The human experience has a significant influence on decision-making — personal and professional.

Some influences can be obvious, like a positive experience making it more likely for a buyer to engage with a brand in the future. But there can be smaller and equally influential decisioning factors that are difficult to isolate and eliminate.  These random and elusive influencers include simple human factors like bias, fatigue, emotional distress, and even hunger.  This decisioning “noise” can create inconsistent outcomes in what should otherwise be a consistent system.

In his recent book, Noise: A Flaw in Human Judgment, Nobel Prize-winning psychologist Daniel Kahneman examines the impact of random influences in decision-making. Kahneman states that noise can undermine even the most sophisticated decision-making systems, resulting in wasted resources and missed opportunities.

“Noise is required reading at Planck,” says CEO Elad Tsur. “In addition to leading edge data and insights, the goal of our Cognitive Business Analytics Platform is to allow insurance carriers to eliminate noise and bias in underwriting through process automation.”

Like everyone, underwriters’ decisions can be influenced by subjective factors, such as mood, time of day, weather, or even the way research data is presented. This can lead to inconsistencies in the way policies are researched and priced, resulting in customer dissatisfaction and potential premium leak. Using artificial intelligence and machine-learning algorithms to standardize the decision-making process establishes clear criteria and carrier-wide best-practices for evaluating risk.

“Decision-making is a critical part of daily operations in insurance,” says Tsur, “and we understand these decisions can have significant financial consequences.  How a policy is handled shouldn’t depend on the experience or temperament of the receiving underwriter.  Reducing noise allows insurance carriers to make more informed, effective, and consistent decisions.”