Natural language processing Extract quotes from emails

Added value for banks through intelligent automation

Banks and savings banks are sitting on a huge treasure trove of data that can only be processed automatically using digital processes. With a view to regulatory requirements, productivity can be increased and costs reduced.

Big data is one of the most comprehensive technology trends and, due to the variety of its possible applications, is extremely relevant for banks and savings banks. In the bank blog you will find current studies on this interesting topic.

Financial service providers are faced with major challenges. In addition to new competitors and increasing customer requirements for service and products, increasing regulation is forcing banks to expand their compliance teams and adapt IT systems so that the information requested by the regulatory authorities can be generated in a coherent form.

However, this means that banks have to provide new functions over existing systems that were not originally developed for digital business. In addition, 80 percent of the data at commercial and private customer banks is unstructured. The processing of this data is very personnel-intensive and therefore cost-intensive.

Opportunities through digital automation

Banks can withstand these pressures and seize new opportunities by leveraging automation and breakthrough digital technologies. In a whitepaper, Swiss Post Solutions shows how a large part of the processing can be automated through digitization, which frees up human resources and increases productivity.

According to the analysis, 75 percent of manual processes in the banking sector have automation potential. Automation can help reduce costs, optimize processes, offer better quality of service and free up human resources.

Technologies that are used to collect and process customer data via various channels

  • Robot-assisted process automation (RPA),
  • Artificial intelligence
  • Natural language processing (NLP),
  • One-touch processing and
  • Intelligent character recognition.

How customer data can be collected and processed via different channels.

Together, these solutions automate manual tasks, increase efficiency, simplify adherence to compliance requirements and offer a better customer experience.

Robot-assisted process automation (RPA)

Robot-assisted process automation (Roboitc Process Automation, RPA) is the use of software for processes that were previously carried out by humans. The software is considered a robot because it replaces human labor. Combined with artificial intelligence, RPA can be of great benefit in combating fraud and money laundering when handling unstructured data.

Artificial Intelligence (AI)

Artificial intelligence (AI) describes, among other things, the ability of software to think and learn for itself. Based on historical data and patterns, it continuously improves as it carries out its tasks.

Natural Language Processing (NLP)

Natural language processing understands the nuances of human language. It is a powerful tool for extracting the meaning of communications such as e-mails.

Optical character recognition (OCR)

Optical character recognition processes unstructured data from chatbots, text messages, e-mails, e-mail attachments and paper documents and converts this data into a structured form.

Intelligent Character Recognition (ICR)

Intelligent character recognition serves similar purposes as OCR, but processes written text.

More freedom and efficiency

The use of these technologies gives banks more freedom and enables them to use their human resources for less monotonous and more complex tasks - which increases employee retention and efficiency.

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