22 Jan, 2021
Tax authorities around the world are going through a period of digital transformation. Whether it’s to implement taxpayer risk profiling, increase citizen engagement, reduce the cost of debt collection or prevent fraud, data is at the centre of all of these challenges. When governments have access to the right information, they can implement successful tax strategies. With actionable insights driven technology, they have the power to personalise those strategies, improve voluntary compliance and make better informed decisions about the future.
An approach underpinned by machine learning, data science and AI
With an accelerated drive towards digital and cloud-based programmes, more complex data is being produced and made available. An actionable insights driven transformation approach enables public sector organisations to manage these large datasets, ensuring compliance, accuracy and efficiency.
By understanding the demographic profile, personal preferences and digital awareness of citizens, appropriate intervention and engagement strategies can be tailored to improve voluntary compliance, and reduce the cost of debt collection. An actionable insights driven transformation approach automates the entire data analysis workflow, providing more efficient and comprehensive insights. Free from bias, human errors, and time constraints, data remains compliant, with the entire process becoming more efficient and cost effective. The advantages of this approach can be seen across the public sector, from tax authorities to local councils, to benefit and entitlement agencies, as well as licensing bodies.
Transforming the way tax authorities operate
Tax authorities can benefit considerably from an insights driven transformation approach, which enables them to identify trends to improve voluntary compliance. For example, machine learning is an actionable insight driven technology, a type of artificial intelligence (AI) that processes data without needing to be programmed in a specific way. By thoroughly analysing data through technology like machine learning, the system builds an algorithm based on the patterns it recognises. It’s able to distinguish between taxpayers who voluntarily comply and those that require frequent reminders. In doing this, the system identifies taxpayer trends. By monitoring behavioural patterns, machine learning also picks up areas of inconsistencies, or potentially fraudulent activities, which can be dealt with immediately.
Insights driven technology empowers tax authorities to determine who pays on time, to what level of intervention they respond to, and how well existing services and systems work. The data is used to re-calculate behaviour models and risk profiles and predict future behaviours and patterns, enabling tax authorities to tailor their approach to individual taxpayers, encouraging voluntary compliance at earlier stages of the tax lifecycle.
This solution is used to drive operations and embed continuous learning and improvement into debt processes. The decision rules engine assigns customised sequences of collection interventions to each debt, which the debt management system allocates to the relevant channel. By integrating machine learning with legacy batch-processing, tax authorities achieve flexibility and speed, whilst, at the same time, maintaining resilience across business-critical systems, which thousands of employees rely on to do their jobs.
Benefits of an actionable insights driven transformation approach
By utilising AI and machine learning to identify trends in taxpayer behaviour, tax authorities can devise risk profiles and trace fraudulent activities, which, in turn, empowers them to implement appropriate enforcement and preventative measures. Conventional debt processing systems could be replaced with innovative digital analytics solutions, which use customer behaviour insights to mass customise debt collection interventions. Tax authorities benefit from intelligence, flexibility and speed, with the ability to implement changes at low cost, analyse their effectiveness, and continually improve the success rate of each business activity. Time-consuming and costly taxpaying delays could be replaced by predictive analytics, data-driven processes that have voluntary compliance at their core.