In the ever-evolving technology landscape of the insurance industry, minimizing costs is not just a “nice to have,” it’s a necessity. With vast amounts of data, policy documents, claims reports and customer communications to handle, insurance companies are increasingly turning to cutting-edge technologies like Natural Language Processing (NLP) and Generative AI, such as ChatGPT, to streamline their operations. One capability that is making waves in the industry is generative summarization.
Generative summarization, a common capability of Large Language Models (LLMs), can transform insurance processes by providing efficient, automated ways to extract insights from the lengthy files and case histories that insurers deal with on a daily basis. In this blog post, we’ll explore what generative summarization is, why it’s a game-changer for insurance, and why every insurance company should consider integrating this technology into their workflow.
What is Generative Summarization?
Generative summarization is a technology that uses deep learning models and LLMs to produce coherent and contextually relevant summaries of lengthy texts. These automatically provided summaries give knowledge workers a quick overview of what is happening with an insurance customer or claim. Unlike extractive summarization, which takes sentences or phrases verbatim from the original text, generative summarization creates entirely new content that captures the core message/intent of the source text. This technology has the potential to revolutionize how insurance companies process and manage their vast troves of textual data.
Generative Summarization Use Cases
Here are several ways that generative summarization can be used to enhance efficiency, accuracy and decision making within key insurance processes.
Claims Processing
One of the most significant areas where generative summarization has a profound impact is in claims processing. Insurance claims often involve extensive documentation, including police reports, medical records and witness statements. With generative summarization, insurers can automate the extraction of critical information, identify inconsistencies and generate concise, standardized summaries of claim documents. This not only accelerates the claims process but also reduces the risk of errors.
Policy Underwriting
When underwriting policies, insurers must review lengthy contracts and legal documents. Generative summarization assists in breaking down complex policy documents, allowing underwriters to quickly grasp the terms, conditions and exclusions. This improves the efficiency and accuracy of policy underwriting, reducing the likelihood of coverage disputes down the road.
Customer Communications
Generative summarization is also invaluable in managing customer communications. It can analyze customer inquiries, emails and chat transcripts, automatically generating short and actionable summaries. This ensures that customer service representatives have access to critical information while responding to customer queries, enhancing the overall customer experience.
Risk Assessment
For insurance companies, understanding risk is paramount. Generative summarization can parse vast data sources, including news articles, financial reports and expert opinions, to provide concise summaries that help insurers make more informed decisions regarding risk assessment and portfolio management.
An Insurance-Trained Language Model
Generative summarization is a key capability in the expert.ai insurance-trained language model, the Enterprise Language Model for Insurance (ELMI).
It’s pretty impressive to see a complex task like summarizing a 10-page medical report and legal demand request done by a computer in less than 20 seconds! Typically, a manual summary drafted by a human could take up to 10 minutes when you include the time to review the documents and draft the summary. That’s a 95% reduction in the time needed to create an AI-generated summary like the one below.
Mickey Mouse, a 53-year-old male patient, visited Tidal Health on March 27, 2023 with a pain in his neck. He was prescribed physical therapy sessions twice a week for three weeks and was advised to avoid heavy lifting or pressure on his neck or shoulder regions until his next follow-up visit in two weeks.
Adding generative summarization capabilities to insurance processes helps your knowledge workers make smarter decisions and spend less time reviewing materials. With generative summaries insurers can:
- Enhance efficiency and automate the summarization of documents. Insurance companies can significantly reduce the time and resources required to process claims, underwrite policies and manage customer inquiries.
- Improve the accuracy and consistency of decisions using AI that is designed to minimize errors. This ensures that key information is not missed and that decisions are based on a comprehensive understanding of the data.
- Save money by reducing processing and review times for high-value staff.
- Deliver better customer service with timely and accurate responses to customer inquiries, improve customer satisfaction and loyalty.
- Reduce risks with expanded data coverage and analysis to help insurers better assess and mitigate risks, leading to more profitable and sustainable operations.
AI and capabilities like generative summarization are here to stay in the insurance industry. It enhances efficiency, accuracy and cost effectiveness while also improving the quality of customer service and risk assessment.
Insurance companies that embrace this technology are poised to reduce their costs and deliver better outcomes for both their businesses and their policyholders.
