Robotic Process Automation especially in the context of increasing productivity. Software robots serve to automate simple and structured processes.However, RPA is very process-oriented and needs a specific input in order to process the individual processes correctly. An exception in the processes prevents complete processing.Especially when handling more complex cases, manual intervention is required.If the existing data are available in an unstructured form, cognitive computing methods can be used to evaluate them in the backend.Subsequently, RPA can be used to process the analyzed data in the front-end.The combination of these two technologies can add value to complex processes such as the insurance industry.
Four possible areas of application for cognitive computing in everyday life
1. Risk management
Banks and insurance companies need extensive data in order to create detailed risk analyzes, such as:For example, liquidity risk, hacker risk or fraud.The use of cognitive computing can be used as a prediction of such events.The systems evaluate large amounts of data from different sources and detect patterns and irregularities.The following applies: The more data available, the better the evaluation options.
2. Image recognition in medicine
We are in the middle of demographic change and the quality of medical care is becoming more and more relevant.In particular, technological development offers numerous advantages and supports doctors in their activities. For example, in the field of radiology, cognitive computing can be used to detect anomalies. So far, radiologists had to control thousands of findings and analyze possible deviations. The error rate of these evaluations is around 15 to 30 percent.
3. Autonomous driving
Electric mobility is causing a change in the industry. With autonomous driving, the next mega trend is ready for series production. Distance control systems, navigation systems and lane departure warning systems already ensure a certain degree of autonomy today. In the future, however, self-learning systems will ensure completely autonomous driving.
4. Cognitive Computing in Customer Relationship Management
A close customer relationship is known to ensure sustainable business relationships. Often, customer service stores large amounts of data and evaluates them at great expense.
Intelligent systems are already being used to collect and evaluate relevant customer data. Cognitive computing can help analyze this data and then tailor it to customer needs.
Outlook
RPA and Cognitive Computing offers an innovative way to handle complex processes. The combination of human and artificial intelligence offers enormous future potential and will be used increasingly in companies.
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