Insurers can use AI to analyze real-time public data in a timely manner. This blog explores the importance of public information for commercial underwriters to get timely, comprehensive risk profiles of businesses.
A common question to NeuralMetrics is, “What makes your AI-enabled data analytics platform different from other solutions?” Briefly, our solution doesn’t rely on private and static data sets but instead looks at dynamic, publicly available structured and unstructured data sources to help commercial underwriters make informed decisions about risks and exposures. Access to fresh risk-quality data and insights on an as-needed basis ensures insurance organizations are using the most recent and up-to-date information in their risk assessment workflows.
Here’s an example of just how vital public data can be for risk assessment. One of our clients was underwriting a business and our system produced an alert that this was a higher risk than what they perceived it to be, based on their risk appetite parameters. The client decided to continue the underwriting process and bind the policy. Then, the business ended up with an expensive claim. Subsequently, risk-assessment processes were audited internally, including the question of why NeuralMetrics flagged the account as a higher risk despite being undetected within the client’s existing underwriting workflows. This was because the NeuralMetrics platform accessed and evaluated public information, and uncovered information that the business was conducting activities at night, which triggered a high-risk flag based on the insurer’s guidelines. The detail was buried in public information sources and, therefore, not easily accessible to underwriters doing manual research.
In providing risk-quality insights, the NeuralMetrics platform doesn’t make judgement calls. Those decisions are for insurers to make, based on their underwriting guidelines and risk appetites. Why? Because each insurance organization has its own risk tolerance rubric and process for deciding what exposures are in or out of appetite. Our goal in supporting underwriting teams is to provide access to a diverse range of public data — providing comprehensive overviews of potential risk, so insurers can make informed decisions on which classes of business and policies to quote and bind.
For an in-depth discussion about how NeuralMetrics is using AI to help insurance organizations improve risk assessment, listen to our technical co-founder, Marcus Daley, on the Edge of AI podcast.