Every large financial services company is pursuing AI initiatives in 2022. Some are in the earliest stages. Others have been investing in the technology for years. Regardless, all recognize that natural-language processing (NLP) is a foundational capability for their long-term AI business goals. Unfortunately NLP is still an emerging technology, and the best options for deploying it are not immediately obvious.
In this blog post, I’ll put aside the technobabble and address the key considerations for applying NLP in financial services companies.
NLP primers
Confused about NLP? You’re not alone, and it isn’t your fault. Do a Google search on the topic and you will become even more confused.
Wikipedia defines NLP as “a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data.” The article then describes a bewildering array of common NLP tasks that have little relevance to how your company actually works.
Skip the Googling and dig into a few resources we’ve created for business leaders like you:
- Become an AI Company in 90 Days — Our book introduces you to topics like machine learning, training data, and NLP. Take 30 minutes to skim through the relevant sections and you’ll save yourself weeks of research.
- Adventures in AI — The world’s first AI comic book tells the story of how a data scientist uses NLP to save the day at a life insurance company. The story reinforces the value proposition of NLP and the steps to get organizational momentum behind a proof of concept.
- Blog post: The coming NLP Revolution in Insurance — The insurance industry — and life insurance in particular — currently lags behind the rest of financial services in its adoption of information technology. This blog post explains why NLP breakthroughs will fundamentally change the industry in the next few years.