Lease abstraction and extraction is becoming increasingly complex while demands are rising for better data quality for portfolios of leases in multiple countries or asset types. We looked at the future of data standards for lease abstraction to provide our perspectives as a leading provider of artificial intelligence and machine learning tools for lease abstracting and extraction.
Several organizations have been building data standards for lease abstraction over the past years in a bid to address the emerging needs of the industry. These organizations have been at the forefront of development and implementation of real estate information exchange standards, including those for commercial real estate.
In this paper, we look at the trends driving the industry towards a standard data model, its advantages, the challenges that hinder lease abstraction standardization, and how standard data models can support new and emerging use cases.
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