Humans, Robots Must Combine in Digital Ecosystem

With the pressure to adapt to digital, many CFOs are responding by using technologies on a one-off basis.
Felice PersicoJune 27, 2017

It is the dawn of a new era for the finance function. This might sound like hyperbole, but it is a reality for a CFO in the midst of digging into masses of data to provide boards with analysis of more complex information while sticking to the existing reporting schedule.

Felice Persico

Felice Persico

Technologies like data analytics, robotic process automation (RPA), and artificial intelligence (AI) are dramatically shifting how the finance function works. And it requires an equally significant shift on the part of finance professionals in the way they do things. This raises the inevitable question: which of these two actually delivers value in a digital world — humans or machines?

With the pressure to adapt to digital, many CFOs are responding by using technologies on a one-off basis, taking advantage of RPA here and some analytics there, and that is leading to silos. But to maximize the effect of what these innovations offer, companies must better connect different technologies and then combine them with human capability.

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Take RPA, which can help enable the automation of repetitive, high-volume tasks. Used alone, it has great advantages, such as increased speed, efficiency, and accuracy of manual tasks. That in itself is already progress. Yet layering machine learning on top of it is where you can truly take advantage of technological advances.

For example, it is not uncommon for companies to have hundreds of thousands of lease contracts. Machine learning can digest large volumes of contracts and assist the user in determining whether it is a capital lease or an operating lease, which further determines the right accounting criteria and accounting treatment.

RPA can be used to gather the right information, compare it to existing account records, and assist in reconciling the outputs. The AI capability adds another layer of sophistication, enabling the machine to provide recommendations and suggest actions.

Imagine the level of insight AI can provide by sorting through complicated, and often high-value contracts to extract meaning, define complex clauses, and find outliers. It could look for different definitions of “indemnity,” for example, or highlight unusual payment profiles.

Then it could gather the 20 most representative contracts and the 20 most unusual contracts, meaning that CFOs can gain a better understanding of risk in their business.

Essentially, you only realize the full potential of the technological advances when you connect technologies and make the user experience seamless. Although analytics can be put to work with one data set, the true value is when analytics takes data from multiple sources and starts to drive exceptions and correlations. Consider how, within the audit, data analytics could further allow auditors to focus on the right risks earlier on.

This could mean isolating transactions that have different risk profiles and applying specific audit strategies in those areas. For example, by conducting robust testing and analysis to higher-risk manual transactions, auditors can alert the CFO if there has been an unusually large percentage of credit transactions processed inappropriately. And that could indicate fraud or misstatement.

Optimizing the potential of combined technology to improve existing processes requires creating seamless workflows between humans and machines. Companies still need the right mix of talent (traditional audit skills blended with new skills like data analytics) as well as technology, as they pivot to new ways of working.

It is about enabling better interaction between humans and technology in this digital ecosystem. The focus should be on providing the most value, which is at the point where we provide judgement or make a business decision.

Where can new technologies take us next? What if an auditor can download a company’s ledger in real-time and upload it for bots, which then can apply procedures and test it, and apply the vast majority of controls?

Deep learning techniques can be applied to other more complicated controls in cases in which the transaction is not routine. Auditors can then focus even more on providing professional skepticism and judgment, leading to higher quality audits.

At the end of the day, it is about how we connect all of this technology to create a digital ecosystem. Instead of seeing innovation in isolation, the real power will come from integrating it and combining it with human capability. That is what will create a true end-to-end digital solution where both humans and machines work together to deliver value.

Felice Persico is global vice chair of assurance at EY.