Cognitive Robot Process Automation Is It a Better Option Than RPA?
Cognitive RPA Intelligent Process Automation for Telecom Industry
Cognitive RPA leverages AI-powered technologies like Optical Character Recognition (OCR), Text Analytics, and Machine Learning (ML) to improve the experience of your workforce and customers. Cognitive automation, unlike other types of artificial intelligence, is designed to imitate the way humans think. The global RPA market is expected to cross USD 3 billion in 2025 according to a study.
Generally speaking, RPA can be applied to 60% of a business’s activities. In banking and finance, RPA can be used for a wide range of processes such as Branch activities, underwriting and loan processing, and more. With it, Banks can compete more effectively by increasing productivity, accelerating back-office processing and reducing costs. If your job involves looking into digitization opportunities and automation of business processes, it’s not far reaching for you to come across awareness for robotic process automation (RPA) and cognitive automation. RPA is not new; it has been around for many years in the form of screen scraping technology and macro. Today, developers are working to incorporate cognitive technologies, such as speech recognition and machine learning, into robotic process automation – and are giving bots a brand new talent.
Cognitive Automation Applications
While making changes and replicating the process, some RPA tools need to stop. While debugging, the rest of the RPA tools allow for dynamic interaction. It allows developers to test various scenarios by changing the variable’s values.
Insurance firms such as AIA and AXA have used RPA to automate their tasks of fraud checking and policy renewal, along with calculating premiums and gathering data. This has helped insurance firms to focus on customer services tasks, which cannot be automated. The emergence of cognitive technology has created various opportunities for telecom and IT services providers to streamline day-to-day work environments. Some of the outsourcing companies have already implemented RPA to automate their business processes.
Cognitive Automation resembles human behavior which is complicated in comparison of functions performed by RPA. Having limited functionality, RPA could not offer a 100% automation solution. As a matter of fact, there are only about 20% companies who were able to adopt and materialize RPA properly. The rest of RPA adopters either faced managerial hurdles or could not get the technology right.
As the complexity of processes is growing, the human workforce is developing the need for a sharper assistant who can also bring intelligence on the table. The conventional RPA tool is more or less a brainless fool that can carry out actions with remarkable accuracy and speed. It is a fine mimic that can duplicate manual actions with 100% precision. With advancements in AI and ML, RPA tools are getting smarter and paving way for hybrid, cognitive RPA platforms. Another viewpoint lies in thinking about how both approaches complement process improvement initiatives, said James Matcher, partner in the technology consulting practice at EY, a multinational professional services network. Process automation remains the foundational premise of both RPA and cognitive automation, by which tasks and processes executed by humans are now executed by digital workers.
Robotic and Cognitive Automation
Companies can leverage unstructured data using RPA and complementary technologies, streamlining their processes, or extracting valuable information. Manually identifying and performing such processes is impossible to do in a reasonable time. According to IDC, in 2017, the largest area of AI spending was cognitive applications. This includes applications that automate processes that automatically learn, discover, and make recommendations or predictions.
CIOs are now relying on cognitive automation and RPA to improve business processes more than ever before. Conversely, cognitive automation learns the intent of a situation using available senses to execute a task, similar to the way humans learn. It then uses these senses to make predictions and intelligent choices, thus allowing for a more resilient, adaptable system. Newer technologies live side-by-side with or intelligent agents observing data streams — seeking opportunities for automation and surfacing those to domain experts.
What is cognitive RPA and why do you need it
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