Artificial intelligence (AI) and natural language processing are rapidly changing the insurance industry. Improved access to data, higher computing power and changing consumer expectations all contribute to greater acceptance of AI by operators and better informed decisions to improve risk management and customer collaboration. Accern offers a system that allows customers to apply AI methods without coding. Here are some of the ways that insurance industry players are using AI, based on what we’re watching on our platform.
1. Managing Multiple Types of Data.
Insurers use huge amounts of data to run their businesses. Some of the information comes from well-structured databases or Excel spreadsheets, but much of it comes in the form of PDF files, audio recordings, images, emails, and other file types. Human workers to review files through manual processes that can take hours or even days, often leaving room for human error, insurance companies use artificial intelligence to extract vital data.
2. Automating Analysis
Integrating automation into the underwriting process can save human subscribers time and improve their productivity. Once the files have been processed and the most important data extracted, insurers can use artificial intelligence to assess how much coverage an applicant should get and what the price should be. These processes can help insurers comply with specific insurance policies and guidelines while increasing personalization and customer satisfaction. Analysis of bank statements, tax returns, medical history, creditworthiness, demographic profiles, employment information and more can be done instantly to identify fraudulent information that customers tried to qualify for lower rewards or higher benefit payments.
3. Increasing Personalization
After insurers extract key data points from unstructured data and analyze the results, insurers can better understand a customer’s current and future insurance needs. For example, agents can use artificial intelligence 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.
In addition, we see customers creating simple neural network-based models using historical data. Models can help our customers recognize patterns and predict future behavior of their policyholders, use information about a customer’s emails, calls, and online activity to predict whether the customer will stay or leave. These are just a few examples of how AI continues to transform the way insurance is offered and help the industry operate more efficiently, provide better service and manage risk more effectively.
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