Artificial Intelligence
4 charts that show the opportunities and challenges of RPA
- Automation has the potential of transforming the financial industry.
- Given organization challenges, though, it's not a done deal.
The hype machine is revving up for the arrival of robotic process automation, or RPA. As with most new technologies, the fanfare is way ahead of where adoption is today.
Combining machine learning, artificial intelligence, and big data, automation today is best suited to complete menial, repetitive back office tasks. Though the deep technology isn't ready yet, we're eventually talking about machines thinking and acting like humans.
Here are four charts that show the size of the automation opportunity along with the challenges associated with rolling out such an ambitious set of technologies.
Consultants like to whip up the financial FOMO whenever a big new technology appears on the scene. While the market appears to be massive, the financial industry isn't quite there when it comes to adopting RPA. Nearly two-thirds of respondents to a new KPMG study plan to fully implement RPA within three years.
There will be challenges, though. Slow rates of adoption and implementation can be further hindered because of looming organizational challenges common in the financial industry.
Automation isn't binary -- it doesn't happen that a company just turns on automation from one day to the next. It's a spectrum, and as companies begin to experiment and rollout RPA, they move away from just creating islands of automation to incremental and even transformative business models.
"A lot of change has to happen that’s really uncomfortable and sometimes political, and most companies are not prepared for that," said Cliff Justice, KPMG partner and leader of Cognitive Automation initiatives. "Projects implemented from the bottom up are not going to scale because they haven’t been designed to scale. If this isn’t a C-level initiative, then it’s not going to be successful at scale."
When polled, executives first point to the back office as the first destination for automation technologies. With this view, automation onshores many of the activities that were sent offshore over the past two decades. But instead of a desk jockey hammering out reconciliation reports, it's an army of bots filling in spreadsheets while we sleep.
But the more forward looking leaders can see beyond the financial industry's biggest cost centers. These executives look out to the front end of the organization -- to customer service and marketing -- to unlock the value in automation.
The RPA market is growing quickly. Depending on how broadly you define the market to include artificial intelligence and machine learning, we're already talking about billions of dollars. It's the expected growth a few years out where things start to get interesting.
But getting broad adoption will be an issue. Moving from small POCs to broad adoption of automation requires sweeping company changes. Not all financial institutions will make the leap.
"Many traditional businesses with legacy approaches risk falling behind digital-first companies if they stay with the status quo," said KPMG's Justice. "It takes a comprehensive transformation of business and operating models to compete in their own market at the level at which a Tesla or Amazon do in theirs."
RPA isn't quite here yet
Consultants like to whip up the financial FOMO whenever a big new technology appears on the scene. While the market appears to be massive, the financial industry isn't quite there when it comes to adopting RPA. Nearly two-thirds of respondents to a new KPMG study plan to fully implement RPA within three years.
There will be challenges, though. Slow rates of adoption and implementation can be further hindered because of looming organizational challenges common in the financial industry.
4 stages of intelligent automation
Automation isn't binary -- it doesn't happen that a company just turns on automation from one day to the next. It's a spectrum, and as companies begin to experiment and rollout RPA, they move away from just creating islands of automation to incremental and even transformative business models.
"A lot of change has to happen that’s really uncomfortable and sometimes political, and most companies are not prepared for that," said Cliff Justice, KPMG partner and leader of Cognitive Automation initiatives. "Projects implemented from the bottom up are not going to scale because they haven’t been designed to scale. If this isn’t a C-level initiative, then it’s not going to be successful at scale."
Bot farms in an office by you
When polled, executives first point to the back office as the first destination for automation technologies. With this view, automation onshores many of the activities that were sent offshore over the past two decades. But instead of a desk jockey hammering out reconciliation reports, it's an army of bots filling in spreadsheets while we sleep.
But the more forward looking leaders can see beyond the financial industry's biggest cost centers. These executives look out to the front end of the organization -- to customer service and marketing -- to unlock the value in automation.
The market for intelligent automation
The RPA market is growing quickly. Depending on how broadly you define the market to include artificial intelligence and machine learning, we're already talking about billions of dollars. It's the expected growth a few years out where things start to get interesting.
But getting broad adoption will be an issue. Moving from small POCs to broad adoption of automation requires sweeping company changes. Not all financial institutions will make the leap.
"Many traditional businesses with legacy approaches risk falling behind digital-first companies if they stay with the status quo," said KPMG's Justice. "It takes a comprehensive transformation of business and operating models to compete in their own market at the level at which a Tesla or Amazon do in theirs."