Artificial Intelligence and Insurance Underwriting
People are making a big deal about it — because it’s a big deal.
Artificial Intelligence (AI) and natural language processing are rapidly changing the insurance industry.
Improved access to data, growing computing power and changing consumer expectations are all contributing to increased carrier adoption of AI.
Major life insurance and annuity issuers are using AI to make faster and better-informed decisions, to improve the way they manage risk and work with customers.
Accern offers a system customers can use to apply AI methods without coding. Here are some of the ways that insurance industry players are using AI, based on what we’re seeing on our platform.
1. Managing Multiple Types of Data.
Insurers use vast amounts of data to run their operations.
Some of the information comes in through well-structured databases or Excel spreadsheets, but much of it arrives in the form of PDFs, audio recordings, images, emails and other types of files.
Instead of using human workers to comb through the files, through manual processes that can take hours or even days and often leave room for human error, insurance organizations are using AI to extract the key data.
2. Automating Analysis
Building automation into the underwriting process can save human underwriters time and improve their productivity.
Once files are processed and key bits of data extracted, insurers can use AI to evaluate how much coverage an applicant should receive and what the price should be. Using AI in these processes can help insurers follow specified underwriting guidelines and policies while increasing personalization and customer satisfaction.
Analyzing bank statements, tax returns, medical history, credit scores, demographic profiles, employment information, and more can all be done instantly.
Insurers are also using AI to identify fraudulent information that customers have tried using to qualify for lower premiums or bigger benefits payments.
3. Increasing Personalization
After extracting key data points from unstructured data, and analyzing the results, insurers can better understand a customer’s current and future insurance needs.
Agents can, for instance, use AI to speed up the process of providing personalized life insurance recommendations, based on a consumer’s medical records, family medical history, bank statements, income and tax returns.
Additionally, we are seeing clients create simple neural-network-based models using historical data. The models can help our clients find patterns and predict their policyholders’ future behavior. Clients can, for example, use information about a customer’s emails, calls and online activity to predict whether the customer 0will stay or leave.
These are just a few of the ways we are seeing AI continue to change the way insurance is offered — and help the industry operate more efficiently, offer better service and more effectively manage risk.