Generative AI data engines for commercial insurance classification and risk assessment can now address the “small data problem” of providing appropriate coverages and premium pricing for small businesses.
Today, artificial intelligence (AI) is all over the news. The rise of OpenAI has put this conversation front and center. There’s talk of computers taking over the world, deep fakes, and the spread of misinformation — plus the concern that AI is going to eliminate jobs, in some cases, overnight.
For people in those types of jobs, an alternate view is based on practicality, rather than fear. AI itself isn’t going to steal jobs. But professionals who embrace AI may well gain an upper hand in increasingly competitive job markets. Everyone is better off understanding the power and potential of AI and proactively leveraging cognitive and generative technologies in positive ways. For instance, a recent report from MIT suggests AI isn’t going to take away jobs but is likely to change them.
AI is already making a substantial impact on the way work and jobs are evolving across industries. In insurance, AI has led to positive impacts, especially in roles that rely heavily on data. Insurance underwriting is a good case in point:
AI is making the entire underwriting process faster and more accurate. The technology enhances underwriters’ abilities to better identify and evaluate risk factors and determine precise insurance premiums via access to real-time data about risk quality. AI also enables the automation of many manual tasks, much faster analysis of large data sets about exposures, and substantial improvements in fraud detection. Already, many underwriters are spending less time on manual research and fact-finding for risk assessment. Instead, they can shift their data-driven focus to more confidently assess new account opportunities that meet their companies’ risk appetites.
NeuralMetrics embraces the idea that underwriters’ work and output can be enhanced with faster, more dependable information about risk—particularly when it comes to commercial insurance. As an example, AI-powered insurance data solutions, like our classification and risk assessment data engines, can now address a prevalent, industry-wide “small data problem,” otherwise known as the challenge of providing appropriate insurance coverages and premium pricing.
For many small- and mid-size businesses, where only a modest amount of risk information is typically available. But, by using AI technology and providing it only a business name/address or website, underwriters can gain access to vast public data sources, and then generate instantaneous risk insights for accurate policy pricing, while remaining compliant with local laws and regulations.
For more perspective on how OpenAI and are impacting business operations, check out our article in Forbes.