As Artificial intelligence is rapidly advancing, Insurance companies, brokers and agents are looking to use artificial intelligence or “augmented intelligence” in the their business. What are insurance use cases for AI they ask? This is a common question that we come across, and I have highlighted some very broad, but typical areas of the two themes of AI, namely Generative AI and Trained AI.
Common generative AI use cases - content creation like images, content, summarization & knowledge bases.
Sales and Marketing: Content Creation, Advertising, Imagery, Training, Sentiment analysis
Customer Service: Chatbots, Communications and service questions, Personalization
Knowledge Base: Information on product, Training material, Process and Quality standards
Technology: Programming assistants, Data and analysis, Application and development
Trained AI: These are specific areas that use your company information and historical data to determine probability of events.
Underwriting: Adherence to policy wording, Cover approval on products
Claims: Streaming and Triaging claims, Claim Approval and thresholds for acceptance, Assessment requirements
Finance: Fraud detection, Default and delinquency
Operations: Supply chain approval, personalization and product targeting, communications and proactive alerting
So what next:
You have an idea of the areas you might like to try in your insurance business, but before diving headfirst into solutions, use cases should be centered around what the problem is that you are trying to solve. These range from detecting issues, improving productivity or reducing costs, among many. It may even be to enhance your back-office teams build internal efficiencies.
Using enterprise AI technology is key to the digital transformation, and integrating this into your digital and AI data strategy is a capital investment that you plan for. Years ago, building, deploying and maintaining AI solutions was a big scary effort with costs that would blow out. The great thing about the advancement in technology is the reduction in cost to implement solutions or proof-of-concepts (POC). AI for insurance use cases are more accessible and not exclusive to the big insurtechs and insurance companies.
I have worked with Insurers, Agents, Brokers and Intermediaries that leverage the powerful advantages and solve the common challenges of adopting AI into operations with a focus on retention, churn and defection. After all keeping clients on the books, is easier than getting new ones!
Book a chat or send me a message if you want to know more about Enterprise AI solutions!
Have a look at my youtube video on how to adopt AI and use AI for insurance: https://youtu.be/1eTZYS_UvD0