Mapping the Future of Consumer Credit with Infact
The global credit market is colossal—so vast, in fact, that it underpins nearly every financial transaction in our day-to-day lives. Whether you’re buying a home, financing a car, or using a credit card, credit information is the backbone of these decisions. In the UK alone, almost £30 billion in consumer loans are issued every month, over 80% of UK adults hold a credit product, and there are nearly as many credit cards as there are people in the UK.
Despite the scale and importance of this market, lenders have been relying on outdated instruments that were revolutionary in their time but now struggle to keep up with the dynamic landscape of modern finance. Traditional Credit Reference Agencies (CRAs) are one of those old tools, offering a limited and sometimes inaccurate view of the world. The more you look into it, the clearer it becomes that insufficient innovation is the reason why both lenders and consumers often find themselves lost, frustrated, and unable to reach their financial destinations.
The Problem: An Outdated Map Holding Us Back
CRAs are vital to any growing market because they provide lenders with access to additional customer data that they may not have on their own. This data helps lenders evaluate – amongst other things – whether the customer and their intentions are real (fraud risk), if they can afford the loan (affordability), and the probability of the debt being repaid (credit risk).
Today financial products are more accessible and deeply integrated into our daily lives. Credit cards live in our phones, we shop and pay online, use facial recognition at checkout, and receive loan and insurance offers tied to the purchases we make. To keep up with the pace of product innovation, lenders are forced to consider a broader array of factors in their credit decisioning processes. Modern lenders are turning to alternative (i.e. utility bills and rental payments), contextual (consumer-permission bank account data and payroll information) and proprietary data (i.e. real-time signals derived from novel product structures) to refine their pricing strategies and improve credit assessments.
However, traditional CRAs – which have dominated the landscape for decades – still rely on data structures and methods that haven’t evolved with the times or adapted to the needs of modern lenders. For lenders dealing with increasing volumes and shorter maturity loans, the data furnishing process and developer experience remain unnecessarily complex and outdated.
Buy Now, Pay Later (BNPL) is one of many instances where modern services are reshaping how consumers interact with credit, yet CRAs struggle to integrate this data meaningfully. As a result, consumers using BNPL often miss out on the benefits of building a credit profile, while lenders are left with an incomplete picture of the consumer’s creditworthiness and credit history.
To imagine the world of a modern lender, consider perhaps the frustrating experience of trying to visit London using a physical map without any knowledge of the latest tube strike or delays on the District line. You might get around to seeing Big Ben and Oxford Street, but you’d be in a sweat from having chosen the Central line in peak rush hour. Worse even, the wasted time planning and dealing with delays likely means that you wouldn’t have had the chance to think about taking a stroll through Notting Hill.
For millions of people, these outdated maps create real problems. In 2024, over 16 million UK adults—about 25% of the population—had non-standard credit histories (i.e. thin file, credit impaired or highly indebted), making it difficult for them to access the financial products they need. Among these, 5 million are “credit invisible,” unable to secure loans because the old system can’t see them. The real-world impact of this is that some consumers might find themselves locked out of opportunities they deserve or saddled with mispriced credit offers that don’t reflect their true financial health.
At the same time, for lenders, this can also mean taking on unnecessary risks, missing out on potential customers, and making decisions based on incomplete or inaccurate information. Not only does a modern approach to Credit referencing improve current financial products but also allows us to build new products that better serve our modern needs. In this instance, imagine a world without innovations like Uber, Deliveroo or Strava or, more importantly, one where pilots and emergency crews struggle to get to their destinations on time, all because we chose to stick to physical maps.
