ChatGPT: A conversation about underwriting life insurance

Have you heard the hype around ChatGPT?

Created by OpenAI, ChatGPT is an AI-powered chatbot that answers questions and engages in open-source AI conversations. ChatGPT can understand and generate text just like humans and works as an assistant that users can ask to complete tasks or answer questions. It is based on machine learning technology that allows it to understand and respond to natural language input. ChatGPT can be used for a variety of tasks such as answering frequently asked questions, text generation, and even creating conversations. Some use cases include customer service, content creation, and language translation, where it can save time and resources by quickly processing large amounts of text data.

The RGA decided to test ChatGPT by asking three questions related to underwriting and the future of life insurance. The ChatGPT responses below are completely AI generated. These answers are followed by a short FAQ that takes a closer look at this new topic.

Three questions for ChatGPT

Note. The answers below have been completely generated by ChatGPT.

What is the future of digital distribution in life insurance?

Digital distribution in life insurance refers to the use of digital channels and technologies such as websites, mobile apps and social media to sell life insurance policies to customers. The future of digital distribution in life insurance is likely to continue to grow and expand as more and more consumers get used to buying insurance online.

There are a number of factors driving the growth of digital distribution in the life insurance industry. One of the key factors is the growing use of technology and the Internet by consumers. More and more people are using the Internet to find and buy products and services, including life insurance, and this trend is likely to continue in the future.

Another factor driving the growth of digital distribution in life insurance is the increased use of data and analytics. Insurers use data and analytics to better understand the needs and preferences of their customers, and to develop more personalized and targeted products and services. This will likely lead to the development of more innovative and customized life insurance products that can be sold through digital channels.

Overall, it is likely that the future of digital distribution in life insurance will be one of continuous growth and innovation as insurers strive to meet the changing needs and preferences of their customers.

How will COVID-19 affect long-term mortality in the US?

It is difficult to predict the long-term impact of COVID-19 on mortality in the United States. The pandemic has already had a significant impact on mortality, with more than 1.1 million COVID-related deaths reported in the country. However, it is possible that the death rate from COVID-19 could decline over time as more people become immune to the virus and as effective vaccines are developed and distributed.

There are other factors that may affect the long-term mortality rate from COVID-19. For example, the effectiveness of public health measures, such as wearing masks and social distancing, in controlling the spread of the virus could have a significant impact on the number of deaths. In addition, the availability of effective treatments for COVID-19 may also play a role in reducing the death rate from the virus.

It is important to continue to monitor the situation and take measures to control the spread of the virus in order to minimize the impact on mortality.

Both of Jerry’s adoptive parents died around the age of 40 from hemophilia. How could this affect Jerry’s long-term health prospects?

Hemophilia is an inherited disorder that affects the body’s ability to control blood clotting. People with hemophilia often bleed easily and have prolonged bleeding after injury or surgery. The severity of hemophilia can vary greatly, with some people having only mild symptoms, while others have severe and life-threatening episodes of bleeding.

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If Jerry’s adoptive parents had hemophilia, it is likely that Jerry inherited the condition from them. This means that Jerry may also be at risk for bleeding episodes and other complications of hemophilia. It is important for Jerry to be aware of his hemophilia and take steps to treat the condition to reduce the risk of complications. This may include taking medication to stop bleeding, avoiding activities that could lead to injury, and seeking medical attention for bleeding episodes as needed.

It is also possible that Jerry may be a carrier for hemophilia, meaning that he has inherited the genetic mutation that causes the condition, but does not have the disease himself. In this case, Jerry may not experience any symptoms of hemophilia and will not need to take any special precautions to treat the condition. However, it is still important for Jerry to know his family’s medical history and potential risk for hemophilia, as this could affect any children he has in the future.

FAQ

Note. All of the answers below were generated the old fashioned way – by humans.

What does this ChatGPT demo show us?

In our demo above, we chose three questions to illustrate both the strengths and weaknesses of the tool. The first two questions ask him to write about life insurance underwriting topics, and ChatGPT does an excellent job. The third question is more problematic and shows a marked weakness: ChatGPT fails to recognize that a child cannot inherit a genetic disease from a foster parent. If its original corpus does not contain enough examples of the inability of adoptive parents to pass on genetic traits to their adopted children, ChatGPT will not be able to make that connection.

What are the main limitations of ChatGPT?

ChatGPT and other language models have several limitations. These models:

  • Trained on large amounts of text from the Internet, which may contain bias and may cause the model to reproduce biased language and stereotypes.
  • Lack of common sense, which can lead to nonsensical or unrealistic answers.
  • May have difficulty with tasks that require knowledge of specific subjects or industries
  • Not designed for tasks that require reasoning and logical thinking, such as deduction and induction
  • Lack of empathy and inability to understand the situation and respond emotionally to it

ChatGPT only gets access to the written text while it is being trained. He cannot use tabular data, charts, or data sources created since his last training.
What is the potential value of ChatGPT for the insurance sector?

ChatGPT and other language models can be used to perform several insurance-related tasks, including:

  • Providing automated customer service through chatbots, answering frequently asked questions and providing information about policies and claims.
  • Help underwriters analyze large amounts of unstructured data such as customer reviews, social media posts, and news articles to identify potential risks and inform underwriting decisions.
  • Processing large amounts of textual data such as claims and policy statements to identify patterns and anomalies that may indicate fraudulent activity.
  • Content generation such as policy summaries, coverage explanations, and customer communications
  • Enable multilingual customer service by translating customer requests and responses into their preferred language.

A significant amount of media hype surrounds ChatGPT and other language models due to their potential to revolutionize the way we interact with computers and automate a wide range of tasks. These models use advanced machine learning techniques, making them capable of understanding and generating natural language similar to human conversation. Although not without limitations (as shown above), ChatGPT can be fine-tuned for specific tasks or industries, making it a versatile tool for many applications.
This blog entry has been reprinted with permission from RGA.

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