Digital Footprinting Analysis for Fraud Prevention: Full Guide

Digital footprint analysis can help fight fraud, identify loan applicants who are likely to default, and more. All while keeping business operations efficient and customer onboarding friction to a minimum.

Find out what digital footprint analysis is, why you need it, and how to implement it below.

What Is a Digital Footprint?

The term refers to the information – “the footprint” – we each leave behind as we spend time on the internet. This is sometimes thought of as, and called, a “digital shadow” that a user casts, knowingly or not.

This ranges from registered accounts on various websites and services to our social media accounts and public posts, to upvotes or downvotes on reviews, and so on – including content on all sorts of digital platforms, from ads to forum comments.

Digital footprints are linked to aspects of our online identities, such as IP addresses and email handles, rather than our real names. These often overlap, providing detailed insights into our legitimacy and serving as valuable information for background checks. They reveal much about a person without direct interaction, offering an idea of their identity and trustworthiness.

Types of Digital Footprint

In general terms, there are various types of digital footprint, which depend on what aspect of it we’re focusing on and how the footprint is left behind – such as passive, active and private footprint. Let’s take a closer look.

• Active digital footprint: The primary distinction between active vs passive digital footprint. An active digital footprint comprises all the actions they intentionally make online – e.g., a tweet, a comment on Facebook, or a review on Tripadvisor
• Passive digital footprint: Everything else – everything not created by a user’s actions and/or not intentionally shared with the organization doing the footprinting. For example, the pages you visit more often on an e-shop or whether you’ve been to a website before.
• Anonymous: Data left behind by anonymous users are sometimes called anonymous digital footprints. This is still valuable to several stakeholders – for example, information on a website visitor’s cursor movements can show a company which parts of their home page are more appealing.
• Eponymous/personally identifiable: If, for any reason, you use your full name online, part of your digital footprint can be eponymous – linked to your real, full name. This is, for example, generated when you are signed in to online accounts that use this name. For example, when you use LinkedIn logins to access third-party websites.
• User input: All data originating from the user’s own input, including clicks, forms filled and other deliberate actions. There is a lot of overlap with an active digital footprint, but they are not identical.
• Sensor data footprint: When they use mobile devices, which come with accelerator sensors, GPS, etc, a user’s digital footprint includes data from these sensors.

Digital Footprint Examples

Examples of what makes up a digital footprint include things like public comments on forums, social media posts and uploads, and any places where their email address has shown up inadvertently or not (e.g., on mailing lists, if made public) etc.

Here is an example of the digital footprint linked to an email address:

• Facebook profile registered with an address
• Skype profile registered with address & public name, handle, shared information (see image below)
• Google profile exists
• Gravatar profile exists, and its username
• OK.ru profile exists, and the date is registered.
• and so on.

As we’ll see below, for purposes of fraud prevention, the absence of a digital footprint is as important as its existence, as it isn’t easy for a fraudster to mimic a real, good customer in this way.

How Does Digital Footprinting Work?

Digital footprinting takes one or more data points and gathers the user’s related online activity through a reverse lookup. Starting with an email address or phone number (for example), the process will find things like:

• whether any social media accounts are associated with that data point
• whether the data point is linked to any data breaches
• what the user’s IP address is, and which country they are usually based in
• how long a phone number or email address has been active
• whether a phone number or email address is a disposable one
• which network a phone number is on

The digital footprint is built up of all these pieces of information, which combine to create a unique profile – a footprint – of the individual. It uses open data to do this, i.e., data that the user has opted to share publicly. A business can analyze the resulting footprint to inform their decisions relating to the user, including whether they may be a fraudster or likely to default on a loan.

Why Is Digital Footprint Analysis Important?

Digital footprinting is important to businesses because it can help them fight fraud, determine how likely a customer is to default on a payment and assess a range of other risks. It enables businesses to make informed, data-driven choices about who they deal with and on what terms. All without increasing friction for the customer, meaning organizations can use it without impacting customer satisfaction levels.

Reduced fraud risk boosts profits, satisfies regulators, and enhances public reputation, attracting more customers. Digital footprinting is also vital for individuals, as institutions evaluate their online reputation.

How to Catch Fraud Using Digital Footprint Analysis

Digital footprint analysis can help businesses spot fraudsters by identifying common red flags. Together, these red flags enable organizations to identify users with digital footprints that look suspicious and, thus, are likely to belong to fraudsters. Examples of suspicious behavior include the use of:

• a VPN
• a temporary email address or phone number
• an email address or phone number with no associated social media or other accounts
• an email address that has never been in a data breach.

Leading digital footprint analysis tools carry out this process in real time, then assign a risk score to each user. Organizations can set their own weighting for these risk scores to finetune the analysis to meet their own needs. In this way, businesses can use digital footprint analysis to catch likely instances of fraud before the event rather than after.

Digital Footprinting Monitoring: Key Findings

At SEON, we use extensive data to understand and counteract fraud tactics, a key part of our prevention strategy. For this guide, we analyzed transactional data from ecommerce, online lending, and iGaming sectors to reveal insights into our defense systems.

1. IP Addresses Are Linked to the Most Triggered Rules 

Most rule triggers across sectors are related to high-risk IP addresses. Fraudsters use proxies and VPNs to avoid detection and mimic their victims’ online presence. In our data, 52% of iGaming and 65% of ecommerce rule triggers were due to high-risk IP addresses, highlighting the need for effective device fingerprinting and proxy detection as a first line of defense against fraud.

2. More Accounts = Safer to Approve

Approved transactions typically involve users with more online profiles. In ecommerce, legitimate users have an average of 5.68 social media or platform accounts, while declined users average 2.89, and those for manual review have 3.37.

This trend is similar in iGaming and online lending, where approved users have 4.34 and 5.45 profiles on average, compared to 1.26 and 1.02 for declined users. A higher number of profiles generally indicates a safer user.

3. More Data Breaches = Safer to Approve

Digital footprinting also considers the number of data breaches associated with an email address. “Good” users in ecommerce averaged 2.44 data breaches, while fraudsters averaged 0.68. In iGaming, legitimate accounts averaged 1.26 breaches versus 0.65 for suspicious ones. Loan applications showed 1.02 breaches for approved users versus 0.15 for declined ones. Given major breaches like Yahoo’s and Marriott’s, most email addresses have likely been compromised at some point.

These findings underscore the importance of comprehensive digital footprinting in assessing user intent and preventing fraud.

Digital Footprinting Analysis and Monitoring: Key Takeaways

SEON’s research has shown that fraudsters are relatively lazy, settling for throwaway email addresses and disposable phone numbers with virtually no related online presence. This means that digital footprinting can be effective in helping spot and block fraudsters. As digital footprinting is frictionless for customers, businesses can do so efficiently.

Our experience also shows that businesses increasingly rely on digital footprint signals over time. This increased trust results from organizations seeing their fraud metrics improve when they introduce digital footprint analysis.

Frequently Asked Questions

Sources

• Datareportal: Global Social Media Stats
• Crowe: The financial cost of fraud 2021
• Tech Jury: 27+ Biggest Data Breaches In History
• Internal SEON data