What is Cognitive Robotic Process Automation?

Cognitive automation tools can handle exceptions, make suggestions, and come to conclusions. Traditional automation requires clear business rules, processes, and structure; however, traditional manpower requires none of these. Humans can make inferences, understand abstract data, and make decisions. If you change variables on a human’s workflow, the individual will adapt and accommodate with little to not training. Cognitive Process Automation brings this level of intelligence to the table while keeping the speed of computing power. “We see a lot of use cases involving scanned documents that have to be manually processed one by one,” said Sebastian Schrötel, vice president of machine learning and intelligent robotic process automation at SAP.

Machine learning enables bots to remember the best ways of completing tasks, while technology like optical character recognition increases the data formats with which bots can interact. Cognitive automation adds a layer of AI to RPA software to enhance the ability of RPA bots to complete tasks that require more knowledge and reasoning. Organizations can use cognitive automation to automate more processes. This data can also be easily analyzed, processed, and structured into useful data for the next step in the business process. Cognitive process automation can automate complex cognitive tasks, enabling faster and more accurate data and information processing.

What does cognitive automation mean for the enterprise?

When it comes to choosing between RPA and cognitive automation, the correct answer isn’t necessarily choosing one or the other. Generally, organizations start with the basic end using RPA to manage volume and work their way up to cognitive and automation to handle both volume and complexity. RPA relies on basic technology that is easy to implement and understand including workflow Automation and macro scripts. It is rule-based and does not require much coding using an if-then approach to processing. As processes are automated with more programming and better RPA tools, the processes that need higher-level cognitive functions are the next we’ll see automated. The technology you use is determined by the nature of your process.

All of these have a positive impact on business flexibility and employee efficiency. Unlike traditional unattended RPA, cognitive RPA is adept at handling exceptions without human intervention. For example, most RPA solutions cannot cater for issues such as a date presented in the wrong format, missing information in a form, or slow response times on the network or Internet. In the case of such an exception, unattended RPA would usually hand the process to a human operator.

Insurance – Claims processing

The newest, emerging field of Business Process Automation lies within Cognitive Process Automation (CPA). While Machine Learning can improve algorithms, true Artificial Intelligence can make inferences, assumptions, and teach itself from abstract data. It solves the issue of requiring extremely large data sets, budgets, maintenance, and timelines that only innovative, enterprise organizations can afford. The simplest form of BPA to describe, although not the easiest to implement, is Robotic Process Automation (RPA). This first generation of automation, when emerging, was the pinnacle of sophistication and automation. It created the foundation for the future evolution of streamlining organizations.

Other than that, the most effective way to adopt intelligent automation is to gradually augment RPA bots with cognitive technologies. In an enterprise context, RPA bots are often used to extract and convert data. After their successful implementation, companies can expand their data extraction capabilities with AI-based tools. These technologies allow cognitive automation tools to find patterns, discover relationships between a myriad of different data points, make predictions, and enable self-correction. By augmenting RPA solutions with cognitive capabilities, companies can achieve higher accuracy and productivity, maximizing the benefits of RPA. Deloitte explains how their team used bots with natural language processing capabilities to solve this issue.

Given that the majority of today’s banks have an online application process, cognitive bots can source relevant data from submitted documents and make an informed prediction, which will be further passed to a human agent to verify. Upon claim submission, a bot can pull all the relevant information from medical records, police reports, ID documents, while also being able to analyze the extracted information. Then, the bot can automatically classify claims, issue payments, or route them to a human employee for further analysis. This way, agents can dedicate their time to higher-value activities, with processing times dramatically decreased and customer experience enhanced.

• Typically, organizations have the most success with cognitive automation when they start with rule-based RPA first.
• Intelligent/cognitive automation tools allow RPA tools to handle unstructured information and make decisions based on complex, unstructured input.
• Businesses are increasingly adopting cognitive automation as the next level in process automation.
• However, as those processes are automated with the help of more programming and better RPA tools, processes that require higher level cognitive functions are next in the line for automation.

It can take anywhere from 9-12 months to automate one process and only works if the process and business logic stays the exact same. Even a minor change will require massive development and testing costs. What we know today as Robotic Process Automation was once the raw, bleeding edge of technology. Compared to computers that could do, well, nothing on their own, tech that could operate on its own, firing off processes and organizing of its own accord, was the height of sophistication. However, that this was only the start in an ever-changing evolution of business process automation.

Marketplace supported cognitive capabilities

Cognitive automation, therefore, marks a radical step forward compared to traditional RPA technologies that simply copy and repeat the activity originally performed by a person step-by-step. Some companies use process intelligence technology what is cognitive automation for this purpose. The transformative power of cognitive automation is evident in today’s fast-paced business landscape. This makes it a vital tool for businesses striving to improve competitiveness and agility in an ever-evolving market.

Let’s see some of the cognitive automation examples for better understanding. Cognitive automation can uncover patterns, trends and insights from large datasets that may not be readily apparent to humans. With these, it discovers new opportunities and identifies market trends. The human brain is wired to notice patterns even where there are none, but cognitive automation takes this a step further, implementing accuracy and predictive modeling in its AI algorithm. The concept alone is good to know but as in many cases, the proof is in the pudding.

Cognitive automation is an umbrella term for software solutions that leverage cognitive technologies to emulate human intelligence to perform specific tasks. When it comes to repetition, they are tireless, reliable, and hardly susceptible to attention gaps. By leaving routine tasks to robots, humans can squeeze the most value from collaboration and emotional intelligence. This is why robotic process automation consulting is becoming increasingly popular with enterprises. RPA tools without cognitive capabilities are relatively dumb and simple; should be used for simple, repetitive business processes. Banking chatbots, for example, are designed to automate the process of opening a new account.

Like our brains’ neural networks creating pathways as we take in new information, cognitive automation makes connections in patterns and uses that information to make decisions. Cognitive automation has the potential to completely reorient the work environment by elevating efficiency and empowering organizations and their people to make data-driven decisions quickly and accurately. Upgrading RPA in banking and financial services with cognitive technologies presents a huge opportunity to achieve the same outcomes more quickly, accurately, and at a lower cost.

RPA and the First Steps in Enabling Cognitive Automation

The banking and financial industry relies heavily on batch activities. One of their biggest challenges is ensuring the batch procedures are processed on time. Organizations can monitor these batch operations with the use of cognitive automation solutions.

“The problem is that people, when asked to explain a process from end to end, will often group steps or fail to identify a step altogether,” Kohli said. To solve this problem vendors, including Celonis, Automation Anywhere, UiPath, NICE and Kryon, are developing automated process discovery tools. By enabling the software bot to handle this common manual task, the accounting team can spend more time analyzing vendor payments and possibly identifying areas to improve the company’s cash flow.