There are billions of records streaming continuously from the likes of satellites, Wi-Fi access points, hand-held devices, and aerial and ground-level sensors. Geospatial data is more available than ever, with recent estimates of the location-based services markets suggesting it could be worth $30B by 2027, expanding at a compound annual growth rate of 15-20%. Used correctly, geospatial data can provide many business advantages and can contribute significantly to better decision-making when used in combination with traditional business data.

What is geospatial data?

Geospatial data is time-based data that is associated with a particular location on the Earth’s surface. If you’ve ever searched for ‘Gas stations near me’, you’ve used geospatial data.

It often involves large sets of spatial data drawn from a range of sources in an array of formats, including census data, satellite imagery, weather data, cell phone data, drawn images, and social media data.

Managing the rise of geospatial data

The need for analyzing geospatial data has been on the rise across the public and private sectors. In government, this includes law enforcement, tax, social security, emergency management agencies, and in the private sector, companies in fields such as banking, insurance, telco, logistics, and aviation. These organizations tend to have access to vast amounts of geospatial data (such as the location of cars, where phone calls have been made) and their businesses are heavily influenced by it.

But dealing with large geospatial data sets presents a number of challenges, which is why many organizations struggle to take full advantage of it. To make the most of geospatial data, it needs to be put in context.

Without the right tools, analyzing it can be a manual and lengthy process, forcing users to rely on third-party software to connect and make sense of data from disparate systems. This leads to missed revenue opportunities, exposure to unnecessary risk, inaccurate decisions, and operational inefficiencies. The inability to search based on geographical data has created a need for unintegrated and automated third-party applications.

Introducing Geospatial Search

The latest feature of the Quantexa 2.1 platform – Geospatial Search – is designed to make the most of geographical data by making sense of its connections to other related data points, which in turn provides context. Users can interactively define locations on a map, add filters and conditions, and run queries to further enrich investigations – aiding them further in uncovering risky and fraudulent activity.

Geospatial Search use cases

1. Geospatial Search powers connected law enforcement investigations for governments
   When conducting criminal investigations, government authorities have vast intelligence available, such as names, common criminal activity areas, license plate numbers, phone numbers, residential addresses, places of travel, common routes, and more. The key to a successful investigation is understanding the connections, trends, and timelines of all the data available.

2. Underwriting in P&C insurance can benefit from geospatial data
   In recent times there has been an increase in severe natural disasters such as hurricanes and wildfires, and other externally influenced catastrophic events. These events often have large geographical influences, but historically it has been challenging to bring both internal and external data together consistently to review geographical exposures in one place.

Enabling insurers to better understand geospatial data helps them make more accurate underwriting decisions. Not only this, but it also helps predict future claims and prepare advanced strategies for claims prevention and reserving – thus reducing losses.

The future of Geospatial Search

With the vast and rapidly increasing volume of data that is readily available, public and private sector organizations must maximize geospatial data to improve their investigations and decision-making processes. And Geospatial Search is providing the solution.