Natural language processing
The field of AI that lets machines read, classify, summarize and produce text, transformed by language models, and central to a business where contracts, claims and reports are written.
Natural language processing covers the methods that let a program work on human text: segment it, recognize entities, people, places, amounts, dates, classify it by topic or sentiment, extract relationships, summarize, translate or produce it. For decades these tasks relied on linguistic rules and specialized statistical models, each trained for one task. Language models based on the transformer architecture unified the field: a single model, possibly fine-tuned, performs most of these tasks with unprecedented quality. Insurance is natural ground for these techniques, because most of its information is written: policies and endorsements, applications, free-text claim descriptions, adjusters' reports, correspondence, court decisions. Uses range from automatic classification of mail to analyzing claim descriptions to spot emerging causes, through clause comparison and fraud detection in narratives. The limits lie in accuracy, linguistic biases, and the difficulty of guaranteeing that a model truly understands a legal text rather than reproducing its form.
Textbook case: by analyzing the free-text descriptions of 200,000 home claims, a language model reveals a 40 percent rise over two years in fires mentioning e-scooters or e-bikes on charge, a cause that standard claims coding lumped into the general electrical fire category.
NLP, natural language processing
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