With the global Natural Language Processing (NLP) market expected to reach USD 44.96 Billion by 2028, according to a report by Reports and Data, there has never been a better time to understand how such a technology works in accurately comprehending human speech.  

The commercial and operational benefits of adopting NLP technology are increasingly apparent as businesses have more and more access and visibility across their unstructured data streams. Firms who adopt early are positioning themselves as market leaders, with the benefits gleaned from trading insights pivotal in gaining a competitive advantage.  

Here we break down how NLP works to uncover these invaluable market insights.  

What is NLP?   

Put simply, NLP is a technology used to help computers understand human language. The technology is a branch of Artificial Intelligence (AI) and focuses on making sense of unstructured data such as audio files or electronic communications. Meaning is extracted by breaking the language into words, deriving context from the relationship between words and structuring this data to convert to usable insights for a business.   

How NLP works. 

In our everyday lives we may use NLP technology unknowingly - Siri, Alexa and Hey Google are all examples in addition to chatbots which filter our requests. In this way we can interpret the technology as the bridge between computers and humans in real time, streamlining business operations and processes to increase overall productivity.  

NLP techniques rely on Deep Learning and algorithms to interpret and understand human languages and, in some cases, predict a human’s intention and purpose. Deep Learning models ingest unstructured data such as voice and text and convert this information to structured and useable data insights. The technology extracts meaning by breaking the language into words and deriving context from the relationship between these words. In this way do we use NLP to index data and segment data into a specific group or class with a high degree of accuracy. These segments can include sentiment, intent, and pricing information among others. 

NLP Algorithms Index and Segment data 

The indexing process can be further broken down into stages.  

1) Tokenization – whereby the text is broken down into semantic units or single clauses,  

2) Stop word removal – removing words that add no unique information, e.g., prepositions and articles,  

3) Stemming/lemmatization - transforming words to their root form and assess context of word use. 

4) Part of Speech Tagging - words are tagged according to grammatical case.  

NLP models identify sentiment, intent, and entities. 

Algorithms can be formed in two ways to drive the NLP training model. Following a rule-based approach, algorithms are created by linguistic engineers and follow manually crafted grammatical rules. However, a faster and more powerful approach is in Machine Learning (ML) algorithms whereby learning models are based on analytical and statistical methods and require a degree of training which concurrently learns from the examples introduced.     

From this training, associations between words are recognised, which feeds into the machine knowledge bank in order to ascertain the motive of the text, providing firms with key data insights which enhances business opportunity. Furthermore, the greater the training, the vaster the knowledge bank which generates more accurate and intuitive prediction reducing the number of false positives presented.  

With VoxSmart’s NLP solution, firms are fully in control of the training of these models, ensuring the outputs are tailored and specific to the needs of the organisations with the technology rolled out on-premise. This not only puts the firm in the driving seat but also reduces concerns regarding data ownership, with the firm having full authority over their data. 


Although few may work directly with the inner workings of NLP, the benefits across a firm are testament to its ingenuity and innovation throughout capital markets and regulated industries. VoxSmart’s scalable NLP solution is attuned to the specific needs of our clients, with training models tailored to a firm’s requirements.  

Interested in learning more on VoxSmart’s NLP solution can help your business? Get in touch with us today here! 

If you liked this, then you may also be interested in: 

    New call-to-action