In the complex world of mergers and acquisitions (M&A), deals involving property-rich companies present unique challenges. These companies often hold substantial real estate assets, intricate ownership structures, and nuanced corporate (and individual) tax implications.

Conducting thorough financial and tax due diligence is essential to assess risks, uncover hidden liabilities, and ensure compliance across all relevant jurisdictions. Artificial Intelligence (AI) is increasingly playing a pivotal role in streamlining and enhancing this process, making it faster, more accurate, and more insightful. Head of Tax Patrick TR Thornton explains more.

1. Automated Document Review and Data Extraction

AI-powered tools can analyse thousands of documents at a speed and accuracy far beyond human capability. In property-rich acquisitions, this includes reviewing:

• Property ownership and title deeds

• Lease agreements and tenancy contracts

• Loan covenants and security documents

• Historical accounts and tax filings and HMRC correspondence, with overseas tax considerations

Natural Language Processing (NLP) allows AI to extract relevant data points—such as rent terms, break clauses, historic tax treatment, and capital allowances—from unstructured legal, financial, and tax documents. This drastically reduces time spent on manual review while improving precision.

2. Financial Risk Analysis and Anomaly Detection

AI systems can ingest large volumes of financial data and identify irregularities or patterns that may indicate risk, such as:

• Overstated asset values

• Inconsistent depreciation and amortisation policies

• Unrecorded or hidden liabilities

• Cash flow anomalies

Machine learning algorithms compare financial metrics against industry benchmarks and historical performance to flag outliers for further human review. This is especially valuable for property-rich companies where investment property, and rental portfolio, revaluations, and hidden liabilities can distort traditional ratios.

3. Tax Compliance and Optimisation Insights

Acquisitions of property-rich companies often involve complex tax considerations, including:

• Capital gains tax, and chargeable gains to corporation tax, on property disposals

• Stamp Duty Land Tax (SDLT) and Stamp Duty

• Transfer pricing and intra-group transactions

• VAT on commercial properties

AI can assess tax positions and structures by analysing past accounts and tax filings, real estate acquisitions and disposals, and intercompany transactions within group structures.

Advanced tools can simulate post-acquisition tax impacts, identifying potential exposures or opportunities to maximise cash flow and manage working capital of the acquiring company.

4. Ownership and Entity Structure Mapping

Many property-rich entities operate through layered corporate structures involving multiple jurisdictions. AI tools can map these structures using entity recognition and relationship detection. Visualisations of ownership hierarchies help identify:

• Ultimate beneficial owners (UBOs)

• Cross-border tax implications

• Exposure to regulatory regimes (e.g., ATAD, DAC6, FATCA)

This capability enhances transparency and helps acquirers comply with anti-money laundering (AML) and know-your-customer (KYC) obligations.

5. Environmental and Regulatory Risk Assessment

AI can also be trained to scan for environmental liabilities or regulatory red flags by analysing public records, local filings, and ESG reports. For property-rich companies, this can include:

• Asbestos or contamination risks

• Planning permission breaches

• Zoning restrictions

• Non-compliance with energy efficiency standards

Such insights can be crucial for deal pricing, post-merger integration, and risk mitigation.

6. Scenario Planning and Deal Structuring

With predictive analytics, AI can model different deal structures and assess the financial and tax consequences.

For example, should the buyer purchase shares of the company or just the property assets? What would be the impact of a change in tax residency or overseas holding structure?

AI-powered simulations enable deal teams to test various scenarios and make informed strategic decisions backed by data-driven insights.

Conclusion

AI is not a replacement for professional judgment, but it is a powerful enabler of more effective and efficient due diligence.

In acquisitions involving property-rich companies—where the stakes are high and the details are complex —AI helps uncover hidden risks, streamline workflows, and enhance confidence in decision-making at the outset.

As technology continues to evolve, it is poised to become a standard tool in the M&A toolkit, transforming how financial and tax diligence is conducted across the board.

Careful consideration and sensible professional advice should be sought alongside the use of AI in M&A transactions; so please do not hesitate to get in touch.

Please do feel free to contact us if you have any questions; we regularly provide due diligence on a range of business, fund, and property transactions:

Patrick TR Thornton (Partner)

PatrickThornton@childandchild.co.uk / 020 7201 3579

Michelle Lu (Private Client Senior Tax Manager)

MichelleLu@childandchild.co.uk / 020 7201 1886

The information contained in this article is general guidance only. The application and impact of laws can vary widely depending on the specific facts involved. The information in this article is provided with the understanding that the authors and presenters are not giving legal, tax, or other professional advice and services. As such, it should not be used as a substitute for consultation with professional legal, tax or other competent advisers. Before making any decision or taking any action, you should consult a Child & Child professional.