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October 8, 2024
How to Improve Solvency Assessment with Digital Footprints
Explore how digital footprints improve solvency assessments, providing deeper borrower insights and optimizing credit decisions.
Explore how digital footprints improve solvency assessments, providing deeper borrower insights and optimizing credit decisions.
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.
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:
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.
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.
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.
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.
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.
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.
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.
Modern alternative data vendors offer financial institutions several varieties of digital footprints.
They are classified according to these characteristics:
1. Depending on the user’s involvement in creating the digital footprint, we distinguish between:
2. Based on whether the user’s identity can be established, we classify footprints as:
3. In terms of how the data footprint is created, we have:
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:
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.
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:
Reverse phone number lookup. A phone number on a loan application can provide valuable information about the owner, such as:
IP address lookup. This verification method detects discrepancies and suspicious activity based on the borrower’s IP address, helping to establish:
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.
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.
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.
To stay up to date, financial institutions should be aware of key trends that will shape digital footprinting soon.
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.
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.
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.
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:
By gathering information from 140+ sources, we provide our clients with:
Our creditworthiness assessment method helps financial institutions expand their client base, lower default risks, and detect fraud.
RiskSeal’s digital scoring system collects the electronic footprint of potential borrowers from 140+ online platforms, including local web services. To access a detailed applicant profile and their digital credit score, simply provide us with the data submitted in the loan application.
Through digital footprint analysis, a lender receives hundreds of data points about a potential client. Based on this information, they can assess the borrower’s creditworthiness. For instance, the use of premium services, paid subscriptions, or professional social media accounts positively impacts the digital credit score.
Digital footprint analysis helps financial institutions achieve their main objectives: optimizing credit decision-making, improving credit risk assessment, and increasing the accuracy of identity verification. This allows lenders to approve more loans, reduce fraud, and minimize the risk of defaults.
Digital footprints, also known as web or cyber footprints, are the data left behind from a user’s online activities.
Digital footprints result from registering on various platforms, making online purchases, using digital services, posting on forums or social media, etc. Web footprints are also formed through the use of sensors, such as microphones, cameras, and IoT devices.