Challange: Data overload
There’s no doubt that the data exists on real estate pricing and sales. The challenge is getting access to the most accurate data, and then analyzing it with the best prediction modeling possible. That’s overwhelming for most data scientists, let alone commercial bankers who have other tasks to deal with.
A recent Frost & Sullivan report explained how it is necessary to bridge the gap between data scientists and business pros like those in commercial finance and real estate. “The goal is to help organizations of all types discover and model patterns in their own data (and data they can get), so that profitable optimizations can be made to related business processes and systems,” according to Big Data & Analytics Analyst Sandy Borthick.
Gnowise Solution: Superhuman data analysis
Predictive analytics pulls together massive amounts of data and artificial intelligence to help deliver better value on client investments. With Gnowise predictions, hundreds of data series are taken into account, and this can be combined with other bank data for better user experiences.
Further, Gnowise uses unique machine learning and data science simulations that can be adjusted to factor in the latest economic factors. Combined with all that valuable data and this platform can be considered superhuman.
Early adopters of this technology will have a competitive edge. According to Borthick, “Data is all that matters and financial service providers are being left behind with legacy systems. Large tech firms and FinTech start-ups are leading in all of the major growth services, and data network effects will mean laggards can never catch up.” The banks that adopt the right tools, access the best quality information and that can leverage it to make better customer experiences will be the ones that rise to the top.