Posted inEmergent Tech

How AI-driven automation in finance builds business resiliency

Emerging technologies can help organisations automate essential but non-core tasks previously done by humans. But RPA’s potential goes beyond simply replacing human effort in specific tasks, says Mauro Schiavon of Deloitte Consulting

How AI-driven automation in finance builds business resiliency
How AI-driven automation in finance builds business resiliency

Leading enterprises are highly kinetic—dynamic, resilient and seek opportunities to drive business value using the latest digital technology. Today, many companies are embracing robotic process automation (RPA) to drive value by freeing staff from manual and repetitive tasks.  

In fact, Deloitte is helping finance organisations combine the power of RPA along with machine learning and artificial intelligence to perform essential but non-core tasks previously done by humans. That is translating into finance teams closing the books faster and handling accounting exceptions in an entirely new (and highly beneficial) way.

According to Deloitte Insights’ 2020 report, Automation with Intelligence, 78 percent of organisations globally have already implemented RPA, and 16 percent plan to do so in the next three years. But RPA’s potential goes beyond simply replacing human effort in specific tasks. Organisations that are implementing automation at scale are re‑envisioning how work can be done, which means they can achieve radical change.

Automation makes people more valuable

One reason financial leaders believe RPA is valuable is that it saves money. Deloitte’s report found that organisations expect an average cost reduction of 24 percent over the next three years in the areas they are targeting.

But more mature organisations have moved away from a strategy of simply reducing headcount. Instead, they’re using the technology to increase workforce capacity.

Ninety percent of executives say they expect their automation investments to increase their workforce capacity over the next three years. These kinetic companies know that technology can provide the data and analysis to inform human decision-making, but it can’t yet replace humans as decision-makers.

More intelligence, greater resilience

Business resilience comes from the ability to respond quickly and intelligently to shifting conditions—especially significant and unexpected events like Covid-19. Automation frees people so they can work on critical activities that bots can’t do: interpreting data, addressing issues, and interacting with other people—including customers, vendors, and counterparts.

In the finance function, RPA is already proving its value with:

  • Faster closes: As these processes are getting more and more formalised, AI and cognitive technologies are handling exceptions and adjustments. Where a financial close used to take weeks, automation reduces financial closes to a matter of days or even hours.
  • Improved data confidence: Bots never get tired. They can process huge amounts of data quickly, and they don’t make mistakes. As a result, they can ensure data accuracy and integrity not with spot checks, but with continuous monitoring and exception recovery. Fewer human errors and efficient exception handling not only speeds time to value but also means better regulatory compliance.
  • Greater security: The same benefits that RPA brings to data accuracy also apply to security. Around-the-clock automated cyberattack protection is a necessity, given that hackers deploy malicious bots to continually probe systems for vulnerabilities.
  • Smarter data conversion: Automation also helps maintain security during data conversions, such as those that occur when transmitting from one system to another or migrating from a legacy environment to the cloud. Automation can continuously test to ensure that the data in the new environment is identical to the data in the previous one.

SaaS puts automation within reach

Companies that try to develop their own AI and ML-driven systems are often stymied by the complexity involved; do-it-yourself machine learning projects require hard-to-find and very expensive, highly trained data scientists. enterprise software-as-a-service (SaaS) solutions, like modern cloud-based ERP systems, offer a better way, building in RPA and other forms of intelligent automation across the platform. These capabilities can be continually updated, augmented, and integrated throughout the solution. 

SaaS platforms facilitate the uptake of new automation capabilities without the need to upgrade, patch, or purchase additional software. This lets companies reap value from advanced technologies faster than ever before. In the end, the best technology is that which frees employees to focus on rewarding work that drives the enterprise forward.