ChatGPT and the Future of Customer Service in Insurance
After accumulating over 100 million active users in a little over 2 months since its release (in November 2022), ChatGPT has been taking the tech world by storm. In fact, Microsoft has leveraged this bleeding-edge technology and incorporated it within its own Bing search engine in an attempt to disrupt the search engine market. Along with these disruptions, is it possible that ChatGPT or similar tech can disrupt the customer service aspect in the insurance sector? Let’s find out!
- Potential uses and benefits of ChatGPT in Insurance
- Limitations of ChatGPT
- Chatbot use cases in insurance
- The road ahead
Potential uses and benefits of ChatGPT in Insurance
- API integration: Insurance companies can make use of the ChatGPT API and integrate it within their own website. ChatGPT can then act as a sales representative on their insurance website and interact with the prospective customer; much like a live chat executive might. The tool can then begin to understand the customer’s requirements and spit out the most relevant insurance quotes.
- Customer support: The ChatGPT API can also be used to troubleshoot customer grievances and inform the customer about possible solutions to their complaints or queries.
- Lower costs: The ChatGPT tool is much more likely to cost lower compared to hiring an actual human being. This can increase the profitability of the insurance company.
- Limitation of human error: Human beings are prone to the error. The AI tool, if properly trained will likely dish out accurate and relevant information.
- Breaking the language barrier: AI tools like ChatGPT are language agnostic. They can chat with a user in English, Hindi, Marathi, or any other regional language.
- Availability and consistency: ChatGPT does not need a break. It can work around the clock. No lunch or dinner breaks. In fact, it can be online 24×7.
- Summary of policy bonds: This could be a game changer within the insurance industry. Insurance bonds are usually very long and nuanced. You can ask ChatGPT to make a summary of your insurance bond and highlight the most important and noteworthy points. The tool will do so and you can make a better more informed buying decision due to this.
Limitations of ChatGPT
- Missing a human touch: At times, the ChatGPT chatbot can seem like its missing a human touch. Its answers may come out more robotic in nature. This tendency is likely to be eliminated completely as the technology gets more robust.
- Compromised training data: That chatbot and its results are based on the integrity of the training data. At times, this training data set may be polluted due to human biases, and this can create incoherent or irrelevant responses.
- Lack of empathy: The tool is a computer program; it is not a human. This makes it completely lack any empathy. This lack of empathy may cause the tool to not understand the gravity of a particular request made by a customer.
Chatbot and AI companies in Insurance
Let us look at some of the most notable chatbot use cases in the insurance industry and attempt to get an idea of how things in the future may pan out.
Haptik AI: The Indian AI company Haptik is currently building a suite of products that insurance companies can use in their interactions with customers. Haptik has products that insurance companies can use in their customer interactions on the following platforms:
- WhatsApp Messaging
- Insurance website
- Facebook Messenger
Flo AI: Progressive Insurance has a chatbot called Flo (made by Microsoft) that assists their customers to do the following:
- File claims
- Change payment dates
- Get insurance quotes
Allstate Business Insurance Chatbot (ABIE): ABIE is a chatbot on Allstate Insurance’s website that helps prospective customers in answering initial questions about the product. ABIE can also point customers to the most relevant insurance policies.
GEICO’s Kate chatbot: Similar to ABIE, GEICO’s Kate chatbot helps customers get the relevant information and sends the best and most relevant motor insurance quotes based on their requirements.
The road ahead
The world of machine learning and AI has come a long way. From the 1950s, when Artificial Intelligence pioneer Arthur Samuel introduced the first self-learning software for playing checkers to OpenAI’s ChatGPT in 2022. Machine learning and AI have come a long way. That being said, this is still just the tip of the ice berg.
These technologies have the potential to geometrically increase efficiency and profitability of companies and will most likely be heavily invested in, causing a surge of AI and ML products and applications across the insurance sector and beyond.