Fintech won on speed. It must now compete on understanding
Wed, 2nd Sep 2026 (Today)
On World Fintech Day, it is worth remembering how dramatically fintech changed SME financing. Over the past decade, applications that once depended on physical documents and weeks of manual review have moved online. Embedded finance has taken this further by integrating access to capital into the eCommerce, marketplace and point-of-sale systems businesses already use. In some cases, SMEs can now receive a financing decision within days or even hours.
Having started businesses myself, I know why this matters. Opportunities rarely wait. A supplier may require payment before a customer pays. Inventory may need to be secured before a major sales season. A new contract may create an immediate need for people or equipment.
Fintech gave entrepreneurs something invaluable: time.
But as operating conditions become more volatile, speed alone is no longer enough. The next challenge is understanding the business well enough to ensure that a fast decision is also the right one.
Volatility Changes Everything
In June 2026, one in six Australian businesses was experiencing supply-chain disruption, according to the Australian Bureau of Statistics. The impact was even greater in several SME-heavy sectors, affecting 28% of manufacturers, 27% of wholesale businesses and 22% of retailers.
Recent financial results from the aviation sector also illustrate how quickly geopolitical shocks can alter operating costs. Net fuel costs at one major carrier increased by 78.5% year on year during the quarter ending June 2026. With continued instability in the Middle East it poses a risk to global trade and supply chains.
For SMEs in Australia, Singapore and Hong Kong, these pressures can translate into:
- Higher fuel, freight and insurance costs
- Longer or less predictable delivery times
- Suppliers requesting earlier payment
- More capital being tied up in inventory
- Customers taking longer to settle invoices
Consider an eCommerce merchant that brings forward an inventory order because future shipping schedules are uncertain. The decision may be commercially sensible, but it could significantly reduce the company's cash reserves before those goods generate revenue.
What may have started as a 30-day cash flow gap could quickly extend to 90 days or longer, creating a timing mismatch between cash outflow and revenue inflow.
Within days, the business's financial position may look very different. Accounts prepared months earlier may show the decline in cash, but not the reason behind it.
This is where the limits of speed become visible. When an assessment relies on an outdated or incomplete picture, reaching a decision faster may only produce the wrong conclusion sooner.
Context Creates the Edge
As volatility makes historical snapshots less reliable, fintech providers must move beyond processing information faster. They must interpret what that information means.
A fall in cash reserves could indicate deteriorating performance. It could also show that a healthy business has invested earlier to protect itself against disruption. Detecting the movement is relatively straightforward. Understanding its cause is the most valuable task.
Doing this well requires three changes:
First, financing providers need more current signals. Recent transactions, invoices, sales performance, and customer-payment patterns can offer a more immediate view than annual counts alone.
Second, they must interpret why the numbers have changed. Revenue and expenditure should be considered alongside seasonality, supplier terms, delivery schedules, and the company's operating cycle.
Third, that understanding must influence the financing offered. Context should shape not only whether a business qualifies, but aso the amount, timing, and repayment structure. A fast approval offers little value if its repayment schedule pressure on the business before its investment begins generating revenue.
Artificial intelligence can support this process by analysing finacnial information at scale, recognising changing cash-flow patterns and identifying cases that warrant closer examination.
This is the approach we have taken in developing an AI-powered credit assessment engine. It was designed to analyse business data more efficiently and reduce the end-to-end fianncing process from days to hours. The objective, however, was not simply a faster decision. It was a more precise decision informed by a clearer view of the business.
That distinction is essential. AI's greatest value is not producing an answer more quickly. It is helping decision-makers ask better questions before reaching one.
The Next Race
Understanding should not be confused with automation.
AI models can still be affected by incomplete information, historical bias, and assumptions that are difficult to explain. Technology may identify a change in a company's cash flow, but human judgement is still needed to determine whether that change reflects seasonality, disruption, investment, or genuine deterioration.
A fast rejection that cannot be explained does little to improve financial access. A fast approval that overlooks whether the financing is suitable for the business is not progress either.
The responsibility of fintech is therefore growing alongside its capabilities. Financing providers must ensure that decisions remain explainable, data is used appropriately, and unusual circumstances receive human attention.
When I was building businesses, speed mattered because every day spent waiting could mean losing an opportunity. That remains true. But founders now also need financing providers capable of recognising when external conditions have changed the story their numbers appear to tell.
On World Fintech Day, the industry should celebrate how successfully it shortened the distance between an application and an answer. Its next task is to close the distance between that answer and what the business genuinely needs.
Fintech won the first race by moving faster. The next will be won by understanding better