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The Impact of Natural Language Processing in the Insurance Industry

Feb 28, 2022
Natural Language Processing in insurance

Natural Language Processing in the Insurance Industry

The insurance companies depend on data that provides them with the insights they require to develop the services and products and make their insurance business more agile and efficient. But, the majority of the data generated daily is in the unstructured format coming in the form of text documents, emails, legal reports, research, videos, voice recordings, social media posts, etc. This unstructured data is a goldmine for the insurers, but quite difficult to analyze.

Fortunately, most insurance companies now embrace evolving technologies like Natural Language Processing (NLP) to apply understanding and structure to complex, unstructured data. Insights from this information can be used to mine information that enables predicting risks, bringing growth opportunities to the surface. Natural language processing (NLP) meets the industry’s needs by automating insurance processes, resulting in increased operational efficiency and profit margins. According to a recent report, the global Natural Language Processing (NLP) market size to grow from USD 11.6 billion in 2020 to USD 35.1 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 20.3% during the forecast period (source).

Attractive Opportunities in the NLP Market



Artificial Intelligence includes learning predictable, repetitive tasks and replicating them on a larger scale faster than humans. NLP is a subset of AI technologies that understands unstructured data from the interaction between humans and computers and interprets it in meaningful ways.  

In the present landscape, with NLP blooming in the insurance sector, machines can understand humans in the innate way we communicate, understand the intent behind language, and eventually automate communications. This, in turn, bridges the gap between human and machine language. Insurance companies use NLP to automate communications to make sense for consumers and provide them with an excellent user experience. Key Management Group Inc. uses NLP techniques and Deep Learning, which helps structure the free flow text data. To know more, please visit

Why Choose KMG as Your NLP Partner?

  • Enhanced Customer Service: Speed and personalization are the two most significant factors of consumer experience in the insurance sector. KMG uses NLP-driven virtual assistants, which creates an automated customized experience for each insurance consumer and assists in providing answers faster, accurately, and efficiently.
  • Improved Fraud Detection Capabilities: Fraud is an expensive loss for insurance companies. With the colossal volumes of claims being processed, insurers can’t pinpoint every single instance of fraud. Therefore, NLP technologies are one of the most efficient options for fraud detection. KMG integrates NLP solutions into the insurance mobility system to understand and analyze the unstructured data, which detects recurring patterns in past fraudulent claims and raises an alert if a new fraud is suspected. 
  • Faster Claims Processing: A vital portion of insurance companies’ time goes into claims processing. Despite developments in technology, few parts of claims management are still manually done. This makes it challenging to eliminate human errors. But, thanks to the NLP-driven voice-to-text functionality, insurers can now use a virtual assistant to collect consumer information over the call and fill in the claims form. Also, NLP AI tools can cross-verify the claims form with the individual’s policy details, assess it for fraud, and reject or approve the claim without any human intervention. This complete process takes place in a much faster time.
  • Greater Accuracy in Underwriting: Underwriters are responsible for analyzing policies and documents to draw key conclusions. Since there are many elements to consider, it can be challenging for underwriters to make an accurate estimation. KMG uses NLP solutions that enable underwriters to quickly extract relevant data to assess the level of risk, which saves time.


Insurance is a continually evolving sector. Integrating insurance test automation systems with AI-driven technological innovations such as identity resolution, cloud computing, predictive analytics, natural language processing, etc., provides insurance companies with powerful tools to meet the ever-changing consumer needs and behaviors.

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