Fractal Labs' tool interprets users' data to identify blind spots, provide insights, connect business data and help businesses plan ahead
This service uses natural language processing to enable users to seek information and ask questions without needing to be experts in finance. Pretty useful, considering research shows almost three-quarters of UK small businesses do not have a financially qualified person on their staff.
At the heart of Fractal Labs' tool is a machine learning engine that identifies patterns in the financial data fed in from different sources. It then uses them to forecast the company's income and cash requirements – up to 90 days ahead.
This allows users to track their financial position as frequently as they wish. And it enables the system to alert them to issues it decides they should be aware of.
If the company needs to seek external funding, the financial information that has already been integrated into Fractal Labs' tool from different sources can be exported seamlessly, on a permission basis, to finance providers via APIs. This makes the application process as quick and frictionless as possible.
"Integrating everything into one place saves small businesses a lot of time and adds a lot of efficiency as well as giving them access to a sophisticated forecasting tool to understand the health of their business," says Nick Heller, Fractal Labs CEO.
"Our view is that this has to be done in a very lightweight, user-friendly way. People don't want to be staring at numbers all the time – they want to be alerted when they need to be alerted."
The service highlights information in graphs and numbers but adds automated text as a commentary around them. This clearly shows the points the user needs to be aware of – all of which a user can receive via their smartphone or tablet.
"We always try to position information in very graphical but more importantly natural language format, so it's more accessible for the user," says Nick. "We might say, 'it looks like you're trending in the wrong direction and here's why', and let the user ask, 'why are my costs increasing?'. We can then dive down into the data and explain.
"It's meant to be very conversational. It's a technology-based service but we're trying to create a more human-like interaction."
of SMEs don't have a financially qualified person on the team
of SMEs consider analysis of financial data a major pain point
of SMEs only apply for financing a week after it's needed