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In the early 20th century, modern credit bureaus were formed, looking more closely like we know them today. Taking a page out of the commercial-loans book, retailers began offering consumer credit to individuals. These retailers all had individual credit managers, tasked with determining creditworthiness of applicants. In 1912, they decided to band together and formed a national association to “develop a standard method for collecting, sharing and codifying information on retail debtors.”

In subsequent years, the three major credit bureaus in the U.S. were born – today known as Equifax, TransUnion, and Experian. Through the 70s and 80s they worked together to develop consistencies in credit reporting methods and pushed for an unbiased, more automated way of determining credit scores.

A credit report comes first. A detailed historical record of your financial transactions and financial status, a credit report includes everything from identifying personal information (name, address, date of birth), to consumer credit accounts (credit cards, lines of credit, auto loans, mortgages), and ‘inquiry’ information (i.e., information on the companies who have pulled your credit report to make you offers of new credit products, or pre-approvals for upsells, etc.). A credit score is then calculated based on that information. Typically a three digit number (we’ll get into regional differences later), this credit score quickly tells potential lenders how creditworthy you are. In North America, the higher the score, the lower risk you are and therefore, a more worthy applicant.

Traditional credit scoring systems are not without fault, however. They often don’t take into consideration additional factors that can influence your credit risk level (i.e., most modern credit reports don’t include rental payments, which can be a very accurate predictor of someone’s propensity to pay back debt.) And there can be a significant lag between an applicant’s activities and pulling a credit report/score – real-time data is much more valuable (and accurate) in assessing an individual’s risk.

So how do credit scores really work? A mathematical formula based on the information found in your detailed credit report, a credit score allows potential lenders to instantly assess how creditworthy you are. A higher credit score indicates that a) you are more likely to pay off your debt/repay any credit provided and b) pay off that debt both on time, and according to the agreed-upon terms. With a more favorable credit score, you are more likely to have lenders extend you credit products, such as new credit cards, auto loans, mortgages, and consumer loans. Beyond that, the higher your credit score, the more likely it is that lenders will offer you better terms, including flexible repayment schedules and lower interest rates. If you are stuck carrying a low credit score, you run the risk of not being able to access credit when you need it or having to accept higher interest rates.

A FICO score (Fair, Issac and Company) is one of the most well-known credit scores in the US. In fact, “FICO scores are used by 90% of the top US lending institutions for their risk assessment needs.” These three-digit scores, which first began in 1989, are calculated based on the information found in your credit report from one of the three major credit bureaus. There are five main factors that FICO uses to calculate your credit score, with different categories carrying different weights. (Sidenote: other credit scores are calculated much the same way but may have different weights associated with the main contributing factors.)

For FICO scores, the factors are:

Despite the overwhelming prominence of the United States’ three main credit bureaus, there are regional differences in credit scoring models and the use of credit scores. While each region uses the same basic premise of evaluating an individual’s credit history to determine their creditworthiness, there are variations in how that credit scoring is executed. The main variations in credit scoring methods relate to:

A credit score that is rated as ‘good’ or ‘excellent’ will save most people thousands of dollars over the course of their lifetime. If you have excellent credit, you get better rates and payment terms on everything from mortgages and auto loans to credit cards and lines of credit – essentially anything that requires any sort of financing. If you have a better credit rating, you are seen as a lower-risk borrower, with more banks and lenders readily competing for your business by offering better rates, fees, and perks. On the flipside, those with poor credit ratings are seen as higher-risk borrowers, and may either have less favorable lending terms (higher interest rates in particular), or be unable to access credit at all when they need. Apart from just accessing lending products, those with poor credit scores may find it difficult to find rental housing, rent a car or even obtain life insurance.

Lenders use credit scores as part of their risk decisioning process to determine the creditworthiness of a potential individual or business customer. So, the ripple effect of either a positive or negative credit score is significant – and it can last an incredibly long time, particularly if there are delinquencies or defaults noted on your credit report.

However, part of the issue with this is that credit scoring can often have inherent biases. This greatly impacts various demographics from fairly accessing credit. For example, immigrant communities may not have formal credit histories. No credit history = low credit score. Low credit score means they can’t easily access lending products and therefore can’t start building a credit report/score. Or they are forced to accept suboptimal terms with exorbitantly high interest rates and may have difficultly paying down that debt as a result. Which of course, is a mark against you on your credit report.

The example above is not uncommon in our global society – there are countless immigrant populations in countries all over the world, and millions more who have no access to formal financial services products. There are many terms for those who lack a traditional credit history – thin-filed, credit invisible, unbanked, underbanked – but it essentially refers to anyone who doesn’t have information in their official credit history/report to generate a credit score. This includes an estimated 62 million Americans, 200 million people in Latin America and 3.6 million in Asia having no access to formal credit. One-third of all adults globally (up to 1.7 billion people) lack any type of bank account.

How can lenders ensure equal access to credit, even for those without formal credit histories, without sacrificing their risk strategy? One way is to use alternative data. Alternative data includes anything outside of a traditional credit report that may indicate creditworthiness, including telco information, rent and utilities payment info, social media and web presence, travel data and open banking info.

Because this type of data is often missing from traditional credit reports (and thus the formulation of credit scores), they can be inherently biased towards certain minority demographics. The data that FICO scores consider (like payment history, length of credit history, etc.) is also often influenced by generational wealth and the passing of large assets like homeownership (i.e., mortgage data counts towards your credit score, rental payment usually does not). “The Black homeownership rate was 44% at the end of 2020 compared to the 74.5% rate for non-Hispanic white consumers. Since credit scoring models look at homeowners’ housing payments and ignore renters’ rental payment history, Black consumers are at another disadvantage, despite both types of payments falling under the same category of “housing.” Ensuring that lenders are supplementing traditional credit scores with alternative data helps to overcome that bias and ensures financial inclusion.

Using alternative data helps to provide a more holistic view of the financial health (both current and future potential) of customers, improves decisioning accuracy and even helps increase fraud protection with improved identity verification and KYC onboarding processes. Enabling more accurate credit decisioning allows lenders to expand their market safely, without increasing risk, and helps to encourage access to all unbanked/thin-filed individuals, setting people on the path to safely building their credit scores. Eighty-seven percent of lenders using alternative data are using it to more accurately evaluate thin/no-file customers and 64% improve their risk assessment among unbanked consumers.

Apart from individual lenders looking to alternative data sources, some credit bureaus are now offering ways to boost credit scores for thin-filed consumers:

Also, read:

What is Banking as a Service?

It’s clear that credit reports and credit scores have a significant impact on your ability to access credit. But as the financial services industry evolves, there are more and more innovative ways to determine creditworthiness, including the integration of alternative data, implementation of advanced decisioning solutions, and using more accurate, predictive models with artificial intelligence. And there are now more varied opportunities to access credit and financial services products, including the advancement of buy now, pay later (BNPL) solutions, and neobanks and fintechs who are taking a fresh approach to credit products.

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