The Federal Inland Revenue Service’s (FIRS) TaxPro Max platform lacks the advanced predictive capabilities needed to detect sophisticated tax fraud and revenue manipulation, a data scientist has said.
Okay News reports that Mr. Emeka Atuma, an independent consultant and trainer in Data Science, made this assertion on Friday at the 10th Blakey’s National Tax Conference held in Lagos. He presented a paper titled “Data and Artificial Intelligence in Administering Tax in Nigeria” at the event.
The Principal Partner and CEO of Management Consulting and Business Advisory Services stated that while TaxPro Max can improve compliance through electronic filing, it cannot accurately identify tax avoidance schemes and more complex problems.
Digital Filing Without Predictive Intelligence
According to Atuma, TaxPro Max largely functions as an electronic filing and payment platform, with little analytical depth to assess the credibility of returns submitted by taxpayers. The data scientist explained that TaxPro Max is a start, but it does not have the predictive analytics to determine whether a filing is fraudulent or whether a taxpayer is deliberately manipulating the system.
He explained that advanced Artificial Intelligence (AI) systems can analyse historical data, detect unusual patterns and flag suspicious filings—such as companies consistently keeping revenue just below tax thresholds to reduce liabilities. However, such intelligence is currently missing in FIRS’ TaxPromax platform.
Atuma’s explanations were in response to a member of the audience who complained about issues with his e-filing where he was wrongly assessed and an inaccurate tax amount was imposed on his firm and was never reviewed in spite of his protests.
Why AI Matters For Tax Administration
Atuma noted that AI combines data science, machine learning and deep learning models to analyse large datasets and identify compliance gaps. Once reliable data is available, AI can distinguish between compliant taxpayers and those at high risk of evasion, allowing tax authorities to focus audits where they matter most.
However, he stressed that AI does not work in isolation, adding that AI can only function where quality data exists. He noted that poor data integration across government agencies could undermine tax collection efficiency.
The expert identified fragmented taxpayer data as one of FIRS’ biggest constraints. Information on the same individuals and businesses is spread across multiple agencies, including the Corporate Affairs Commission (CAC), National Identity Management Commission (NIMC) and the Central Bank of Nigeria (CBN).
He insisted that until these sets of data centres are aggregated, cleaned up and standardised, they might not be good enough to work with in advanced AI analytics. He also cited infrastructure deficits—unreliable power supply, limited bandwidth and outdated legacy systems—as barriers to deploying advanced analytics at scale.
Rather than scrapping TaxPro Max, Atuma recommended extending the platform by embedding machine learning algorithms behind it. This would allow the system to analyse stored tax returns, flag anomalies and support risk-based audits without replacing human judgement.
Atuma added that even the most advanced AI system would struggle to capture Nigeria’s large informal economy without broader data collection mechanisms. To address this, he suggested expanding data capture points beyond banks to areas such as SIM registration, healthcare access and other everyday services that require identity verification.
