Does bias affect lending to SMEs?

60 min watch

Why is it so hard for small and medium-sized enterprises to get business loans? SME lending represents a huge market for business finance. Around £5.4 trillion worth of missed opportunity. The difference between supply and demand for working capital credit for SMEs is shocking. It begs the question, what’s stopping banks and alternative finance houses from lending to SMEs?

We asked the expert

Trade Ledger invited Tobias Baer to share his thoughts on these questions in conversation with Martin McCann, Trade Ledger’s CEO and founder. Tobias is an independent senior advisor to financial institutions and fintech and a scholar cooperating with the University of Cambridge. He specialises in Data Science, Risk Management, and Psychology, and shared some invaluable, real-world insight into the question: is there some bias in the data?

Short answer: yes, quite a bit. But there doesn’t have to be.

It’s not the lenders’ fault, necessarily. The bias is systemic. It is practically embedded in the products, technology and processes that have remained largely unchanged for the past 30-plus years.

Tobias pointed out three levels where bias comes into play:

  • Strategic bias. “Small businesses are risky, expensive and difficult to serve.”
  • Decision bias. “We use the same criteria to decide whether to lend to large business or a small one.”
  • Cognitive bias. “I have to do as much to manually underwrite a small loan as a large one.”

Essentially, the lending industry is engineered around lending to large companies. Little wonder that, according to our data, 57% of SME applications for credit are abandoned or rejected.

SMEs are seen as difficult to lend to for a number of reasons. There’s volatility: a SME may be more reliant than a larger company on a key individual, customer or supplier, and therefore can be more affected by market changes. Then transparency: auditing and reporting are generally more relaxed for SMEs, so their situation is more opaque. And there’s profitability. The profit margin for SME lending is generally smaller, so why spend assessment or underwriting time and resources, when there are bigger returns to be had from the same effort with large companies?

What’s the answer?

If only lenders had some way of speeding up how they find, and assess the risk of lending to, those SME gems.

They do. It’s in the data.

Not just the backward-looking financial data but operational, up-to-the-minute data that’s available on demand. Data that provides insight into much more than financial performance. Data that indicates the personality, operations and relationships that paint a fuller picture of the SME.

That is where the problem (and opportunity) lies. Most lenders are not looking at data in the right way. They aren’t even looking at the right data. They cannot get a handle on the amount of digital data that is available for informed, insightful decision making. They may not have much appetite to use new data sources to find out about the profitable SMEs that represent whole new markets, let alone the desire to serve their needs. All of this introduces bias into their decision-making. It’s time for a new approach.

Redefining the future

The world is facing a lot of disruption from Covid, climate change, political change, rapid innovation, and other factors. Lenders must become more agile, in order to partner with the SMEs that respond to these challenges. Being open to understanding digital data makes it easier to be agile in lending, and for that you need a plan.  

There are so many more answers in the far-ranging discussion between Tobias and Martin. It’s an enlightening 45 minutes that will have you thinking differently about the world of SME lending – including how assessing risk can actually push lenders towards higher-risk borrowers, what laundry bills reveal, and the role of machine learning/artificial intelligence.

We love to talk about any aspect of business lending, chat with us.

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