing number of transactions and interactions between the government and its citizens.
Finally, the last strategy is the one to implement a hybrid model. This model merges the same advantages of the on-cloud model with the safety and transparency of blockchain technology. This strategy allows us to have a fully immutable digital trace of interactions. This system reduces the possibility of litigation to zero, and it is the most suitable one for governments concerned with maximum transparency.
ASSA’s Value Proposition
One could ask: that’s great, but governments already do all of that, they have employes exactly for these tasks, why would you need ASSA? The answer is that these operations, as aforementioned, are time-consuming, they distract the labor force from more impendent tasks. ASSA is not going to replace humans, it’s a tool. By automating solicitations, settlement offers and so on, officers can refocus on tracing actual wrong doings. These frees up time, resources, and energy, while increasing tax collection by a projected at least 15%.
A Future-Ready Partner
At ASSA, we specialize in precision fine-tuning that helps organizations stay ahead of tomorrow’s most complex challenges. From boosting tax-revenue efficiency and advancing sustainable environmental solutions to unlocking the full power of AI in forward-thinking law firms, our team blends cutting-edge analytics with deep domain expertise to deliver measurable results. Partner with ASSA to gain a future-proof strategy, elevate operational performance, and lead in an era where data-driven innovation decides who wins.