Modern enterprises in various industries are essentially data-driven organizations. They gather vast volumes of business and consumer data for demand forecasting, advanced decision-making, strategic planning, supply chain management, service personalization, advertising campaigns, and whatnot.
Fintech companies and banks are no exceptions to this across-the-board drive, utilizing data engineering and analytics in their basic workflows, such as fraud prevention, risk assessment, customer segmentation and retention, algorithmic trading, operational efficiency optimization, and more.
As the competition in the niche becomes ever fiercer, forward-looking financial actors go beyond analyzing traditional data and tap alternative sources of information that can provide them with a deeper understanding of their target audience and additional insights into current market trends. Location intelligence is one of the alt data practices that allows financial organizations to hone their competitive edge.
Traditional vs. alternative data in the financial sector: The difference made plain
What information do financial firms conventionally employ in their pipeline routine? As a rule, these are records obtained from financial statements, earnings reports, press releases, SEC filings, macroeconomic summaries, industry digests, and other publicly available channels. While reliable and trustworthy, such traditional data can’t provide a comprehensive view of any shop floor area or entity.
Financial enterprises increasingly involve alternative data from social media, product reviews, email receipts, web traffic, IoT devices and sensors, satellite images, jet tracking, credit card transactions, and more to complete the picture.
After proper analysis and processing, this largely unstructured data allows financiers to fill in the gaps existing in traditional data, pinpoint risks, and identify growth opportunities that remained otherwise concealed. Currently, the alt-data market manifests a meteoritic spike, increasing from slightly above $1 billion three years ago to the expected $17.4 billion by 2027.
Geospatial information is one of the crucial growth drivers in this field, predicted to account for a $1 billion-worth market within three years – an astounding surge from $154 million in 2021. Such an impressive rise explains the ubiquitous advent of location intelligence into financial business practices.
Meet location intelligence
Location intelligence uncovers patterns and derives insights by analyzing spatial and geographical data. In other words, it studies what happens on the surface of the earth to arrive at a comprehensive understanding of spatial dynamics and figure out the business implications of these developments.
The most important data types location intelligence draws upon include:
- Demographic data – age, gender, ethnicity, educational level, marital status, address, and other population characteristics.
- Wealth data – information about income and economic status of people or households, pivotal for reaching out to affluent strata.
- Transaction data – everything related to consumer transactions employed for dissecting customer preferences, spending behavior, and sales performances.
- Retail outlets data – geographical locations of stores and other commercial establishments, instrumental in analyzing niche competition and market saturation.
- Points of interest data – positions of hospitals, schools, parks, and sports facilities that are the staple of urban planning and real estate assessment.
- Footfall data – information on the quantities of people passing through a certain place that can be instrumental in business site selection and choosing marketing initiatives.
- Administrative boundaries – geographic delineations of countries, states, provinces, cities, and districts, pivotal for market analysis and regulatory compliance.
Where can you obtain this data? Satellite imagery, public statistics, and enterprises’ business records (like clientele addresses or store locations) are the typical sources of relevant location intelligence that can be accessed free of charge or bought from its owners. Besides, you can leverage cutting-edge technological tools (Geographic Information Systems (GIS), Internet of Things sensors and gadgets, cloud computing, etc.) to collect, process, and analyze geographic data.
Yet, the most widespread and valuable source of location intelligence is GPS data pinged by people’s phones across cellular networks. With the advent of 5G and the increasing availability of mobile devices, this source of alternative data is likely to become the foundation of location intelligence for digitally driven enterprises.
Given the multitude of channels and huge volumes of data to be searched, retrieved, and processed, location intelligence can’t be effective without the employment of state-of-the-art know-how, such as:
- Big Data. This technology excels at collecting and handling limitless datasets containing both historical and real-time data points.
- Artificial intelligence. Whatever insights are derived from geospatial data, AI can swiftly and accurately sift them through to forecast trends, detect anomalies, and automate complex workflow processes.
- Machine learning. Its algorithms enable high-precision data analysis and service personalization by learning from training data and enhancing software performance over time.
Financial organizations can enjoy the boons location intelligence relying on geospatial data ushers in by applying it across multiple shop floor processes. Investment management is one of such areas where the perks of location intelligence are particularly evident.
How to improve investment decisions with location intelligence
The investment domain is a high-risk financial sphere where an imprudent step or wrong decision can cost you thousands and sometimes millions of wasted dollars. Modern fintech solutions (for instance, an investment application or an investment feature of a personal finance app) benefit greatly from harnessing the power of location intelligence, allowing individuals and organizations to maneuver their portfolios. What are the investment sectors where geospatial data can unlock hidden business value?
Real estate
Before investing in this kind of property, you should study geospatial data displaying its land topography, proximity to commercial and recreational amenities, public transportation, infrastructure, school districts, natural landscapes, historical landmarks, etc.
Location intelligence can also supply such risk-related information as earthquake fault lines, flood areas, and wildfire zones. When you amplify it with other critical data (population’s income level, crime rates, demand for properties, and more), you will have a clear understanding of whether purchasing property in some areas is a sensible and safe investment.
Agriculture
Here, you should look for climate and weather-related insights (for instance, extreme temperatures, altitude, soil fertility characteristics, precipitation volume, probability of natural disasters, etc.) to determine the economic sensibility of investing in agricultural business initiatives in a specific location.
Energy generation
Weather conditions also play a mission-critical role for investment decisions in this field. Cold climates and long night hours condition more demand for energy, so investing in a power station in such places is worthwhile.
Another investment-inviting development in this realm is geospatial data that registers many people moving to an area, which is indicative of the potential surge in economic activity and, consequently, a future increase in the local demand for energy. And when you discover that the number of sunny or windy days in an area is quite significant, you can consider financing the construction of a solar power plant or a wind farm there.
Retail
To predict whether a site for a retail outlet or an existing store is likely to bring profit (and therefore is worth investing), you should analyze such geospatial data as its proximity to residential areas, competitors’ presence, availability of public transportation routes, vehicle traffic intensity, foot traffic data (with typical movement patterns), visit attribution, and even parking lot fill rate.
As a result, you will arrive at a ballpark figure of consumers who will patronize the mall in question and see whether the money they are likely to spend there is a satisfying ROI for you.
Telecommunications
By analyzing population density, foot traffic, and hotel booking dynamics, you can gauge the demand for internet consumption.
If it proves sufficiently high, you can invest in telecommunications organizations that will set up Wi-Fi hotspots and develop digital infrastructure in such potentially income-generating neighborhoods.
Key takeaways
For any future-oriented business with big-time aspirations, analytics, and decision-making based on traditional data can’t provide a sharp competitive edge. To thrive and expand, they should tap alternative data sources, where location intelligence reigns supreme. The geospatial data it furnishes is highly instrumental in many verticals, the financial sector including.
By taking any information from the physical world and mapping it onto your investment strategy in real estate, agriculture, retail, telecommunications, and other domains, you can revolutionize your investment decision-making and reposition your portfolio to let it bring maximum profit.
James is the head of marketing at Tamoco
