Generative AI insurance use cases - WRITER
Generative AI Insurance Use Cases
Intro
Insurance has historically been stuck in a digital transformation rut — it’s often one of the last industries to embrace emerging technologies. But enterprise-grade generative AI solutions have the potential to change the insurance industry’s reputation for lagging behind. With generative AI technology like large language models (LLMs), insurance companies are re-imagining how they underwrite, sell, and service complex products.
Generative AI can efficiently collect and distill large amounts of data, allowing for improved decision-making on traditionally complicated products like life and disability insurance and annuities.
LLMs help consumers, agents, and customer service representatives by answering complex questions, assisting, and managing conversations. They also reduce underwriting time and cost, reduce risk, and improve customer satisfaction. In short, generative AI is set to bring powerful benefits to the insurance industry.
“Generative AI presents insurers with an exceptional opportunity to reinvent themselves and deliver enhanced value to customers, shareholders and society in a holistic manner. It’s no overstatement to say that its long-term impact will be transformative, and the immediate-term effects can be profound.”
Ernst & Young1
The first step in realizing such transformational benefits is identifying high-value use cases that’ll have the quickest, largest impact on your company. Welcome to the Big Book of Generative AI Insurance Use Cases.
This is your go-to place for learning how to use AI for insurance and the advantages you can gain from doing so. It’s a guide to help get the ball rolling on your AI-related initiatives and to figure out the right requirements for a successful AI platform. We also provide tips to help you dodge any bumps along the road.
How to get the most out of this guide
We organized this guide in modules by team function. You’ll find sections for marketing, underwriting, claims management, and support.
We then divide the functions by different use cases — exploring how you can use generative AI to create, analyze, and govern data and content. So you can, for example, see exactly how an underwriter could use a platform like WRITER to summarize policies.
A quick word on generative AI, WRITER, and ChatGPT
Generative AI is a broad term that encompasses a variety of different technologies and techniques, such as deep learning and natural language processing (NLP). These tools can be used to generate new images, sounds, text, or even entire websites.
In this guide, you’ll learn about content creation, analysis, and compliance use cases, like those supported by our full-stack generative AI platform, WRITER. You’ll see the different types of AI capabilities that are possible, as well as how to best implement those use cases using WRITER.
Note that WRITER isn’t just a ChatGPT alternative. While ChatGPT is built on an OpenAI large language model (LLM) and trained with public data, WRITER is built on our own family of LLMs (Palmyra) and trained with datasets curated for industry-specific use.
Three big ideas for AI in insurance
At the heart of our enterprise AI platform is a desire to create a product that your people will love, guided by three core principles: a focus on people, support for your brand, and business-readiness for the insurance industry.
A focus on people
Our goal is to provide your people with an intuitive, straightforward, and simple-to-use experience, right where they work. We strive to support their work and boost their productivity with a variety of powerful use cases encompassing all areas of the insurance sector, ranging from policy management to risk analysis to compliance.Support for your brand
We understand the needs of insurance companies when it comes to building a brand. WRITER automatically enforces your AI guardrails so work is compliant, accurate, inclusive, and on-brand.Business readiness
We built the WRITER platform specifically for enterprises, recognizing the importance of protecting the data you share with us — we don’t use your data to train our models, and we adhere to global privacy laws and industry-recognized security standards.
Here are highlights of the use cases we’ll explore
Marketing
Underwriting
Claims Management
Support
Marketing Use Case Examples
| Type | Example |
|---|---|
| Create | Write copy for an integrated ad campaign for our homeowner’s insurance product, tailored to this customer profile. |
| Analyze | Analyze customer data to identify potential new markets for life insurance products based on customer age, gender, location, income, etc. |
| Govern | Identify any potential legal, regulatory, and brand compliance issues in marketing materials before they’re published. |
Underwriting Use Case Examples
| Type | Example |
|---|---|
| Create | Write a report outlining the risk factors associated with a long-term disability insurance policy for a 40-year-old male with a family history of chronic illness. |
| Analyze | Compare the average claims cost for renters insurance policies across different zip codes and age groups. |
| Govern | Review existing life insurance policies and alert the underwriters to any potential compliance issues. |
Claims Management Use Case Examples
| Type | Example |
|---|---|
| Create | Generate detailed descriptions of property damage using images and text descriptions from a claims adjuster. |
| Analyze | Summarize the key details from a member’s claim dispute call recording. |
| Govern | Scan claims documents for any discrepancies in coverage or claims history. |
Support Use Case Examples
| Type | Example |
|---|---|
| Create | Create an interactive knowledge base to help agents quickly access relevant information. Generate content to explain the implications of the latest regulatory changes. |
| Analyze | Generate a summary of the key takeaways from the customer call. Identify the most common customer inquiries related to auto insurance coverage. |
| Govern | Detect potential regulatory non-compliance in customer support conversations. |
Functional Requirements
With the right tools in place, all of these business-transforming use cases are possible. Here are the capabilities your generative AI software should have:
- Knows your products
- Adheres to your legal and regulatory rules
- Speaks in your voice
- Writes in your style
- Integrates easily into existing workflows
- Understands relevant data formats
- Detects claims and checks facts
- Protects everyone’s data (yours and your customers’)
- Meets the compliance needs of secure organizations.
Case Study
How a top life insurance company uses WRITER to accelerate compliant content
The content design team and help center at one of the largest life insurance companies in the US faced a challenge that many companies experience: needing to produce content that adheres to brand messaging and compliance requirements, but in a timely and efficient manner.