Granular policyholder data has increased exponentially during the past decade, with many insights buried deep inside. Insurance companies are so inundated by data that they often rely on non-scientific manual methods in their pursuit of those insights.
With AI tools, insurance leaders can parse huge volumes of data almost instantly, enabling them to underwrite and price all classes of insurance more precisely. More accurate underwriting and pricing leads to fewer claims, lower loss ratios and higher profits, while reduced labor and costs let them write more new business.
The unique combination of AI, ML and actuarial techniques empowers insurance companies to decide whether to accept a specific risk by quantifying the risk and recommending pricing based on policy holder rating factors.
Available as either an app or an API, the technology can be fine-tuned based on your specific data, improving outcomes even further as the tool learns over time.
Insurance companies also gain insights about the rating factors that most contributed to a prediction, enabling the company to streamline interpretability, business planning and strategy.
