Tax authorities deploy AI machine learning and RPI to detect VAT fraud
Romania’s Minister for Digitalisation has claimed that the use of Artificial Intelligence machine learning and Robotic Process Automation (RPA) has increased the country’s VAT receipts by between 0.9% and 1.0%.
The tax office has been using AI, ERPs, robots that automatically process data and correlate it to have relevant financial data, to increase VAT collections.
Romania is joining a long list of jurisdictions using AI for VAT , helping in a range of activities including:
- Detecting fraud with predictive modelling
- Improving experiences for tax payers using chatbots
- Raising operational efficiencies with trend and sensitive machine learning analysis
See have VATCalc is using AI for tax advice and getting VAT calculations right.
Romania has one of the largest by proportion VAT Gaps. In January 2024, Romania e-invoicing is being introduced to help reduce the deficit further.
Examples of tax authorities using Artificial Intelligence
- Italy, possibly the most fervent users of AI for detecting tax evasion, last year identified over 1 million high-risk cases with AI-driven data analysis. This includes a latest algorithm that cross references financial data to identify taxpayers at risk of not paying. Its VeRa algorithm compares tax filings, earnings, property records, bank accounts and electronic payments looking for discrepancies. High-risk taxpayers then receive a letter asking them to explain the differences. The more data VeRa processes, the smarter it becomes.
- Vietnam has announced that it will be adopting Artificial Intelligence before the end of 2023 to help identify tax fraud. This includes, for example, to flag firms that issue invoices too often, for unusually high amounts or in other ways indicating attempts to slash taxable revenue.
- Australia claims to have identified over $530 million in unpaid tax bills and prevent $2.5 billion in fraudulent claims using AI models, including deep learning and natural language models.In addition to detecting underpayments, the ATO’s AI systems have also been utilized to combat GST fraud. This includes the ATO has employing gradient-boosting machine learning models, which have been successful in identifying fraudulent behavior patterns.
- US, the Inland Revenue Service has drawn-up a second-half 2023 plan to adopt Artificial Intelligence technologies and algorithms. It will be adding AI tools to identify taxpayers who make $1 million and up, and have more than $250,000 The IRS’ initial focus will be using AI analysis to replace existing paper-based reporting and returns. Its existing Modernized e-File (MeF) system already accepts 76% of paper tax returns processed without human intervention. This next phase will be about experimenting and adopting AI models to extract valuable information from this exercise.
- India from May 2023 is using AI to identify fraudulent applications for input tax credits via false GST registrations. The central government’s Business Intelligence and Fraud Analyst (BIFA) site, the e-way portal, and the Rajasthan government’s Business Intelligence Unit (BIU) would collaborate to detect GST numbers that appear to be false.
- India‘s Income Tax Department is using AI to identify falsified income tax deductions. It uses algorithms designed to identify unusual ratio’s between income and political or charitable donations.
- Malta, UK, Canada, the Netherlands and Ireland use an AI system that daily compares wealth based on public sources with that declared in their VAT and tax returns. It also sources public registers, bank accounts (in limited circumstances) to identify undeclared assets and spending.
- Sweden deploys AI to identify and highlight tax risk issues when businesses apply for new incorporations. Since 2021, it has been able to review for tax avoidance flags in registration applications. This has also helped speed-up the application process by reducing the manual time required in reviewing documentation.
- Poland’s System Teleinformatyczny Izby Rozliczeniowej (STIR), analysis data provided daily by banks and credit unions report account data and clearinghouse data on a daily basis for all transactions carried out by taxpayers. It enables the National Revenue Administration (NRA) to detect potential carousel frauds in near-real-time, versus the two months that might have been needed previously.
- France uses AI satellite image scanning to identify signs conspicuous consumption. This can include multiple cars or swimming pools appearing at residents of person under tax investigation. This is particularly useful for local direct taxes (real estate tax).
- Singapore’s Inland Revenue Authority has developed an in-house network visualiser with graph database as an underlying technology to address its auditors’ needs. This tool provides auditors with customised functionalities to analyse intricate, multi-layered relationships between entities during audits/investigations. It can also uncover relationships more than 10 connections deep in a real-time manner.
- Xenon is a tool used by six European countries to investigate tax evasion based on internet searches and surveillance. It was originally developed by The Netherlands
- Brazil has been using AI behavioural insights (called ‘High Performance Inspection’ (FAPE)) to analyse the outcomes of varying standard tax letter requests to taxpayers. It has been evaluating the response of the taxpayer based on their particular background and circumstance to determine the optimum tax communications tone and lever of affirmation. From this, the authorities are able to determine the best approach to take with future taxpayer queries or audits.
- Aside from using AI to detect potential tax fraud or errors, most authorities are now using AI to assist the efficiency of their own compliance and administrative activities. This can include recruitment processes. Countries such as Canada and Singapore are leading the way on this.
- As common on must large private sites, the tax authorities are increasingly using AI-driven virtual assistants. The list of countries includes: Spain, Peru, Australia, Canada, the United Kingdom, Ireland, Finland, Sweden, Latvia, Estonia, the Republic of China, Russia, Singapore, Guatemala, Chile, Mexico, Costa Rica, Colombia and Brazil.