Improving Real Estate Data Quality Through Natural Language Processing

Why NLP?

Processing huge quantities of repetitive data quickly and accurately is challenging to human beings. The more unstructured that data is, the more difficult the remediation becomes and the higher the error rates. Machine learning addresses this problem working with standardised and structured data, as well as transforming unstructured data enabling accurate processing of enormous quantities of data that could previously only be accessed via error prone and time-consuming manual processes.

Natural Language Processing (NLP) is a division of computer science in which the contents of written documents can be understood and processed by computers - including all our human nuances, spelling mistakes, colloquial terms, and huge variety of languages.

In real estate, NLP is increasingly being used to collect, remediate and analyse enormous quantities of unstructured data from a variety of internal and external sources regardless of format or language in a fraction of the time and with much greater degrees of accuracy, security, and oversight than current manual processes.  If you’re managing assets this enables you to quickly and accurately build, and constantly update, a detailed digital image of your real estate portfolio promoting better investment, lending and management decisions.

The Data Challenge

Investing in, owning, and managing real estate involves making economic decisions based on asset-specific, portfolio and market data. Comprehensive, accurate and complete data will result in more informed decisions and better results. It is important to understand the shortcomings of available data and attempt to remediate and enhance the data at the onset, as well as regularly maintain and update throughout the life of the investment. Currently, real estate owners and managers are faced with the challenge of dealing with incomplete, outdated, and conflicting data resulting in considerable time and resources being required to manually remediate these issues.

Why Remediate? 

Accurate, timely and relevant data enables better decision making, empowering value creation for real estate investors and financial institutions. Data remediation helps institutions reinforce their data and comply with regulatory requirements appropriately as well as reducing the resources, time, and associated costs required. It supports the identification of data that may be sensitive, valuable, or improperly used and directs the accurate data to the right endpoint. Remediation empowers advanced analytics platforms so that the right data is made available faster to the decision maker.

Digital Transformation

To have a comprehensive understanding of a real estate asset through its investment lifecycle, you need to look at a whole set of documents such as: title deeds, valuation reports, lease agreements, permits, floor plans etc. However, to successfully achieve this in a secure suitable format, you need an omnichannel approach, given the multiple different sources and formats. Information needs to be extracted, verified, and stored. The higher the number of assets, the larger the volume of documents which requires more resources and investment.

In 2020 the Covid 19 pandemic  highlighted the weaknesses in the real estate investment and lending markets, when the ability to physically meet a client, inspect an asset and access hard copies of documents was no longer an option or a simple process. The pandemic inadvertently accelerated the digital transformation of the real estate industry, forcing institutions to evolve their processes to keep up with the market. Integration of various AI technologies such as Machine Learning (ML), Natural Language Processing (NLP) and Computer Vision, as well as general data analytics, have become essential for real estate businesses to be successful in the long run.

NLP & Real Estate

Real estate valuation reports and agents’ listings contain key information about the property such as the property type, location, market value, built-up area and so on. This information is central to investment and management decision making. Using NLP, allows for rapid remediation, analysis, and actioning of huge amounts of data in a short period of time to deliver the information needed to make the most effective decisions.

Real estate valuation reports and agents’ listings contain key information about the property such as the property type, location, market value, built-up area and so on. This information is central to investment and management decision making. Using NLP, allows for rapid remediation, analysis, and actioning of huge amounts of data in a short period of time to deliver the information needed to make the most effective decisions.