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In the lending industry, the difference between credit and alternative data is a question often asked. Since credit scores are known to identify a borrower’s creditworthiness, using alternative data can be deemed as an unconventional way of credit scoring.

However, as the financial system evolved and more open finance technology providers integrated modern FinTech systems, lenders saw the value of using alternative data for credit scoring. By looking beyond traditional credit reports, your company can now gain a more comprehensive understanding of the financial habits of a borrower—which can lead to fairer credit decisions and increased financial inclusion.

So, what sets traditional credit scoring vs. alternative data apart? How do they differ?

First, Let’s Breakdown Credit Scores

Computing a person’s credit score is primarily based on data collected by credit bureaus. This data includes an individual's borrowing history, credit card balances, loan repayments, credit inquiries, and public records of defaults or bankruptcies.

While credit scores are valuable, they solely focus on debt-related information. This can negatively impact borrowers who are new to the credit system, have a limited credit history, or utilize alternative financial services like rent payments or Buy Now, Pay Later (BNPL) options responsibly. Additionally, credit reports may not accurately reflect an individual's current financial situation, as updates can sometimes be delayed.

Other than alienating certain borrowers from loans, as a lender, you also incur losses in credit opportunities from these untapped groups of individuals who have limited access to loan products.

Credit Score vs. Alternative Data

Using alternative data for alternative credit scoring utilizes a broader range of non-traditional data points to create a more holistic picture of a borrower's financial health. Since people generally have more than one way of performing their financial obligations, alternative data sources can be considered for credit scoring. Different types of sources include:

Utility and Rent Payments
Utility and Rent Payments:
Timely payments for rent, utilities (electricity, gas, water), and phone bills can be powerful indicators of a borrower's financial responsibility.
For instance, if they use Visa to pay their bills, the data can effectively gauge a person’s financial management habits—pinning down whether they settle their recurring bills on time.
Buy Now, Pay Later (BNPL) History
Buy Now, Pay Later (BNPL) History:
Responsible use of BNPL services demonstrates an ability to manage credit responsibly, with timely repayments being positive indicators of creditworthiness. This is a more miniature version of loans, gauging whether an individual practices good debt-repayment habits.
E-commerce Transaction History
E-commerce Transaction History:
Online shopping behaviors such as avoiding excessive debt and following budgets can be positive indicators. By using shopping information, you can differentiate responsible spenders from impulsive buyers.

As an example, if your clients use GoPay for shopping transactions, products like Brankas' GoPay Data can be useful for lenders to check for transaction histories. Their spending habits can demonstrate whether a borrower can be trusted with credits or loans.

By incorporating alternative data, as a lender, you can gain a more complete view of a borrower's financial responsibility. This includes assessing their ability to manage expenses, income stability, and responsible use of alternative financial options.

So, What are the Key Differences of Credit Scores and Alternative Data?

With the definitions mentioned earlier, we can now break down the distinctions between traditional credit scoring vs. alternative data credit scoring. Aside from their sources of data, here are 3 more ways both types of credit information differ:

Traditional Credit Scoring Models

Traditional Credit Scoring Models:

These models rely heavily on credit report data and utilize complex algorithms to calculate a credit score. In the United States, FICO scores (Fair Isaac Corporation) and VantageScores are two commonly used models.
Alternative Data Scoring Models

Alternative Data Scoring Models:

These models incorporate a wider range of data points, including alternative data sources. They utilize sophisticated algorithms like artificial intelligence and open financing for a more comprehensive assessment. Some lenders can develop their own alternative scoring models, while others choose to work with expert FinTech companies specializing in this area.

Which is Better: Traditional Credit Scoring or Using Alternative Data?

The differences between traditional credit scores and alternative data highlight the changing landscape of the lending industry. And while both these methods are good to use for lending companies like yours, it’s worth noting that alternative data is a complementary tool to traditional credit scoring. Integrating them with your traditional practices can open opportunities for both your company as the lender and borrowers.

And if you’re ready to integrate alternative data into your lending systems, consider partnering with Brankas for modern financial services! 

With our products and services, we can upgrade your FinTech systems to create a more seamless and efficient process for your company and clients. We make it easier for you to keep track of your business transactions while making the user experience for your customers much smoother.