Lenders lose a significant share of potential customers due to the limited reach of traditional banking services globally. This is primarily because conventional scoring models cannot evaluate borrowers without a credit history. To address this challenge, more financial institutions are turning to alternative data for credit scoring, enabling them to enhance financial inclusivity.

This article explores how non-traditional data about prospective borrowers helps financial institutions serve populations considered unscorable by traditional banks.

Understanding Alternative Data in the Context of Credit Scoring

Traditional scoring models rely on a limited range of data to assess an individual’s creditworthiness. These typically include information about previously issued loans, such as payment history, credit utilization ratio, types of credit products, and more.

Alternative data, however, goes beyond the information provided by credit bureaus. This includes utility or rent payments, public records (e.g., legal judgments), insurance premium payments, and more.

Among these, digital footprints are considered the most informative source of alternative data.

Alternative Data Enabled by Digital Footprint Analysis

A digital footprint encompasses information about users that remains online as a result of their interaction with the digital ecosystem.

What constitutes a digital footprint?

Social Media Activity

Over half of the global population actively uses social networks, voluntarily sharing personal information in the public domain. Lenders can leverage this data to enhance their understanding of applicants’ creditworthiness.

From social networks, lenders can extract:

• Profile pictures. Comparing available avatars can help verify an applicant’s identity.
• Geotag. These can validate the location provided in the loan application.
• Career and education details. Information found in professional networks such as LinkedIn.
• Public interactions. Users often highlight their participation in events, respond to posts, and more, which can contribute to building a consumer profile.

Utilizing Other Online Resources

Analyzing consumer behavior on other online resources is equally valuable. For example, gambling websites, e-commerce platforms, streaming services, and others. Additionally, knowing a person’s email address can provide a lot of useful information.

From this source, a lender can determine:

• Characteristics of the applicant's consumer behavior. The presence of paid subscriptions and regular high-value online purchases reflects positively on the borrower. Excessive activity on gambling websites, a large number of product returns, or abandoned shopping carts can lower the applicant’s digital credit score.
• Likelihood of loan default. If the applicant makes late payments for subscriptions, this may indicate a predisposition to default.
• Authenticity of the email address. Here, the lender may be alerted to the lack of registered e-mail accounts, a recently created or inactive mailbox.

Data from Mobile Operators

The number of mobile network users worldwide exceeds the number of social media users, making this data source particularly valuable for financial organizations.

What can be determined:

• Authenticity of the Phone Number. Reliable borrowers are unlikely to use virtual SIM cards or burner phones. Additionally, the presence of online profiles linked to the number indicates its authenticity.
• Country of Residence. The lender can compare the operator's code with the country of residence provided in the application.
• Tariff Plan. By analyzing the phone number, it is possible to determine whether the subscriber uses a contract plan or prepaid service, as well as how consistently they pay for their mobile service.

Information from Internet Service Providers

This is another type of data that is publicly available. It can help verify whether the information provided in a credit application is accurate.

Specifically, a lender can learn:

• Type of IP address. This information allows the lender to determine the origin of the credit application — whether it was submitted from a home, a public place, a mobile device, or a PC.
• Borrower’s location. The IP address can be used to identify the user’s actual geolocation, which can then be compared with the residential address stated in the application.
• Fact of IP address concealment. Criminals often use anonymizing tools such as VPNs or proxies to hide their true location.

This broad range of data, accessible through the analysis of digital footprints, enables lenders to expand the inclusivity of their credit assessments for potential borrowers.

How Do Alternative Data Influence Credit Scoring?

Two key benefits of optimizing credit scoring with alternative data can be highlighted:

1. Lending to unbanked population segments. Alternative data provides insights into the financial status and reliability of potential borrowers, even for those who cannot be assigned a traditional credit score.

2. Efficient detection of potential defaulters and fraudsters. Traditional data can be easily forged, such as creating synthetic identities using stolen personal information to apply for loans. In contrast, digital footprints are nearly impossible to falsify.

Modern scoring systems, like RiskSeal, actively leverage the advantages of digital footprint analysis.

Alternative Data Through Digital Footprint Analysis with RiskSeal

RiskSeal is an innovative AI-based scoring system built on analyzing the digital footprints of potential borrowers.

The platform identifies and delivers hundreds of data points from global and local online resources. These insights include:

• Email lookup data
• Phone number lookup data
• Location insights
• Social media activity data
• E-commerce activity data
• Paid subscriptions data
• Name variations
• Avatars

In the context of enhancing credit scoring inclusivity, this approach achieves the following results:

• Expanding access to credit services to 98% of the unbanked population.
• Doubling the number of loans approved.

In addition to optimizing credit scoring, digital footprint analysis provides other benefits for lenders. Among them is the reduction of KYC costs due to the early detection of potential fraudsters.

With RiskSeal, you can expand your target audience, increase the number of loans issued — all without compromising the quality of your credit portfolio.