Gnyana's Big Data Analytics

The biggest challenge in Real Estate Investment is Price Discovery. Other organized markets in Equities, Bonds, Commodities, etc. have evolved an efficient price discovery mechanism by virtue of its institutionalized structure which provides liquidity – multiple buyers and sellers arrive at a consensus price every fraction of a second. However, any direct investment in Real Estate does not have the benefit of liquidity, which implies a fairly diffused pricing probability curve. Structured information of historic transactions is available, but there is no qualitative filtering of variables that may influence the price differentials even for properties in the same geographical location.

For an otherwise similar construction, attributes that are found to influence specific capital values include softer variables like – proximity to malls, parks, schools, public transportation systems, hospitals, etc. Big Data analytics in Real Estate involves compilation, analysis and visualization of disparate information that would influence the capital/rental values of such properties, and affecting a median trend for all such properties across the nation.

Investment opportunities arise when properties get listed at values that are out of sync with these trending values at each given location. And Risk Mitigation happens when, other things remaining constant, investment is done at price points that offer the maximum “Margin of Safety” relative to their median values. On the rental platform, a similar proposition arises when capital values tend to disconnect with the underlying rental values on offer, given a specific backdrop of loan funds available.

Gnyana offers a complete dashboard that enables a user to monitor properties across the nation on a real-time basis. Our analytics platform can monitor the user’s investment on a real time basis. Informed decision making is facilitated by use of advanced statistical algorithms to generate expected values on the property stretching over 10 years into the future, based not just on historic price trends, but Big Data inputs of variables that can influence the same. Like for example, trend of commercial or facilities development of the nearby areas (like setting up of a Metro line, or establishment of a commercial zone, etc.). Gnyana’s dashboard framework enables the monitoring of any individual’s property (or shortlisted property) on a real time basis, with triggers for recommended entry and exit strategies.