25 Reasons why HMRC could use AI for umbrella company background checks

Automating background checks to weed out tax-avoiding umbrella companies could save HMRC time and resources compared to manual investigations. It could also save thousands of freelancers financial heartbreak. Here we share 25 reasons why the latest AI should be seriously considered a solution to a decades-old problem.

By using artificial intelligence (AI) for background checks on umbrella companies, HMRC could significantly improve its ability to detect and prevent tax avoidance among umbrella companies, level the playing field for legitimate businesses, and protect freelancers’ rights to benefits and protection from tax fraud. Well, at least we hope it could.

For those who may be nervous about AI conducting such background checks for fear of computer error or hallucinations sometimes found in language models, the good thing about AI is it could supplement and complement HMRC staff investigations. By automating reg flag criteria for any new or existing umbrella company, unethical practices could be spotted before mass damage is done to freelancers and the Treasury’s purse.

Time-consuming tasks could be cut in half so HMRC staff can concentrate on customer support. No more headlines about how the self-employed won’t have the opportunity to talk to HMRC because the tax authority is under-resourced.

The list below is long but it hopefully proves a point or at the very least gets AI specialist contractors talking. Who would be best to develop and implement it? And what could stop HMRC from giving this serious consideration?

Freelance Informer reader feedback welcome

When you go through this list, some points might seem so obvious you may be wondering why is HMRC not already doing this. Some suggestions might prove complicated when it comes to integrating AI with any legacy computing systems.

That’s why we welcome professional and constructive feedback on how AI could be implemented swiftly in the most cost-effective way to stop tax avoidance spurred by umbrella company directors and staff.

And should freelancers be part of the AI development process? We welcome your input.

Red Flag Detection:

1. Solo Directors: Identify umbrella companies with a single director at the time of registration with Companies House, a potential indicator of a company that will not show their full accounts or have enough employees to carry out payroll and benefits.
2. Ghost Directors: Detect non-existent or disqualified directors associated with the company, raising suspicion about legitimacy.
3. Lack of Employees: Analyse payroll data and business activity to flag companies with minimal or no employees, suggesting potential misuse of the umbrella model.
4. Employer Tax Discrepancies: Compare declared payroll with employer tax contributions, identifying discrepancies that could indicate tax avoidance.
5. Unusual Transaction Patterns: Look into financial data to detect unusual transactions, such as high fees or frequent transfers, that could indicate money laundering or other illegal activity.
6. Links to Blacklisted Companies: Identify connections to companies previously flagged for tax evasion or other financial irregularities.
7. Social Media Sentiment Analysis: Analyse social media mentions of the company to identify negative reviews, complaints, or allegations of unfair practices.
8. News and Media Monitoring: Track news and media mentions of the company to identify any negative publicity or investigations.
9. Sudden Business Expansions: Detect rapid growth in a company with minimal resources, raising concerns about potential financial instability or tax avoidance schemes.
10. Sudden Business Closures: Identify companies that abruptly close down, potentially to evade tax liabilities or disappear with employee deductions.

Efficiency and Cost Savings:

11. Reduced Manual Workload: Automate background checks, freeing HMRC staff for more complex investigations.
12. Faster Processing Times: Analyse large datasets quickly, allowing for quicker identification and intervention against potential tax avoidance.
13. Improved Risk Assessment: Provide a more comprehensive and accurate picture of a company’s financial health and potential tax risks.
14. More Proactive Approach: Spot emerging red flags early on, preventing significant tax losses before they occur.
15. Cost-Effectiveness: Automating background checks can save HMRC time and resources compared to manual investigations.

Fairness and Transparency:

16. Level Playing Field: Ensure consistent and objective background checks for all umbrella companies.
17. Reduced Bias: Eliminate potential human biases in the assessment process.
18. Increased Deterrence: Act as a deterrent to potential tax avoidance schemes.
19. Improved Transparency: Provide HMRC with more data-driven insights to inform policy decisions and enforcement strategies.
20. Protecting Legitimate Businesses: AI can help differentiate between legitimate and potentially fraudulent companies.

Additional Benefits:

21. Enhanced Data Analysis: AI can analyse complex financial data and identify hidden patterns that humans might miss.
22. Continuous Learning: Algorithms can continuously improve their accuracy over time as they learn from new data.
23. Adaptability: AI can adapt to changing tactics used by fraudulent companies to avoid detection.
24. Scalability: AI can be easily scaled to handle large volumes of data and companies.
25. Integration with Existing Systems: Solutions can be integrated with HMRC’s existing IT infrastructure.

🪘Are AI-based umbrella company background checks the way forward?

We welcome insightful and informative feedback from freelance AI specialists, application software developers and tax advisers about how they believe AI could help cull dodgy umbrella companies right from the point of registration with HMRC.