Three Applications of Cognitive Automation in RPA

With the help of cognitive automation and its processes, such as Natural Language Processing (NLP), texts can be analyzed, thereby producing meaningful insights about the disease.

Apac CIOOutlook | Monday, April 05, 2021

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With the help of cognitive automation and its processes, such as Natural Language Processing (NLP), texts can be analyzed, thereby producing meaningful insights about the disease.

Fremont, CA: Robotic Process Automation (RPA) has become an essential part of various industries’ operations. It automates repetitive and time-consuming tasks. One crucial step in the process of RPA is cognitive automation.

Cognitive automation conducts tasks that need critical thinking and human intelligence, unlike RPA, which requires a pre-requisite set of rules.

Here are three applications of cognitive automation in RPA:

Banking

In banking, implementing AI tools to analyze public records, scanning documents, and processing local and international transactions reduces paperwork and helps get vital insights from a customer’s information. It also helps make informed and intelligent decisions about customers who need loans. Insights with the help of cognitive automation can help prevent potential frauds and scams.

Healthcare

A vast amount of data is produced in healthcare regarding patients’ information that needs investment for healthcare purchases directly or linked with its functioning. This data is unsegregated as it is gathered from various sources. With cognitive automation and its processes, such as Natural Language Processing (NLP), texts can be analyzed, thereby producing meaningful insights about the disease. It also helps in making better decisions while filtering through the unstructured data.

Retail

The retail industry includes compiling data from multiple stores and departments, which can be challenging because of the pre-existing silos in the departments. Cognitive automation can streamline data based on the needs of operations. Additionally, with AI tools of cognitive automation, important insights can be gathered from the data complied about the product providers, partners, and retailers, making sure that operations’ efficiency and precision are not obstructed.