A new predictive technology using geospatial data, improves valuation model accuracy
BOSTON, Jan 7th, 2021 — Paper Crane’s foundational Geodatacube architecture and integrated AI algorithm stack have opened new doors for real-estate investors with its optimized advanced analytics on geospatial data. The Paper Crane platform can reduce the resources needed to go from raw data to actionable insights to only to one machine, one person, and a few hours. The location intelligence company has found a way to drastically improve on automated valuation models (AVM) like the Zillow Zestimate.
Historically, geospatial data has been a mainstay in military and government decisions, with broad applications to intelligence gathering, public safety, land and resource management, and urban planning. For many years, inherent complications and technological limitations involved in collecting, storing, and analyzing these data have limited their application to organizations with large financial budgets. However, as communication networks, computational power, and data storage has become more accessible, the collection of time and place data about almost any event or thing has exponentially increased.
Data is accumulating from traditional resources like satellite imagery and from rapidly expanding networks of location sensors, mobile devices, and social media. The increasing penetration and adoption of Internet of Things (IoT), machine learning, big data, artificial intelligence (AI), and services like AWS, have created a new industry for data analytics, and a huge opportunity for the geospatial analytics market. The global geospatial analytics market size was valued at USD 51,700.7 million in 2018.
A technological gap, however, has left even the largest organizations unable to interpret this expanding suite of data to make better strategic and tactical decisions. New technical advances in predictive data analytics have closed this gap. This has opened multiple new opportunities for leveraging location intelligence, including the ability for real estate investors to identify and capitalize on underpriced real-estate assets.