Real estate management software provider, RealPage, has recently announced that it has agreed to buy out CRE Gobal Enterprises, a holding company for data analytic solution to institutional real estate owners with more than $500 bullion worth of assets, Hipercept. RealPage has yet to disclose the amount of the purchase. With this acquisition, RealPage will gain the ability to gather real estate deta tech and develop and offer an integrated solution for real estate investors and asset managers throughout the investment lifecycle.
New York-based Hipercept was founded in 2009 to provide advisory, data management, partner management, as well as application management services to real estate owners in the US, Asia, Canada, and Europe.
Management is headed by CEO Colin Kovas, who has been with the firm since 2014 and was previously a director at NewOak Capital.
Additionally, the company provides FUEL, a cloud-based commercial and multifamily real estate valuation cash flow forecasting solution, and Foundation - a data storage, governance, and analytics platform.
Company partners or major customers include insurance companies, pension funds, major banks, and asset management firms.
According to a market research report by McKinsey, real estate analytic technologies provide developers and asset owners with the tools necessary to rapidly gain relevant property insight and take informed actions based on both traditional and recently-emerged non-traditional data points.
Real estate analysts have to sift through numerous records and data points to discern clear patterns and place their bets with few supporting tools, and by the time the investor collects, compiles, and processes the data needed to distill action - the best opportunities are gone.
Moreover, new and unconventional data sources, such as resident surveys, mobile phone signal patterns, and Yelp reviews of local restaurants are becoming increasingly relevant for the identification of “hyperlocal” patterns - granular trends at the city block level rather than at the city level.
Using machine learning algorithms, real estate analytic technologies automate the data collection process by accessing application programming interfaces [APIs] and connecting various databases before preparing the data for analysis.
Other benefits of real estate analytic technologies include pressure-testing expectations for individual properties, identifying individual assets that would hold their value in declining markets, making capital expenditure decisions on specific properties, and comparing predictive-model outputs to the forecast of traditional sources of market information among others.
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