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An Ultimate Guide To Credit Scoring Software Development

The ground rule for any lender is to check if a borrower is credible enough to provide them with a loan. Banks and financial institutions have long been successfully using various credit scoring models for that. However, a number of rising challenges in the financial sector due to the Covid-19 pandemic such as ROE decline and reduction in loan investments around the globe as well as the necessity to bring in new clients required financial institutions to use a more flexible approach to lending. That’s why many of them are starting creating credit scoring software today.

Credit scoring software allows banks and financial institutions to effectively expand their client bases while preserving the lending risks at a low level.

Therefore, more and more companies are considering utilizing an alternative to conventional scoring models – AI-based credit scoring software.

In this article, you’ll find out what is a credit scoring system, what are the main benefits of this type of software, and how to implement it in your FinTech solutions.

Traditional Credit Scoring vs Alternative Scoring

Before we get to the differences between traditional and alternative scoring, let’s find out what credit scoring is and why it is important.

Credit scoring is a process of evaluating the creditworthiness of borrowers for providing them with a loan. When scoring is performed, an applicant receives a three-digit number that stands for a score. If the score is high, then financial institutions provide the borrower with a loan, though if it’s low then lending is highly likely to be rejected.

Any customer interested in their score can check it as well as banks and various financial organizations once they gain their client’s permission.

Traditional Credit Scoring

There are a number of conventional credit scoring models around the world. Let’s have a look at the most popular ones in the US as an example. They are FICO and VantageScore. Both have much in common though they pay attention to different factors for determining a credit score.


FICO is the most popular scoring model in the US developed in 1989. It’s used by more than 90% of top lenders in the US. FICO offers diverse types of scoring. For example, if a customer wants to get a loan for a car, they should check their FICO AutoScore whereas an application for a credit card will require checking FICO Bankcard Score.

When determining a score, the major factor FICO relies on is payment history. The score range in FICO is usually the follows:


VantageScore is a competing model with FICO created in 2006. Just like FICO, VantageScore also offers its users several suites depending on the loan purpose. Along with this, different suites include various factors for tracking credit behavior, e.g. VantageScore 4.0 model includes trended data in its scoring decisions.

When determining a customer’s score, VanateScore focuses mainly on the customers’ credit card balances and credit utilization ratio. The score ranges include:

The credit scoring models aren’t limited to only FICO and VantageScore which provide their own scores, though they are heavily based on these two most popular models.

Alternative Credit Scoring

An alternative scoring model derives from conventional scoring methods and statistical techniques that are effectively enhanced by digital innovations. It means that lending organizations don’t have to request scoring data reports from credit bureaus. Instead, they can use the latest digital technologies to gather and evaluate customers’ digital footprint.

Utilization of credit scoring software solutions is effective when conventional bureau data is unavailable, there is little access to diverse data sources, or when borrowers fall into the group of underbanked consumers. When these situations occur, lenders experience difficulties in the proper evaluation of loan risks.

How FinTech Companies Utilize Alternative Credit Scoring

Lending companies are becoming more interested in credit scoring software today. It allows lenders to expand their customer bases by shifting their focus from credit-worthy clients to potential customers who would gain low scores in conventional scoring systems. This way, companies can offer loans to those people who have no credit histories or bank accounts, e.g. students, freelancers, households with low income, unbanked people, and others while being assured that they will pay back their loans on time.

The FDIC in its Survey of Household Use of Banking and Financial Services states that 5.4% of the US households which is equal to 7.1 million were unbanked in 2019. The US stats look encouraging when comparing them to the percentage of the unbanked population worldwide by country.