By Jessica Sier

When a Texan business contacted Chris Hooper via Twitter to request his accounting services, Hooper sensed a much bigger opportunity. He had long been watching the freelance economy gaining traction and the barriers to hiring offshore talent disintegrate.

That a US company was reaching out across the Pacific, desperate for someone who was comfortable with modern accounting software to fix the mess its “old school” firm had left, was all the confirmation Hooper needed.

Chris Hooper

“Their local accounting firm had butchered their Xero file by treating it like a desktop QuickBooks file,” he says.

“And suddenly, here I am as an Australian accountant servicing a multimillion-dollar Texan company and I’m thinking, ‘If there’s one, there has to be way more. And I know a lot of other young accountants who would want this kind of work’.”

Accodex was born out of several of Hooper’s assumptions about how the global accounting profession would evolve. The advent of cloud software, the democratisation of the global labour market, and skilled accountants wanting to find their own clients meant Hooper and his co-founders could design a network that allowed professionals to run as independent businesses.

“We built a hub-and-spokes market network [using, as an example, an M&A transaction, plus all the parties and counterparties that go along with that] where accountants, lawyers and other vendors all work on the same file.”

“We built a hub-and-spokes market network where accountants, lawyers and other vendors all work on the same file.”

But one key distinction between a market network and a freelance marketplace is that accountants on the platform source their own clients outside and then fold them into the network. “So accountants are out there hunting and killing their own work and bringing it to us.”

The next step, Hooper says, will be to unify all the data. It’s not uncommon for accounting techs to be running 40 discrete applications, 40 discrete databases, and the only solution for absorbing them all is to warehouse that data then run machine-learning algorithms across the top.

Hooper and his team are hoping to develop the kind of unified database for a future in which machine learning is widely used and commercially viable.

“I accept that machine learning is a given,” says Hooper, “so I got a pen and paper out and started sketching that architecture. It really pays to be ahead of the trend.”

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