Nos perspectives

RPA: Leveraging automation while managing risk

A prudent approach required

The prospects of lower costs, higher productivity, and improved compliance offer a compelling business case for the adoption of Robotic Process Automation (RPA) technologies. Achieving a return on that investment requires a commitment to build and design holistic solutions, and recognition that the digital workforce of the future will still require the human touch in managing risk and building confidence with clients and stakeholders.

A robotic revolution?

Key insights

  • Automation's potential benefits can be hindered by flawed use cases and over-complication during implementation
  • Robotic solutions will be welcomed by firms concerned about fraud, and regulators seeking detailed data logs
  • The uptake of RPA and AI may be crimped by skills bottlenecks, meaning firms must be prepared to train current employees to design and run the technologies

The use of cognitive automation technologies is expected to have a profound effect on the future of work including the use of robotic processes to complete repetitive manual tasks with human employees re-deployed to undertake more value-add activities. While automation is tipped to replace 20–40 percent of the jobs that comprise current labour markets, the losses are expected to be broadly offset by new and different jobs created as a result of the increased economic activity and wealth made possible by the technologies.1

Organizations that have invested in RPA, generally defined as the automation of rules-based processes with software that utilizes the user interface, believe it can provide more full-time equivalent (FTE) capacity. In addition to process efficiencies, robotics also offer firms a consistently growing repository of data, which opens up new opportunities to leverage that data and feed it into other cognitive and Artificial Intelligence (AI)-type technologies.2

Automation growing pains

Despite the many benefits of RPA, broad adoption remains in its infancy and for organizations that have launched automation efforts, implementation and scaling challenges are a recurring theme, according to panelists at a recent Financial Services Council's Technology Workshop Series event on AI and RPA in Sydney. The teething issues can derive from a variety of factors but are often traced back to flawed use cases.

In addition to process
efficiencies, robotics
also offer firms a
consistently growing
repository of data

Moderator David Evers, Director of Client Experience & Solutions at RBC Investor & Treasury Services, said managers at financial services companies need to ask themselves whether they have sufficient understanding of the problem that needs to be solved. “Am I solving a client problem or just automating a bad process that needs re-engineering?"

Even with sound use cases, implementation can get stalled in organizations that are more attuned to managing large platform rebuilds than smaller pilot programs. With large project management teams and detailed change controls, the programs can become so expensive that business cases fail to stack up, panelists said.

Conversely, there are also difficulties for firms that confine automation initiatives to isolated departments, as broader buy-in and support is important in helping to facilitate implementation. “We're seeing large corporations dabbling with AI, but they are doing so in isolation," said Brent Davids, Vice-President at TTEC Digital, an AI consultancy. “They are not adopting a holistic view and implementation is very much in silos."

Scale brings cost, quality, and control benefits

Firms that successfully
scale the technologies
are reaping non-financial
benefits like faster
decision-making,
reduced operational
risk, and increased
efficiency

Despite implementation risks, firms that successfully scale the technologies are reaping non-financial benefits like faster decision-making, reduced operational risk, and increased efficiency along with significant cost reductions. Deanne Hurley, Head of Transformation at BT Financial Group, said RPA had reduced call times between call centre agents and financial advisors seeking superannuation information about their clients from 20 to 30 minutes, to about two to three minutes. “Our bot is actually collecting all that information. We are providing this back to the advisor as a well-organized PDF which has all the information documented," she said.

Financial institutions have taken the lead on automation but it is expected to become ubiquitous in other industries, fulfilling regular financial functions such as data entry, record-keeping, and reporting. Automation's application in regtech, the use of technology to fulfil regulatory requirements, is also yet to be fully realized. With the ability to efficiently produce well-structured and accurate data, RPA and AI can perform tasks that will naturally appeal to regulators seeking logs of information for compliance checks.

“Historically, when regulators have come in and said 'Look, I need information on X, Y, and Z and what happened,' we would need to go and find the documentation. Now we can just pull the robot log because we archive all of the data. We've got it down to a key-stroke," said Hurley. “Our processes are more robust and less error-prone than they were before."

Rebuilding trust through accuracy

Such functionality is attractive in Australia, where a Royal Commission, the country's highest-level public inquiry, has uncovered widespread malfeasance by banks and other institutions, and shaken client trust. “Post-Royal Commission, we are all very focused on rebuilding and maintaining trust. So automation, both AI and RPA, has a very strong role to play in us being able to evidence to our customers, our shareholders, and to the broader community what we're doing has integrity, and is ethically sound," added Hurley.

Maintaining the digital workforce will require human skills

Ambitions may be high but the development and adoption of automation may be crimped to some extent by skills shortages, which panelists suggested may be a factor in the technologies' relatively slow uptake in Australia compared to global peers. Panelist Simon Hicks, Cognitive Artificial Intelligence & Business Development Director at IPsoft, said there was “huge" concern that Australia was being left behind in healthcare, while Hurley felt the nation's financial services industry was up to four years behind the curve.

“There's a shortage of skillsets in the areas for these technologies," PwC partner and technology risk expert Nicola Costello told the workshop. “With the skills shortage in Australia I don't think we have another option than to take smart, capable people and try to train them up."

This means firms will need to imagine and plan for the future shape of their workforce as they roll out automation. “How do we make sure that we still have a good value proposition as we start to digitize?" said Costello. “We want to be able to attract the best people and retain the knowledge needed to successfully build, test, and run this technology."

 

What is Robotic Process Automation (RPA)?

RPA is the use of software to process and manage repetitive tasks previously performed by humans. RPA is most commonly applied to rules-based predictable and replicable processes that require the handling of high volumes of structured data. RPAs can perform these repetitive tasks more quickly, and accurately, freeing employees to focus on higher-value tasks that required human strengths such as emotional intelligence, reasoning, judgement, and client interactions.

 

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