Thought leadership: how data-driven lending can solve the SME funding gap

09 December, 2020Helene Panzarino

Small to medium size companies have suffered from a large, persistent funding gap for decades, primarily because banks haven’t been able to offer suitable lending products. But thanks to data, analytics and technology, lenders are now able to provide SMEs with finance that meets their needs.

Neon sign saying openSmall and medium sized companies, that are key contributors to gross domestic product (GDP) in many countries, always have to sit on the financial side lines, prohibited from playing on the main funding stage.

As a result, they have to seek creative – sometimes foolhardy – solutions to their financial needs.

The reasons why they find themselves in the role of financial outcasts are varied. However, they mainly stem from banks being unable to make the right kind of lending products available at scale.

Small to medium enterprises (SMEs) have not always got the products and services they required, because of:

  • risk factors
  • pricing pressures
  • patchy availability of 360-degree data, and
  • out-dated technology.

To add to this, deal processing was slow with lenders who typically made lending decisions based on a business’s historic information.

But historic information is not going to be much use as we navigate the choppy waters of Covid-19. That was then and this is now – the new now.

So smart metrics with a forecast view – as opposed to a forensic view – will be required by both business owners and banks.

How traditional credit processing methods have been superseded

One company trying to bridge the £1.2 trillion global credit gap for SMEs with data solutions is Australian-based Trade Ledger. They carried out a study which found that with traditional credit processing methods:

  • 57% of SME credit applications are abandoned
  • SMEs spend on average 30 hours applying for credit
  • SMEs wait an average 120 days for funds to reach their account.

Historically banks monopolised the credit market for SMEs and were always risk averse – tending to skew their business towards the safer end of the credit spectrum.

However, from 2008 – when the banks tightened their lending criteria even further – a new type of non-bank lender emerged, offering borrowers cheaper options of credit.

These new lenders applied technology to the lending process, which reduced both the timescale to underwrite an application – and the costs. They opened up new distribution channels, making it easier and quicker for SMEs to access funding options and further disrupting the market for incumbents.

They opened up the market with more choice for SMEs seeking capital. They matched today’s chief financial officers (CFOs) – forward looking, strategic, data driven executives – with credit providers who shared their ideology.

This new type of data-driven lending solutions continues to help solve the SME funding shortfall. What’s more, these new lenders have ambitions to become the engine for the truly scalable growth of open finance.

How data and analytics can make the credit industry more efficient

The transition to a digital economy has accelerated in the last couple of years – not just for borrowers but for the entire credit sector.

Technology has redefined the traditional approach to underwriting. And financial institutions have more dynamic instruments to study:

  • borrower types
  • risk bands, and
  • target yields.

Lenders have real-time cloud accounting systems. So there’s no need to use bills of lading and other archaic tools when their customers are moving to real-time supply chains based on smart inventory tracking.

Lenders that use data are not only more agile and cost efficient. They can identify market opportunities quicker and scale the technology across different geographies and regulatory environments.

By accessing data in real time, they can automatically structure and tailor loans to the borrower’s profile, which also drives improved customer satisfaction. All businesses are unique and so are their credit requirements.

Knowing the answers to questions – such as how many payments are made on time, what business cycles for trading and cashflow are happening, and so on – allows lenders to make smart data-driven decisions.

Lenders realise that the future of business finance is not just better products. They need to create bespoke lending services for individual customers based on insights from data that they’ve interrogated. And they must supplement these new offerings with services from associated parties.

If a lender wants to attract and retain SMEs, it’s no longer enough to offer a basic account and a lending facility. Marketplaces, improved point-of-sale offerings, geolocation marketing – and a whole host of other more embedded solutions – are required.

Helene Panzarino 
Helene Panzarino is the Fintech Programme Director at LIBF's Centre for Digital Banking & Finance. Originally a Commercial Banker, Helene is an experienced fintech ‘sherpa’, programme director, exited entrepreneur, educator and author. The CEO of New Financial Laboratory, she takes community banks to the digital future by connecting them to the fintech of the present. 

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