Currently, Natural Language Processing has been having a strong impact on various sectors. Looking at the insurance industry and its security, we’ll break down the most relevant use cases.
Let's get started!
NLP in Insurance
Insurance Claims Management
NLP can be used in combination with OCR (character recognition) to analyze insurance claims. For example, IBM Watson has been used to analyze structured and unstructured text data to discover the right information to process insurance claims and send it to a machine learning algorithm. This is responsible for labeling the data according to the sections of the claim request form.
NLP can be combined with machine learning and predictive analytics to detect fraud and misinterpreted information from unstructured financial documents.
For example, a 2010 study revealed that NLP language models could detect misleading emails, which were identified by "reduced frequency of first-person pronouns and signature words, and elevated frequency of negative emotion words and action verbs."
NPL in cybersecurity
1. Spam detection
NLP models can be used for text classification to detect spam-related words, sentences, and sentiments in emails, text messages, and social media messaging applications.
Likewise, spam detection NLP models usually follow these steps:
- Data cleaning and preprocessing: elimination of padding and empty words.
- Tokenization: sampling of text into smaller sentences and paragraphs.
- Part-of-speech (PoS): taggingTag a word in a sentence or paragraph to its corresponding part of a speech tag, based on its context and definition.
2.Prevention data exfiltration
Exfiltration data is a violation of security involving copying or unauthorized transfer of data from one device to another. To exfiltrate data, attackers use cybersecurity techniques such as Domain Name System (DNS) tunnels.
What does this mean? DNS queries that reflect a request for information sent from a user's computer (DNS client) to a DNS server. Also sending phishing emails that leads users to provide information to hackers.
Here at LISA insurtech we have acquired knowledge in NLP in order to offer the insurance industry the ability to operate effectively and offer an ideal service to its clients.
How do we do it?
- Through chatbots by allowing the complaint to be processed in a simple and fast way.
- We automatically translate all documents.
- We look for certain patterns within the texts that allow us to identify the critical data in the documents.
- We detect the "feeling" found in the description of an event and the state of mind of the person who makes said description.
- We search based on keywords. And it is used in the health field to determine amounts to be compensated depending on the illness/injury.