Algorithms vs Experience: SME capital raising for special situations in the new world
In ‘Top Gun Maverick’, Tom Cruise plays an old-school flyboy. He believes the new generation of pilots has become too reliant on theory and technology. Maverick instead values instinct and experience and so is at odds with the hierarchy. There is one scene where the Rear Admiral says to Tom Cruise “the end is inevitable Maverick. Your kind is headed for extinction”. Tom Cruise replies: “Maybe sir, but not today”.
Is algorithm lending the future?
For the new generation of commercial finance professionals, algorithm-based lending seems to permeate every corner of the commercial finance market. To the point where some brokers think that capital raising via asset-based lending, assessed using human experience (rather than algorithms) is headed for extinction. Maybe – but not today – and not for lending in special situations or where the capital raise is larger (in excess of $1M).
By special situations we mean those defining events in the life of a business. They include distress, business turnaround, business acquisition and major strategic transitions. Situations where historical information is less relevant than an understanding of the future of the business.
Key data point algorithms
Let’s look at three of the data points algorithms used for credit assessment, and see how they stack up against an experienced lending team of specialists:
Financial statements
Algorithms assess a small business’s balance sheet, income statement, and cash flow statements to assist in decision-making. For maybe 70% of lending scenarios this makes sense. However financial statements are historical documents – certainly evidencing any mistakes a business has made. They don’t however consider how business restructuring or other strategic changes a business makes will play out in the future, potentially supporting the decision to lend.
Revenue and cash flow
Some algorithm-based lenders have excellent technology for scraping data from bank statements. There is no doubt such data can provide powerful insights into a business – particularly where financial statements are not available. Again, however, this is historical information. Excellent for providing quick decisions for 70% of lending scenarios, but largely irrelevant in a restructuring scenario where the business moving forward may be very different to the business looking backwards. In those instances, we need to consider the restructured and re-capitalised balance sheet.
Business history and credit score
Algorithms are very reliant on credit scores. In the past, a credit report was only useful for showing any adverse credit history. Today’s credit reports produce a magical number that you might be forgiven for thinking was inscribed on a tablet from Mt Sinai. Certainly, a credit report can provide new information. But the credit score itself plays no part in serious commercial lending in special situations.
The future
There is no doubt the data-crunching technology available to lenders today has streamlined mainstream small-business lending.
In special situations – particularly where the funding requirement is upwards of $1M, it takes an experienced team to interpret historical financial data in the right context; read and understand sophisticated financial forecasts; and view not just the history of the business, but its potential future as a restructured, recapitalised business.
Maybe AI and algorithms will ultimately replace the experience and instincts of a specialised asset-based lending team of professionals. But not today!