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34.253.101.190  Public Scan

Submitted URL: https://t.sidekickopen84.com/Ctc/DJ*23284/clDb304/JkM2-6q7W6N1vHY6lZ3lmW85Jzst1r7Y2jVvtzy-5XV2r9W2XfGzx2jRvH7W1jXmm56fGx2KW3d...
Effective URL: https://www.unacast.com/post/3-use-cases-financial-services
Submission: On January 04 via manual from US — Scanned from DE

Form analysis 3 forms found in the DOM

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3 USE CASES FOR LOCATION DATA IN FINANCIAL SERVICES

By

Jon Torre

Unacast

Senior Sales Director

Published on:
May 11, 2021
May 11, 2021
Last updated:
January 28, 2022

‍Location data is commonly used in many industries to help inform investment
decisions and to both detect and measure change. Those use cases are clear for
Commercial Real Estate, Retail and the Public Sector.


What’s less commonly understood are the use cases for location data in the
Financial Services industry. 


What does a hedge fund manager care about migration patterns? Why would a bank
targeting business customers spend time and money to study foot traffic on Main
Street? Better yet, how can a financial services consumer - aka all of us -
actually benefit from the industry’s use of location data?


The 3 most common use cases for location data in financial services that we
encounter here at Unacast typically fall into two categories: investment risk
assessment and marketing to both business and consumer segments. 


We’ll start with using location data to inform business and credit risk
assessment.

‍


INFORMING BUSINESS AND CREDIT/LENDING RISK ASSESSMENT

In another post, our Chief Technology Officer, Frode Bjerke, points out that
there are really only  three overarching use cases for location data across all
industries: Informing decision making, Detecting change and Measuring change. 


The first use case in the financial services industry is squarely in the camp of
informing decision-making, specifically around different types of investments.
One technique that is often applied is to use visitors to a given location as a
proxy for how a business is performing -- not just in a specific location but
across a franchise and in relation to the competition.


For example, a hedge fund could use location data to examine migration patterns
to discover emerging areas, or investment opportunity zones, with indicators
such as net positive population growth and upwards mobility in terms of average
income.


In another application, the investor wants to look at foot traffic data over a
given period of time around a series of custom points of interest, let’s say
publicly-traded retail brand locations. In this scenario, foot traffic volume
and trends versus other locations and brands help to inform the decision whether
to buy, sell or hold that retailer’s stock. 


In a final example for this use case, a lender wants to inform their credit risk
assessment for a privately-held restaurant chain with 200 locations across a
dozen states. With fewer public instruments available to reference, location
data can add a valuable dimension to risk assessment models.



10 Restaurants Gaining Foot Traffic in 2021

To begin with, the lender could examine the population flow in the areas around
each store to understand if the market was growing. The lender could also assess
risk by using foot traffic data relative to specific venues, addresses, or
brands to detect variances indicating a rise or decline in opportunity. 


If the restaurant chain operates some of its own warehouses, no problem. We can
pan over to those venues and study foot traffic patterns that will indicate
peaks and valleys in human activity. For example, a sustained decrease of
typical mobility in a light industrial/warehousing area may be indicative of a
slow-down in operations due to decreased demand in individual restaurants, etc.


In the first two of these examples, the purpose of location data is to augment
and inform other data to support investment decision-making. In the final
example, the purpose of location data is both to detect market variations, and
to inform a wise lending decision.


In the next two use cases, the purpose is to extend some of these capabilities
into a financial service organization’s marketing efforts.

‍


BUSINESS MARKETING

Knowing your customers’ customers is key to marketing. We can’t begin to
position our own stuff for success until we understand what it is that makes our
customers successful, right?


There are plenty of marketing and advertising technologies in use by financial
services providers that help at a demographic level. Plugging location data into
the mix adds a great deal of value.


For example, let’s say a major bank wanted to get better at targeting business
customers. The simple question location data can help answer is: Based on their
visitors, on which businesses should we target our marketing efforts?


In this scenario, location data, which blends beautifully with demographics, can
be used to identify individual venues, locations and businesses with traffic
patterns that reflect the core characteristics of the bank’s target audience. 


So, even though this looks like a very different type of decision than credit
risk assessment, in both cases location data is being used to inform an
investment decision, albeit different types. 


The third common use case for location data in financial services extends on the
idea of knowing the customer’s customer by examining not just foot traffic, but
area of origin and broader movement patterns.

‍


CONSUMER-BASED ORIGIN DESTINATION MARKETING

Even in the COVID age and perhaps now more than ever, studying how people move
through the physical world is vital to understanding their path as consumers. In
particular, understanding where people come from is vital to understanding where
they go and what they do.


If I am in County A and the nearest Home Depot is in County B next door, am I
willing to make that trip, or will I choose to stay closer to home? How does
COVID affect that here and now? 


Is there a noticeable trend of people traveling from far away, perhaps Houston
to New York, or Denver to Miami, who are influential consumers while they’re in
town? 


If so, by understanding more about these people - where exactly they are from,
the average income of that place, the brands and services that do well there -
you can do a better job of marketing to them, either at-home or while they are
visiting. And that is ultimately good for the consumer.


For financial services providers, this can be applied either for targeting their
own consumer audience, or once again as an assessment tool when devising
strategies for pursuing and enabling the banks’ own clientele to service their
customers.

‍


SUMMARY

Many use cases for location data boil down to informing investment decisions and
the financial services industry is certainly no different. Though the manner of
the investment varies, the need in financial services that location data meets
is to intelligently augment broader decision-making processes.


Would you like to discuss your own use case for location data in financial
services? talktous@unacast.com



RESOURCES

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Retail datasets can be a valuable resource for businesses looking to make more
informed decisions. Learn about Unacast's retail solutions.

Dec 14, 2022
Retail competitive intelligence data — where to get it and how to use it
Retail competitive intelligence involves the collection and analysis of data to
gain insights into your retail market.

Nov 17, 2022
What Telco Data Can Tell Us About London's Tube Strike




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