Rethink the finance function in the age of robots

robot finance
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James Williams
Co- founder and CEO
Beyond
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We all know the robots are coming. Coming for our data, coming for our jobs, and (if the more dramatic reports are to be believed) coming for our very existence.

Or are they?

Let's pick apart the AI fact from the hype and see where the real opportunities lie for the future finance function.

They are already here

AI is already transforming core functions of a typical accountant. Repeated processes based on structured data are ripe for automation. Things like:

  • Invoice chasing
  • Matching and reconciling transactions
  • Invoice coding
  • Anomaly and fraud detection

After all, A.I. is measurably faster and more accurate than us fleshy meat-bags at these repetitive tasks. And besides, this work is pretty boring anyway...

Nerves start to jangle when we see the next wave of intelligence being deployed. Recent advancements in natural language processing and machine learning helps AI deal with both the nuances of text and the ever-present ambiguity of a business’s finances. This brings a far greater swathe of traditional accountancy work into reach. We are starting to see:

  • Fully automated bookkeeping
  • Advanced report creation and filing
  • Analysis of legal and tax documents
  • Deep predictive analytics
  • Smart audit assistants

Expectations are changing

People's beliefs of what technology can do for us is fundamentally changing. Across almost all industries, there is a growing expectation that automation will be bundled along with core services. As we shop online, we expect to see helpful recommendations; as we get into a car we expect it to direct us to our destination (and soon to take us there altogether); as we bank we expect to get smart alerts and reminders.

Accounting is no different. There will, of course, be adjustments needed as traditional tasks are commoditised and old revenue streams dry up, but this also raises huge opportunities. This is not a zero-sum game.

In a business context, AI is nothing without people.

While AI unlocks accounting superpowers, finance professionals are needed to put them to good use. Tool selection and setup, ongoing interpretation and tuning, and - of course - accountability are all roles which will need a human touch for the foreseeable future. After all, with great power comes great responsibility.

More importantly, as accountants' time is freed up from menial tasks, they can shift their focus to a higher level, the strategic objectives of the company. Advisory services will become a fertile and lucrative hunting ground. Goodbye business policeman, hello business partner.

Power to the people

Vendors will often say you just need a smart new machine learning tool or shiny dashboard to gain a magical insight into a business. However, as any good AI engineer will tell you, an algorithm is only as good as the data it has access to.

This means, when trying to truly understand the workings of a business, you have to engage the real driving force - its people. Their knowledge and understanding of risks and plans for the future are always essential for true insights.

Here, AI can be an enabler - removing bottlenecks and giving people superpowers.

And ultimately it is a tool of empowerment - helping information flow more freely and enlightening decision-making.

Not so scary after all.

Bringing this to life

In order to build this deep partnership, it’s essential that your systems:

  1. Truly understand the business at its most granular level - its people and the context of all activities across the organisation.
  2. Always contain the most up-to-date data, link with all your tools, and can quickly flag issues, anomalies and opportunities as - or before - they arise.
  3. Enable the company to quickly act on the decisions that can be made from this data.

About James Williams

James Williames

James Williams is the co-founder and CEO of Beyond.

After completing his Masters in Systems Engineering, James spent 4 years working at Barclays Investment Bank building high performance trading systems. 


He spent half a year working in the CIO office where he gained a unique insight into dysfunctional budgeting from both the boardroom and the front line. For good measure, he also has a MSc in Machine Learning from UCL. 

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