a graphic of computerised houses on a giant AI hand

Garbage in, garbarge out: Poor data quality is hampering the proptech revolution

A new report has revealed that significant data challenges are impeding the progress of the proptech revolution in key global real estate markets - the UK, US, China, and India. 

Researchers at the School’s Gillmore Centre for Financial Technology have produced the report – Disrupting the Real Estate Industry: The Proptech Revolution in the UK, USA, China, and India – and it highlights that while proptech holds immense potential to transform the property and real estate industry, the lack of accessible, high quality data is a major stumbling block. 

Kalina Staykova, Assistant Professor of Information Systems and PropTech Co-Investigator in the FutureFinance.AI Group at the Gillmore Centre, said: “The proptech revolution has the potential to transform the real estate industry, but data challenges are a serious impediment. 

“The report highlights that while technologies like AI, blockchain, and the internet of things are crucial, the true impact of proptech lies in its ability to inspire a new way of thinking about property development, management, and transactions.  

“Traditionally viewed as a supportive tool, proptech is now recognised as a catalyst for innovation, driving efficiency, transparency, and sustainability across the global real estate landscape. 

“But widespread adoption may be difficult to achieve due to obstacles such as lack of quality data, or the reluctance of key actors to share data, as well as a lack of digital infrastructure that can support proptech solutions across less urban areas. 

“Without access to high quality, comprehensive data, proptech companies cannot fully realise their potential.” 

The report identifies several key issues: 

  • Data fragmentation: In all four countries real estate data is often scattered across numerous public and private sources, making it difficult for proptech companies to obtain a comprehensive market view. This fragmentation creates significant hurdles for innovation and market analysis.
  • Data quality: Even when data is available its quality is often inconsistent, limiting its usefulness for developing accurate and reliable proptech solutions. This is particularly prevalent in markets with less developed digital infrastructure. 
  • Data access and sharing: A reluctance to share data, driven by competitive pressures and high access costs, is a significant problem. Proprietary data from private providers often comes with prohibitive fees, hindering innovation, especially for start-ups. 
  • Regulatory compliance: Stringent data privacy regulations, such as the General Data Protection Regulation (GDPR) in the UK, add complexity and cost to data handling. Proptech companies must navigate these regulations carefully, which can slow down development. 
  • Varied data standards: The lack of unified data standards across different regions and organisations leads to interoperability problems, making it difficult to integrate data from various sources. 

The report emphasises that addressing these data challenges is crucial for the future of proptech.  

Moris Strub, Associate Professor of Information Systems and PropTech Co-Investigator in the FutureFinance.AI Group, added: “The advancement of the proptech revolution is apparent in each of the four markets we analysed, with emerging property technologies disrupting the traditional real estate sector.  

“The increased use of AI has created a sense of convenience for customers, which is shared across the four markets. Another trend is the increased focus on green proptech to deliver on ambitious sustainability goals.  

“The UK and US proptech markets remain inherently self-driven, with the Chinese market being underpinned by a level of compliance and oversight. At the same time, India has been dealing with gaps in digital infrastructure which require different proptech solutions. 

“To overcome the data challenges in these markets we recommend promoting data-sharing initiatives across industry stakeholders and developing industry-wide data standards. 

“There also needs to be improved data governance and more investment in digital infrastructure if the full potential of proptech is to be unlocked.”

Further reading:

Can generative AI provide better data for financial models?

Do digital currency projects have public buy-in?

Can Britain move decentralised exchanges into the mainstream?

Why AI could transform peer-to-peer lending for investors

 

Kalina Staykova is Assistant Professor of Information Systems and PropTech Co-Investigator in the FutureFinance.AI Group at the Gillmore Centre. She teaches Artificial Intelligence in Business on a suite of Master’s courses plus Cybersecurity in Business on MSc Management of Information Systems & Digital Innovation. She also lectures on Digital Ventures on BSc International Management.

Moris Strub is Associate Professor of Information Systems and PropTech Co-Investigator in the FutureFinance.AI Group at the Gillmore Centre. He is Course Director for the MSc Financial Technology.

Discover more about Finance and Markets. Receive our Core Insights newsletter via email or LinkedIn.