

Today, credit scores are a crucial part of everyday life. They affect everything from mortgages to mobile phone contracts, and a poor score or lack of history can be a real barrier. But when were credit scores invented and how did they evolve?
Find out how your financial institution can benefit from real-time affordability insights to improve lending outcomes.

Table of Contents
We’ve put together a quick history of credit scores, as well as how they evolved and how they work. Stick with us to learn more or, to find out how Finexos is helping to revolutionise the world of credit scoring,book a free consultation now.
Credit scoring has its roots in the American credit bureaus of the 19th century and has evolved into a global practice that influences the world of modern capitalism.
So, when were credit scores invented? Credit scoring as we know it today evolved from the work of the Mercantile Agency, founded in New York City in 1841. The Agency would send correspondents across the US to collect information about businessmen including their race, age, marital status and credit history. This information was used primarily in business-related financial decisions and wasn’t yet a consumer-focussed practice. Needless to say, these methods were founded in the biases and opinions of the time and were far from objective or fair.
Towards the end of the 19th century, the growth of department stores and mass retail in the US saw the emergence of consumer instalment loans, much like the ‘pay in three’ type plans still in use today. The department stores and mass retail outlets needed a way to evaluate individual consumers for their creditworthiness to ensure they’d get their money back.
This need gave rise to the spread of local credit bureaus across the US. Stores would collect information about their customers and submit it to their local bureau for decision-making. From the late 1800s to the early 1960s, more than 2,000 credit bureaus emerged across the US.
However, the 1960s saw the emergence of computer technology, and credit records began to be digitised and centralised. Over the next 20 years, larger bureaus started going town to town, buying up the smaller local bureaus and consolidating their consumer credit files. By the 1980s, there were only five bureaus left, which would then shrink further to three in the coming years.
In the US today, the most popular method of credit scoring is the FICO system, developed by the FICO company in collaboration with the national credit bureaus in 1989. This new standardised method made credit scoring much more accessible to a wider number of lenders and by the mid-1990s it was becoming engrained into more and more financial decisions, primarily mortgage applications.
While the UK has adopted some of these practices, and consumers are assigned a credit score in a similar way, the methods to assess an individual for creditworthiness are far more varied. Individual lenders use their own internal calculations to make decisions, with the most popular method being a statistical model known as logistic regression. This is an algorithm that uses inputs including income, savings and credit score to predict a binary outcome; either a customer is likely to default on their loan or not.
While these individual practices vary, the world of credit in the UK is tightly regulated by the Financial Conduct Authority and consumers can report any unfair decisions to the Financial Ombudsman Service.

Now that we’ve answered the question ‘when were credit scores invented?’, let’s look at the different scoring models. In the UK, there is no universal credit score. There are three primary credit reference agencies: Experian, Equifax and TransUnion. Each uses a slightly different model to assign credit scores and not all lenders will report to all agencies, meaning scores can vary from agency to agency.
The score ranges of each agency and what they consider to be the minimum for a ‘good’ score are broken down in the table below.

The better your score, the more financial products you’ll be eligible for, the higher your borrowing limits will be and the lower your interest rates are likely to be. The process for calculating business credit scores is very similar, and takes into account the longevity of your business, financial history and credit use.
Credit scores are used as a key component in credit application decisions. Lenders will consider your credit score along with other factors when evaluating you as a potential customer.
Scores are also often monitored by your lenders on an ongoing basis to determine your continued financial stability and help spot any warning signs of distress or impending difficulties. The main uses of credit scores in the UK include:
When calculating your credit score, reference agencies collate a range of information about you, including:
Giving an average credit score for the UK is a little complicated because of the lack of a centralised scoring system. Scores will vary for each person depending on which credit reference agency you ask. However, we’ve put together some broad figures from different agencies below.
Average score by agency:

Average scores can also vary by age, as older people have had longer to amass their score and demonstrate financial responsibility. According to Equifax, the rough average scores for each age bracket are:

So, hopefully we’ve answered the question ‘when were credit scores invented?’ and provided some background information about how they evolved as well as how they’re used.
Modern credit scoring systems have changed a lot since the first credit bureaus in the 1840s, but the basic principle is still the same. However, the continuing evolution of digital technology and AI is fuelling progress and helping advance how scores are calculated. For more information, see our guide on AI in credit scoring.
Today, credit scores hold a lot of sway over people’s lives, and a poor score or lack of history can hold people back, barring them from accessing crucial products such as mortgages and vehicle finance. The way these scores are calculated is quite rigid, and founded on fixed evaluations of a person’s profile, ignoring a range of information that could provide more valuable insight into their creditworthiness.
At Finexos, we’re helping lenders to leverage AI to help them make finance more accessible to more people, combatting credit poverty. At the same time, we’re enabling them to make smarter lending decisions, reduce default rates and improve profitability.
To learn more about how our trained AI can help you improve your lending practices, book a free consultation with our team today.

Whether you’re a bank, credit union, or fintech innovator, Finexos equips your team with AI-powered insights to optimise credit portfolios, enhance inclusion, and improve financial outcomes across diverse markets.
Read more about what we’ve been up to on our mission to safely enable more people to access affordable credit.
Lending analytics uses data to offer valuable insights for credit unions, banks, fintech and NBFCs (non-bank financial companies) to make faster and better decisions. It efficiently evaluates, processes and completes financial analysis on loan applications.
The Financial Conduct Authority’s (FCA) Consumer Duty has redefined how financial services companies approach customer protection. At its heart are the four Consumer Duty outcomes – a framework designed to ensure products and services not only meet regulatory expectations but actively deliver good results for consumers.
Data from Fair4All Finance shows that 20.3 million people were living in financially vulnerable circumstances as of 2024 – an increase of 16% from 2022. Financial vulnerability can be caused by a range of factors but is universally harmful to both affected individuals and lenders.
An affordability check determines whether a borrower is qualified to receive a loan. Many factors go into deciding whether a borrower is qualified, such as their income, regular bills and in some cases even postal code.
Affordability assessments are a crucial part of the approval process for almost any financial product, from mortgages to personal loans. But what are they, how are they used, why are they so important, what criteria do they assess and what does the process look like?
The Bank of England’s latest survey on AI in financial services revealed that 75% of firms are already using artificial intelligence (AI), with a further 10% planning to use AI over the next three years. The development and implementation of AI programs requires significant financial and operational investment which not all lenders have the capabilities to undertake.
AI is transforming lending operations and unlocking a world of possibilities for consumers and lenders alike. By providing tools to improve decision-making, the utilisation of AI in lending is helping to create more financial inclusion and credit access for an underserved market. A credit decision engine that uses advanced AI also reduces operational overheads and increases efficiency.
The adoption of generative AI for the finance sector is becoming essential for managing data, mitigating risks and enabling data-driven decisions. Businesses embracing this solution are solving challenges faster and gaining a competitive edge in an ever-changing landscape. Many sectors are already using a form of AI to become more efficient, but generative AI is capable of doing so much more.
Optimising and future-proofing Loan Management Software (LMS) is crucial for adapting to evolving market demands and thriving in a competitive landscape. The use of AI is growing as a means to this end, but what are the key considerations for LMS providers when adopting it to achieve the best results?
The Consumer Duty has reshaped the regulatory landscape for UK financial services and is increasingly becoming the underpinning principal of the FCA’s supervisory approach. It sets high standards of consumer protection across financial services and requires firms to put their customers’ needs first. Lenders must ensure that their products deliver genuine value, protect customers from foreseeable harm, and equip them with the information necessary to make informed decisions.
The Bank of England’s latest survey on AI in financial services revealed that 75% of firms are already using artificial intelligence (AI), with a further 10% planning to use AI over the next three years. The development and implementation of AI programs requires significant financial and operational investment which not all lenders have the capabilities to undertake.
Finexos has formed a new partnership with Endava plc, a leading technology services company.
Finexos is delighted to announce a new strategic partnership with credit reference agency (CRA) and Open Banking Provider, AperiData.
Finexos’ AI-powered credit and affordably risk, analytics and data science platform has been accepted onto the Financial Conduct Authority’s (FCA) Innovation Pathways.
Finexos has partnered with all-in-one loan management system, Fintech Market, to enhance credit decisioning.
Finexos is delighted to announce our achievement of ISO 27001 accreditation, enabling demonstration of gold-standard data protection.
Finexos’ AI-powered credit risk and analytics platform has been accepted into the Financial Conduct Authority (FCA) Digital Sandbox.
The Finexos team is delighted to share that the company has joined Innovate Finance, the independent industry body and voice of UK FinTech.
Finexos has partnered with NayaOne to provide advanced AI-powered Loan Book Vulnerability Analysis (LBVA), that reduces defaults and increases Return on Capital Employed (ROCE), via the NayaOne marketplace and Digital Transformation Platform.
The Consumer Duty is now in force for new and existing products and services.
In a recent BBC interview, the EU’s Competition Chief, Margrethe Vestager, expressed her concerns about the potential for AI to amplify bias or discrimination in loan and mortgage decisions.
The Finexos Board is delighted to announce the appointment of Darren Smith as Chief Executive Officer.
Growth Capital Ventures has led a £695,000 investment round into Finexos, a fintech platform set to improve access to credit for millions of people around the world.