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Software & Systems

Bring on the Back-Office Bots

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August 08, 2017

Back-office processes are often dreary, repetitive and routine -- perfect for a bot.

Distributed ledgerArtificial intelligence continues to advance and find applications in new and innovative ways for corporate treasury, which holds the promise of reducing human error and costs. With that in mind, many companies are thinking about robots for tasks that don’t need a human touch.

At a recent NeuGroup Asia CFO (ACFO) meeting, members discussed how they are beginning to explore and experiment with AI in their financial operations, which are historically dependent on human intervention. Members also heard from Deloitte Consulting about what viable solutions are up and running in the marketplace and how they can be applied to finance operations.

One key takeaway and perhaps a coming normal is that digital finance is the future of finance. Finance has historically been focused on what happened and why. But the needs of the today’s business are becoming ever more predictive – what will happen and why? Operationally, digital finance is about automating labor-intensive work to free up resources for analytical, value-added work that is focused on supporting business strategy. CFOs who can embrace this concept philosophically and practically will be in high demand.

Several members acknowledged being in some stage of robotic process automation or RPA; some in a more exploratory way and others more operationally. Deloitte said that at this point, RPA technology is more readily available, effective, and affordable than people realize. And equally important, it is relatively simple to deploy. On a continuum where artificial intelligence (AI) is at the high end of digitalization, RPA is a lower-tech starting place. The functionality of the solution is to replace repeatable processing that is traditionally performed by a human. The tasks are routine and simple but high volume.

This means that currently, barriers to entry are low. Implementing RPA is much less complex that one would expect. First, according to Deloitte, RPA is not dependent on a company having strong systems integration, which is good for companies that are highly acquisitive and have disparate ERPs. Robots can be programmed to perform within whatever system they need to operate. Second, cost is also surprisingly low. Each robot can be licensed for roughly $10,000-$12,000 per year. How this compares to the cost of the person it replaces depends on the geography, but the robot also can work 24/7 if needed. But cost is not the only consideration. RPA is also about scalability, consistency and error reduction. You don’t necessarily need global process standards but you do need some governance of the program. Deloitte recommends establishing a Center of Excellence in an SSC environment.

To get an RPA off the ground, Deloitte recommends testing RPA on a process that is small scale to gain familiarity and score an easy win. You can then progress to increasingly large and complex environments, funding subsequent stages with savings from prior stages. ROI can be determined through headcount reduction and what activities are suitable for RPA. Individual robots do require a central controller for programming and coordinating groups of robots. Payback generally is within a year but could be longer in low-cost markets.

The Deloitte team pointed out that robotics implementations also can mean significant human resources change, which in turn needs more planning. Replacing people with machines comes with a price. So stepping out of traditional processes with innovative ideas such as robotics for financial operations requires courage, confidence and strong support from external advisors and internal partners. Understanding the opportunities for applying new technologies and being confident in the benefits are also required for long-term success.

But a small test of the concepts will be needed to gain support and generate enthusiasm. And experiencing success with RPA sets the stage for more buy-in as the more sophisticated technologies such as AI become more applicable.

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