Despite this, they often face impossible hurdles when they need money to cover cashflow or expansion. And things have been getting worse. Trade association UK Finance revealed that lending to SMEs dropped 22% in 2023 to £14.3 billion, down from £18.4 billion in 2022. This marked the third consecutive year there has been such a decline in gross lending in the UK, highlighting the urgency for action within the industry to improve access to credit for cash-starved SMEs.

The reason behind restricted lending to SMEs is simple: data. If you only measure the data points available via a traditional lending process, you will miss what’s special and unique about each small business, and dismiss them too quickly.

Many small businesses are unfairly seen as unprofessional, and not standardised enough to accurately assess risk – unless you know exactly where to look in the data. 

Better use of data can redress the balance of fairness

But there is hope for beleaguered small businesses.

The emergence of easy-to-integrate, powerful artificial intelligence (AI) tools in a maturing open banking environment means that data can be used more wisely to properly analyse an SME’s prospects to provide them with hyper-personalised and accessible funding to grow their revenues.

More data, more accurate data, data that’s easier to access, and a deeper understanding of this data is what matters – and it’s shifting the dial when it comes to cracking open small business finance.

Fintech providers are now harvesting the data-rich open banking landscape to offer alternative funding sources. This includes revenue-based finance, which enables SMEs to access funding based solely on their overall business revenue. It’s one of the most cost-effective options available to small businesses.

Revenue-based finance is growing in line with embedded finance as ambitious small businesses move away from traditional banking and towards more integrated financial services that have been seamlessly embedded within their preferred marketplaces and platforms, whether that’s Amazon, eBay, their accounting platform, or one of the social media giants. As a result, the global embedded finance sector is now projected to grow at a Compound Annual Growth Rate (CAGR) of 32.8% from 2024 to 2030.

Because embedded finance providers partner with the marketplaces and platforms that small businesses already use and can access their data, they can quickly gain a comprehensive understanding of the merchant’s revenue and pre-approve funding – eliminating the fear of rejection that keeps many small business owners up at night.

Providers can then holistically analyse a company’s revenue patterns to offer a tailored funding solution that sees businesses only paying back a percentage of their earnings, when they earn. This more equitable and efficient funding process contrasts with traditional financing methods, such as equity debt or term loans, which are often slow and rigid.

Revenue-based finance offers small businesses a number of welcome benefits. They can typically apply in minutes and receive funding within days. It’s also flexible. If revenue slows down, so will repayments. This repayment structure allows the smallest businesses to better absorb revenue fluctuations.

Importantly, revenue-based finance is a lot less risky because there is no requirement to give away any equity or control to external investors, nor are there any stressful personal guarantees. Instead, the funding is provided based on the overall health, and prospects, of a business.

Solutions that can be trusted

The more established fintech providers in the market have developed robust data management processes over the years they’ve been active.

At Liberis, for example, we partner with payments, marketplaces, food delivery, salon management software and many more verticals to reach a diverse range of small businesses. Each partner offers unique insights into specific industries and which data points indicate high performance.

We’ve learned to incorporate this rich data and build a flexible platform to take in the data points that our partners know make a difference when spotting brilliant small businesses. We then use this data to train our AI, incorporating everything from food hygiene ratings and customer reviews.

Every data point helps us to discover hidden gems so that we can extend funding to the small businesses that need – and deserve – it.