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Edited by Ashley Connell

Leasehold Enfranchisement Solicitor at Hetts

Leveraging Artificial Intelligence for Lease Extension Valuations

"Innovation distinguishes between a leader and a follower."
— Steve Jobs

The landscape of property valuation, particularly in the realm of leasehold enfranchisement and lease extensions for flats, is poised for a transformative shift with the integration of Artificial Intelligence (AI). As a professional specialising Leasehold Enfranchisement claims, I have witnessed the complexities involved in determining the premium for lease extensions. The intricate calculations, consideration of numerous variables, and the need for accurate forecasting make the process both time-consuming and costly. AI presents an opportunity to streamline this process, enhancing accuracy and efficiency while still relying on professional oversight for final determinations.

The UK government has suggested the creation of a lease extension calculator and hinted at altering the interest rates applied to these calculations. Could an AI model assist with this initiative? If not directly, could it support valuers involved in enfranchisement claims by providing substantial amounts of important data in a structured manner to aid their calculations, arguments, and negotiations?

The Complexity of Lease Extension Valuations

Lease extension valuations require a deep understanding of various factors, including:

• Property Comparables: Evaluating similar properties based on size, amenities, location, and other features. An AI model can scrape all sold property data and cross-reference the sold price data with the estate agents marketing listing to account for differences, such as floor area, garden space, parking, years remaining on a lease, balcony, mutiple bathrooms etc. The AI model could even scan an estate agents floor plan to fully understand the nature of the property. It can take into account how long the property had been advertised before it sold, how many times the price was dropped and the final selling price as a percentage of the asking price.
• Negative Influences: Accounting for factors that may detract from property value, such as noise pollution or undesirable surroundings, rising crime rates, job losses in the local area and even planning applications for undesrible projects such as a new runway and a projected air flight path. Declining results in school exams, a planning application for a night club, a news article about a plan to build a new sewerage plant... the possibilities are endless. Artificial Intelligence (AI) has the capability to scour a wide array of sources such as planning websites, local news outlets, Twitter, development plans on both local and national levels, infrastructure project sites, web forums, and noise maps. By continuously monitoring these platforms, AI can gather real-time insights on future projects like residential developments, infrastructure expansions, or new commercial zones. AI can also assess factors like future job creation or potential job losses, examining how these could impact housing supply and demand. Machine learning algorithms can then weigh these factors based on past patterns and learned experiences, identifying trends or risks that might otherwise be missed. AI systems synthesize this complex web of information into concise, easy-to-understand reports, helping users make informed decisions by highlighting the most relevant factors shaping a property’s future value.
• Capitalisation Rates: The capitalisation rate is used to convert a stream of future ground rent payments into a present lump-sum value, reflecting the return an investor would require on a property investment and accounting for the risk associated with receiving future ground rent payments. A 5% capitalisation rate is commonly used because, historically, it has been supported by market transactions and accepted in tribunal decisions, reflecting the typical return investors expect from ground rent investments, which are generally considered low-risk. This static approach is not ideal because it fails to account for the significant changes in the economy and future outlook. What if 5% becomes too high or too low? The UK's economy today is vastly different from what it was 15 years ago, with shifts in interest rates, inflation, property market dynamics, and financial regulations. Relying on outdated capitalisation rates can lead to valuations that do not reflect current economic realities, potentially causing unfair outcomes for both leaseholders and freeholders. Adopting a sophisticated algorithmic model that adapts to contemporary economic conditions, and transparently explains its reasoning for human review, should certainly be considered a more fair and just method for determining capitalisation rates. Could the government implement this in there own model? They have repeatedly stated that they will create their own 'lease extension calculator' under the new reforms.
• Deferment Rates: Determining the rate to defer the freehold reversion. This rate (usually 5% as per the Sportelli case) is designed to be reflective of a risk-free rate, such as the return on a risk-free investment, like government bonds, also the expected real in crease in proeprty values over time as well as a 'risk premium' to compensate for risks like propety market volatility, management issues and liquidity. None of these factors are fixed and change from year to year and decade to decade. A model could consider economic factors, such as current inflation rate, bond interest yields and predicted rates looking at the futures market. Is it really fair to still rely on Sportelli from 2007 even though we are now in very different econmic environment? Double digit inflation is now real, and with the goverments debt to GDP ratio now at a level that makes it impossible to service without diluting the money supply, it may only be a matter of time before inflation of 50% or more a year becomes a reality, as is happening in more and more other countries, such as Argentina. Uncontrolled public spending has future consequences.
• Future value: Lease extension valuations involve calculating the loss to the freeholder, by discounting the future value of their reversionary interest back to present-day terms using an appropriate deferment rate. This ensures that the freeholder is fairly compensated for the delay in regaining possession of the property due to the lease extension. When a leaseholder extends their lease, the freeholder loses the right to regain possession of the property at the original lease expiry date. The lease is being extended, effectively postponing the freeholder's right to receive the full value of the property. To compensate the freeholder for this loss, we need to calculate the present value of the delayed reversionary interest. Therefore it is not just the value of the flat today that is important, but if we can attempt to predict the future value by considering factors that will impact the value of the property tomorrow, then the valuation model becomes more accurate.

AI's Role in Enhancing the Valuation Process

AI can revolutionise lease extension valuations with:

1. Rapid Data Analysis: AI algorithms can process vast amounts of data in real-time, including recent sales, market trends, and economic indicators. This ensures that valuations are based on the most current information.
2. Geo-Location Precision and Future Market Projections: AI can utilise geospatial data to assess environmental risks:
   • Flood Risk Assessment: AI models can analyse topography, climate data, and historical flood records to predict flood-prone areas.
   • Air Quality Monitoring: AI can process data from air quality sensors to determine pollution levels, which can affect health and property desirability.
   • Climate Change Projections: Long-term climate models can predict areas likely to be affected by extreme weather events.
3. Infrastructure and Accessibility Issues
   • Traffic Congestion Analysis: AI can use traffic data to assess congestion levels, which may deter buyers due to longer commute times.
   • Public Transport Changes: Predictive models can evaluate the impact of changes in public transport routes or services. Will a new runway, picked up by scanning planning applications and/or news, have a flight path impacting the value? Or perhaps a new bypass near a residential zone.
   • Connectivity and Broadband Speeds: AI can map internet speeds and connectivity issues, essential for remote working lifestyles.
4. Social Media and Sentiment Analysis
   • Community Sentiment: NLP algorithms can analyse social media platforms, local forums, and review sites to gauge public opinion about a neighbourhood.
   • Emerging Social Issues: AI can detect rising social tensions or community disputes that may affect property values.
5. Legal and Regulatory Factors
   • Planning Regulation Changes: AI can monitor legal databases for changes in planning regulations that might allow undesirable developments nearby.
   • Property Legal Disputes: AI can identify properties involved in legal issues, such as ownership disputes or easements, affecting their value.
6. Demographic Shifts
   • Population Trends: AI models can predict demographic changes like ageing populations or declining birth rates, impacting future housing demand.
   • Income Level Changes: Economic models can forecast shifts in local income levels, affecting affordability and market dynamics.
7. Educational Infrastructure
   • School Performance Declines: AI can track and predict changes in school performance metrics, a critical factor for families.
   • University Closures or Relocations: Impact on rental markets and local economies can be significant.
8. Health and Safety Concerns
   • Proximity to EMF Sources: Analysis of electromagnetic field exposure from power lines or mobile phone masts, which some buyers may avoid.
9. Future Development Plans
   • Undesirable Commercial Projects: AI can predict the likelihood of industrial facilities, waste plants, or prisons being built nearby.
   • Urban Decay Indicators: Machine learning models can identify signs of urban decay, such as increasing vacancy rates or declining maintenance.
10. Market Saturation and Competition
    • Overbuilding: AI can analyse construction data to predict market oversaturation, leading to price declines.
    • Repossessions: High rates of property repossessions can depress local property values.
11. Historical Property Issues
    • Previous Damage: AI can access databases for past incidents like fires, floods, or subsidence issues that may not be apparent.
    • Building Material Concerns: Identifying properties built with now-banned materials (e.g., asbestos, certain claddings).

Professional Oversight Remains Crucial

While AI can significantly enhance the valuation process, it does not replace the need for professional judgment:

• Final Premium Determination: The ultimate decision on the premium requires human expertise to interpret AI-generated data within the context of current market nuances.
• Legal and Regulatory Compliance: Ensuring valuations adhere to the Leasehold Reform, Housing and Urban Development Act 1993 and other relevant legislation.
• Ethical Considerations: Professionals must consider the ethical implications of valuations, particularly in sensitive cases.

Benefits of AI-Enhanced Valuations

• Accuracy: Improved data analysis leads to more precise valuations.
• Efficiency: Reduces time spent on data collection and initial analysis.
• Cost-Effectiveness: Lowers costs for clients by streamlining the valuation process.
• Transparency: Detailed reports provide clarity on how valuations are derived.
• Fairness: Natural human bias or error is elimanated.

The future of lease extension valuations?

The integration of AI into lease extension valuations offers a promising avenue for enhancing the accuracy and efficiency of the process. By rapidly analysing a multitude of factors and projecting future trends, AI provides valuable support to professionals in the field. However, the role of the RICS surveyor remains indispensable in interpreting data, making informed judgments, and ensuring compliance with legal standards. Embracing AI as a tool rather than a replacement allows for the best of both worlds. Cutting-edge technology combined with professional expertise.

By understanding and leveraging AI's capabilities, we can evolve the practice of lease extension valuations to better serve clients and adapt to an increasingly data-driven world.