Look Back to Look Ahead

As artificial intelligence (AI) continues to establish a foothold in insurance, it’s important to remember two things: (1) AI can be invaluable in automating routine tasks to reduce the need for manual intervention. (2) The predictive value of AI lies in hindsight; that is, its ability to analyze data, to identify patterns, and to predict outcomes is retrospective.

Predictive AI combines machine learning, AI, and statistical models to identify relationships between variables and to make predictions. To cite a few examples, AI can:

  • Assess and manage risk more effectively by analyzing data from various sources, including social media, credit reports, and medical records.
  • Predict the likelihood of claims, enabling insurers to offer more accurate risk assessments and personalized premiums.
  • Automate claims processing, reducing the time and effort required to settle claims and improving accuracy.
  • Predict customer churn: By analyzing customer behavior and demographics, AI can identify patterns that indicate whether a customer is likely to switch to a competitor, allowing insurers to target them retention efforts.
  • Forecast sales: AI can analyze historical sales data, seasonality, and market trends to allow insurers to prioritize the sales or products or lines accordingly.
  • Detect anomalies: AI can identify unusual patterns in data, such as unusual policyholder behavior or rating abnormalities, to allow for swift detection and resolution.
  • Optimize processes: AI can analyze process data to identify bottlenecks and inefficiencies, enabling insurers to optimize workflows, reduce costs, and increase productivity.

Generative AI, on the other hand, creates new content, such as images, text, and other media, by learning from, aggregating, and adapting existing data patterns. While generative AI is valuable in creative fields and novel problem-solving, its predictive value is limited to generating new content rather than making predictions about future outcomes.

What’s In It For Insurance?

AI is flexing its muscles in the insurance industry, by improving capabilities like customer service, claims processing, underwriting, and fraud detection. Its ability to analyze large datasets and to process information in specifically programmed ways enables insurance companies to enhance customer service by providing personalized policies and improving communication. AI-powered chatbots and virtual assistants can provide 24/7 customer support, answer common questions, and help customers with policy-related inquiries. AI can streamline or eliminate manual, time-consuming tasks; improve the accuracy of rating and underwriting; and bind policies faster. It can aid in policy comparisons, ensuring policyholders get the most suitable products for their needs. And it can help detect and prevent fraud by analyzing patterns and identifying suspicious behavior.

As AI continues to evolve, we can expect it to contribute more significantly to improvements in the insurance industry. Since it relies on data (past) to enable its predictive capabilities (future), it will always look back to look ahead.

In an industry that measures its success retrospectively (based on claims experience), that’s not a bad way to go.

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