RPA (Robotic Process Automation) is an extremely good tool for automating rule-based tasks related to structured and semi-structured data. However, cognitive RPA, as its name suggests, complements traditional RPA with intelligence.
Because corporate processes are highly complex and technologically intertwined, the use of both structured and unstructured data becomes complex. Consequently, the RPA solution alone is not enough. The digital workforce (bots) should make complex decisions that involve learning, reasoning, and self-healing skills.
RPA grown on cognitive RPA steroids in a nutshell, writes Datascience Central. It uses artificial intelligence technologies such as computer vision, OCR (optical character recognition), document comprehension, NLP (natural language processing), text analysis, and a number of unique or out-of-the-box machine learning and in-depth learning models that allow bots to make complex decisions while automating from an endpoint
In addition, many manufacturers offer Human in Loop capabilities, where the output of artificial intelligence and deep learning models (AI / ML) is validated by humans and, once approved, the robots complete the automated process.
In addition to automating web-based applications, RPA can also automate Windows applications and legacy applications for which developing IT integration would be costly, time-consuming, and a huge task. RPA is able to mimic what an end user does with nearly zero error and without the fatigue, boredom, or wickedness that characterizes people in their work. RPA therefore offers greater accuracy, greater performance, SLA compliance, and better compliance. With this fusion of artificial intelligence and RPA (cognitive RPA), end-to-end automation can now be automated and complex cases that previously required human intervention can be handled.
The main purpose of cognitive RPA is to take over from people to all the mundane, repetitive and tedious tasks so that people can focus primarily on strategic tasks. According to Monjima Nandi, author of the article, the motto is “If you hate it, just automate it!”
There are many uses for cognitive RPA or Intelligent Process Automation (IPA). Just a few examples:
- Verification of new subscribers: The information entered by the user is compared with verified identity data to filter out any discrepancies. In addition, the image of the person on the ID card will be compared with the current image and the images of the fraudsters to verify the identity of the new subscriber.
- Invoice Processing: Extracts important information from invoices such as the billing address, shipping address, due date, invoice, items, final amount, etc. to check by reconciling system entries and extracted information.
- Digital Assistant: Identifies failed jobs and takes corrective action based on the underlying logs
- FCR (First Call Resolution): Solving customer problems from the first call to the customer service center by bots assisting employees with real-time guidance (querying customer information, re-entering updated information, launching a problem-solving workflow for known issues, etc.)
- Information Security Officer bots: Bots can easily gather evidence (logs, database records, plain database files, etc.) across different systems and analyze their deviations from established company policies, procedures, and guidelines.
Hardware, software, tests, curiosities and colorful news from the IT world by clicking here