Natural language processing (NLP) is a subset of artificial intelligence that is focused on programming computers so they can (a) understand the human language from a variety of inputs such as e-mails, instant messages, written communications, and verbal which can then be processed by other systems as well as (b) producing natural language outputs again across various sources such as e-mails, written communication and verbal.

The benefits of NLP are widespread, namely:

  • It allows firms to process a large amount of activity (such as customer queries or instructions) very quickly or even instantly without the need for having teams of people assess the request and process it manually. This in turn improves customer servicing.
  • NLP allows firms to be more scalable and cost-effective. Once they have their NLP infrastructure in place then it should be able to cope with a large amount of activity. If volumes increase then the infrastructure can be extended which is much cheaper and quicker than employing more and more staff.
  • This in turn provides benefits around Improved Customer Servicing, Internal Efficiencies, Fraud Management and Better Data Collection.

However, NLP does have some changes, namely:

  • Ensure There Is a Clear Business Reason to Implement NLP.
  • To mitigate risk NLP implementations should be rolled out on a phased basis.
  • A robust infrastructure is required to support NLP
  • Understanding inbound communication is challenging due to different dialects, terminology, languages, phrases and ways of speaking
  • It is important to keep language dictionaries, lexicons, etc. up to date.
  • NLP Still Needs Some Social Acceptance by Customers and the General Public

This area of NLP (and its benefits and challenges) are covered in my book. “Emerging FinTech: Understanding and Maximizing Their Benefits”

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