How to Improve Solvency Assessment with Digital Footprints

Traditional methods of evaluating creditworthiness are no longer effective. Relying solely on financial data offers a narrow view, compromising the objectivity of credit scoring.

At RiskSeal, we found that a user’s digital footprint provides valuable insights into their financial reliability. We enable lenders to create a comprehensive profile of potential borrowers through alternative data obtained from digital footprint analysis.

In this article, we’ll discuss how a digital footprint can help credit institutions optimize their solvency assessment processes for applicants.

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Concept of a digital footprint

A digital footprint is a specific set of data that a user leaves behind due to their online presence and activity.

A person’s digital footprint typically includes:

• visited websites
• published content
• registrations on online platforms
• sent emails
• purchases on e-commerce platforms
• browsing history
• IP address, etc.

All these data points provide lenders with access to understanding a potential borrower's online behavior and financial habits. It’s critical for evaluating creditworthiness and risk profiling.

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Digital footprint statistics for 2025

To achieve business success, fintech companies must stay aware of the key trends in the development of digital footprints.

With this in mind, let’s take a look at the latest statistics on active footprinting and analyst forecasts in this area.

#1. Global internet coverage

The global reach of the internet is confirmed by data on the number of active online users, provided by Statista:

This statistic shows that through digital footprint lookup, financial institutions can gain information on over 5 billion consumers.

#2. Growing number of email users

According to statistics, nearly 4.4 billion people globally actively use email for communication. 

Experts predict this number will continue to grow, reaching 4.5 billion by 2025 and 4.9 billion by 2027.

By knowing only a borrower’s email address, you can gather a wide range of information about them, including registered accounts, subscriptions, photos, and personal data available in the public domain.

#3. Growth of e-commerce

The frequency and value of online purchases can provide insights into the financial standing of an applicant.

E-commerce has grown rapidly in recent years. According to Precedence Research, the global e-commerce market was valued at $16.3 trillion in 2023. By 2025, it is expected to grow to $21.6 trillion, and by 2033, to $67.1 trillion.

The rise in online shopping shows that virtual transactions can be a valuable source of alternative data.

#4. Growth in data creation and consumption

According to Statista’s analysis, there is a rapid increase in the volume of data being created and consumed online worldwide.

It is projected that by 2025, this figure will exceed 180 zettabytes, almost three times the amount recorded in 2020.

This highlights the tremendous potential of the cyber footprint in gathering user information across the internet.

#5. Prevalence of passive data collection

Passive data collection refers to gathering information about website visitors without their direct involvement. Statistics show that 90% of websites have at least one tracking script.

By analyzing a user’s passive digital footprint, a credit institution can monitor nearly all virtual visits made by a potential borrower. This enables the identification of patterns in consumer behavior.

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Types of digital footprints in credit analysis

Modern alternative data vendors offer financial institutions several varieties of digital footprints.

They are classified according to these characteristics:

• User involvement in creating the digital footprint.
• Ability to identify the consumer.
• Method of web footprint creation.

1. Depending on the user’s involvement in creating the digital footprint, we distinguish between:

• Active digital footprint. This includes data that internet users willingly share, such as blog posts, social media updates, and shared photos.

• Passive digital footprint. Refers to information that websites collect without the user’s knowledge, such as browsing statistics, IP addresses, or search history.

2. Based on whether the user’s identity can be established, we classify footprints as:

• Anonymous digital footprint. This is data shared online without revealing the user’s identity, such as posts under a pseudonym or accounts registered with fake credentials.

• Personally identifiable digital footprint. Refers to activities that can reveal the user’s real identity, such as registering on professional networks like LinkedIn.

3. In terms of how the data footprint is created, we have:

• User input data. This is any information that enters the web through active user actions like posting photos, sending messages, or filling out forms.

• Sensor data. Information gathered through various sensors, including cameras, microphones, GPS, and IoT devices. These data points help shape a person’s web footprint.

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Digital footprint examples for credit evaluation

User activity on the internet allows fintech companies and other lenders to perform credit scoring using digital footprints.

Here are examples of digital footprints that can be found:

• Paid subscriptions: Netflix, Disney+, Spotify
• Social networks: LinkedIn, Facebook, Twitter, Instagram
• Messengers: Skype, Viber, WhatsApp, Telegram
• E-commerce platforms: Amazon, eBay
• Job search platform: Upwork, Glassdoor
• Premium services: Apple, Samsung
• Online booking services: Booking.com, Airbnb

In addition, RiskSeal checks the availability of accounts on regional internet resources. 

You can read more about this in our article on alternative data for credit scoring.

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How does digital footprinting work?

Digital footprinting gathers data on a user's online activity and analyzes multiple data points to gain deeper insights.

Alternative credit scoring systems use various methods to create a unique digital profile for each borrower.

Email reverse lookup. By analyzing a borrower’s email address, lenders can access information such as:

• Email deliverability
• Linked accounts on other online platforms
• Domain details
• Creation date of the email account
• Whether the email address is blacklisted
• Type of email (e.g., disposable email detection)

Reverse phone number lookup. A phone number on a loan application can provide valuable information about the owner, such as:

• Phone number type (including burner phones, virtual SIM cards, temporary or incorrect numbers)
• Inclusion in high-risk number databases (blacklists, spam lists)
• Country code, compared with the borrower’s IP geolocation
• Associated digital accounts

IP address lookup. This verification method detects discrepancies and suspicious activity based on the borrower’s IP address, helping to establish:

• User geolocation
• Use of TOR, Proxy, or VPN
• Type of IP address (mobile/residential)
• Inclusion in high-risk IP databases

Modern digital footprint analysis through data science combines various data points into a single borrower profile. It allows lenders to objectively evaluate creditworthiness and make better lending decisions.

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The importance of digital footprint analysis

Digital footprint analysis is precious for financial institutions, helping them achieve critical objectives.

1. Optimizing credit decision-making. By analyzing the digital activities of borrowers, a financial institution can approve up to 30% more loan applications. 

These decisions are highly reliable, as all data is provided in real-time.

Digital footprint analysis allows lenders to offer services to individuals without a credit history, expanding their potential customer base.

2. Enhancing credit risk assessment. Alternative credit scoring models based on web footprint analysis include over 300 data points for each applicant. 

This allows for more informed decisions on loan issuance and helps quickly identify potential fraudsters, reducing KYC costs by threefold.

3. Improving accuracy in identity verification. This process involves facial recognition through AI and real-time comparison of borrower names and locations.

Even minor discrepancies can indicate criminal intent, resulting in assigning a high-risk level and either denying the loan or offering less favorable terms.

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Key findings from digital footprint analysis

At RiskSeal, we utilize extensive datasets on potential borrowers to objectively assess their creditworthiness. 

Through our practice of analyzing numerous digital footprint examples, we’ve identified key patterns that explain the functioning of alternative credit scoring.

#1. Lower digital credit scores are associated with higher default rates.

RiskSeal’s study for a Mexican lender reveals a clear correlation between credit scores and default rates. Borrowers in the 0-99 score range have a default rate of 52%, while those in the 900-999 range show a significantly lower default rate of just 5%.

Default rates decrease steadily as credit scores rise, demonstrating the effectiveness of credit scores in predicting loan repayment risk.

‍#2. The number of web registrations directly correlates with the likelihood of default. 

Studies show that around 70% of borrowers without social media accounts tend to have overdue loan obligations, whereas reliable clients typically have 5 or more profiles on such platforms. 

The absence of accounts linked to an applicant’s phone number or email raises a red flag for lenders. 

Positive trust signals in a Digital Credit Score include consistent information across online services, such as names and photos, as well as the number of paid subscriptions, which reflect online financial literacy and reliability.

#3. The use of anonymizers significantly increases the likelihood of fraud.

According to IPQS data, 95% of fraudsters use proxy servers, SOCKS, VPNs, and other services to hide their real IP addresses during crimes.

Identifying the use of any anonymizer allows the lender to suspect fraudulent intent.

#4. Data breaches positively impact the digital credit score.

Although data breaches can harm individuals and organizations, their existence is a positive indicator when assessing a potential borrower.

Statistics show that the average email address is compromised at least three times during its lifetime.

Data breaches suggest that the email has been in use for a long time, rather than created specifically for applying for a loan.

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Digital footprinting trends for 2025

To stay up to date, financial institutions should be aware of key trends that will shape digital footprinting soon.

Increased focus on the security of confidential data

Companies leveraging digital footprints to assess creditworthiness must follow data protection regulations.

Lenders must comply with legal requirements by using borrower data only with consent and for a specific purpose, while ensuring its safety during processing and storage.

This approach ensures digital footprint use aligns with regulatory standards.

Consumer control over personal data

Users are becoming increasingly aware of privacy issues and demand ethical handling of their data. 

This further emphasizes the need to comply with GDPR, CCPA, and other personal information protection regulations.

Lenders must outline in their GDPR compliance policy the purpose of data collection, types of data collected, rules for sharing with third parties, and storage practices.

Following these guidelines increases customer trust.

Integration of AI-based web tools for digital footprinting

By 2025, financial institutions will rely heavily on advanced technologies when evaluating borrowers.

AI and machine learning-based platforms will play a key role, offering limitless potential in identity verification, credit decision-making, and credit risk assessment.

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Digital footprint analysis at RiskSeal

The RiskSeal platform is built for credit scoring using digital footprints. 

To create a complete profile of an applicant, we focus on a wide range of data, including:

• email
• phone number
• location
• name
• avatars
• IP address

By gathering information from 140+ sources, we provide our clients with:

• Over 300 data points about the consumer.
• A detailed profile of the applicant.
• Their digital credit score.

Our creditworthiness assessment method helps financial institutions expand their client base, lower default risks, and detect fraud.