What is The Future of Natural Language Processing?


Whether you are from a technical background or a non-technical one, you might have come across the term Natural Language Processing (NLP). It is popular because various industries have adopted NLP for competitive growth and to gain business insights. But, what is it exactly?

Natural Language Processing is a branch of computer science, computational linguistics, artificial intelligence, text summarization,etc. In simpler terms, it is a branch of technologies that provide interactions between humans and computers. NLP’s primary goal is to communicate with humans in the natural style.

NLP allows machines to generate and interpret human language, which is easily understandable to humans. It includes tasks such as speech recognition, understanding natural language, document analysis, machine translation, and information documentation.

In this blog, we will discuss what is the future of Natural Language Processing and what should be expected from NLP. Also, we will cover NLP that is involved in financial technology (FinTech) sector. So, let’s dive into the world of advanced and modern technology.

Current Overview of NLP

In recent years, Natural Language Processing has become the talk of the town. Several applications, such as chatbots and virtual assistants, use NLP for better interactions. The primary goal is to understand language translations and sentiment analysis.

However, many times the Natural Language Processing system understands the keyword and sentences but fails to understand the sentiment or context behind them. It includes words or sentences like humor, sarcasm, or wittiness. Also, sometimes it misleads the users, mistakes in sentiment analysis and other applications.

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Additionally, experts train NLP based on a massive amount of data and expect to provide accurate results and predictions. However, it depends on the quality of data and requires specialized specific-domain datasets to perform in multiple applications and industries.

As a result, NLP has witnessed advancement in numerous models and also it enhances understanding of context and meaning. Also, there have been significant improvements in the quality of large-scale databases, allowing them to perform better.

Future of NLP

As NLP continues to advance, there are several potential possibilities for the future of this computer-based technology. Here are some potential advancements and applications of NLP that we may see in the upcoming years:

Advancements in NLP Technology and Research

  • Improved understanding of the context and nuance in sentiment-based language
  • Enhanced interactions in chatbots and virtual assistants
  • Have developed a clear understanding of sentiment analysis, including the ability to identify emotions
  • Better identification regarding the quality of data using NLP models
  • Have managed to understand and generate numerous languages

Potential Future Applications of NLP in Various Industries

  • Education:

 NLP could help students learn a new language, help with writing and grammar, also provide personalized feedback on multiple assignments

  • Healthcare: 

NLP could be utilized to analyze patient data, assist with diagnoses, and conduct overall research about the healthcare sector. 

  • Marketing: 

NLP could be used to analyze customer feedback, observe social media sentiment, and generate more targeted advertising campaigns.

  • Finance:

 NLP could be used to prevent risk fraud, improve customer experience, and streamline interaction between machines and customers

Impact of NLP on Society and Communication

  • NLP offers more accessible and inclusive communication for people with disabilities, including those with speech and hearing impairments.
  • The computer-based technology could save time and resources in a variety of industries, including customer service, healthcare, and various other sectors.
  • NLP could generate more personalized and engaging experiences for customers and users like virtual assistants.
  • It could help us better understand the nuances of human language and improve communication between people from different cultures and backgrounds.

NLP as a Finance Technology

Here are some of the ways that NLP is being used in the finance industry:

  • Risk Assessment

Natural Language Processing is used to analyze massive amounts of financial data. Also, it helps to identify patterns and trends that can help in forecasting movement and asset risk. Moreover, it will detect errors, which in turn, will reduce risks.

The Artificial Intelligence language is used to analyze online articles and social media posts to recognize patterns and trends for generating efficient strategies. Additionally, it can be utilized to assist with credit risk assessment by reviewing the text data from credit reports which will decrease the workload and by analyzing the financial documents, the potential defaults can be corrected immediately.

  • Fraud Detection

The advanced technology allows you to detect fraudulent activities by analyzing customer communications, such as chat transcripts and call logs. Moreover, it will notify you if there are any suspicious behaviour or patterns. 

Also, NLP can be used to monitor social media data and other unstructured data sources to detect potential fraud cases that have different or similar patterns. 

  • Customer Service

NLP-powered chatbots and virtual assistants are being utilized to offer better customer service in finance by answering customer queries and providing account information. It also helps customers to streamline the transactional process.

NLP can also be used to analyze customer feedback and complaints to recognize areas for enhancement in customer service.

As a result, there is a high scope of Natural Language Processing in future.  If you want to make your future in NLP, enroll yourself in the new-age PG Certificate Programme In Financial Technologies (FinTech) offered by IIM Nagpur. This programme gives an excellent opportunity to learn about NLP and the uses of NLP in the business world. 

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