HomeNews & IdeasPerspectivesThe best risk data for underwriting is customer interaction data

The best risk data for underwriting is customer interaction data

McKinsey argues that external data plays a pivotal role in enhancing the effectiveness of artificial intelligence within Property and Casualty (P&C) Insurance underwriting. While this holds merit, our empirical observations in P&C Personal lines suggest that customer behavior at the point of sale (POS) and during endorsements often offers superior insights into customers’ true intentions and attractiveness.

This discrepancy arises from the fact that data, despite its value, is fallible. And customers and policyholders sometimes manipulate correct data to gain pricing or risk advantages. Consequently, carriers face challenges in discerning inaccuracies or dishonesty within the data with the limited time and resources available. This leads carriers to make suboptimal decisions, both by underwriting risks they shouldn’t and rejecting attractive ones.

Clearly carriers need a mechanism to detect and resolve conflicts and uncertainties at POS and endorsement. Specifically, they need to be able to detect and evaluate customer interactions during insurance transactions. Our multi-year experience helping carriers do precisely this showing that such interactions not only clarify data but also serve as behavioral tests, offering insights into customers’ intent and therefore their true risk levels.

But why is direct customer interaction during transactions so valuable?

  • It communicates to customers that their actions are being monitored.
  • It aids customers who may be confused or facing unique issues and are unsure of how to proceed.
  • By dispelling the veil of transactional anonymity, it often deters dishonest behavior among customers.
  • It enables immediate resolution of issues without delays.

Clearly, promptly contacting customers upon identifying issues is the optimal approach for both service provision and risk mitigation. However, in an environment where the number of quote requests per policy issued continues to escalate, relying solely on manual intervention has become economically unfeasible. Consequently, underwriting tends to focus only on the most egregious risk issues, either employing ‘knock-out’ rules that reject entire categories or opting not to address them at all. The latter is particularly prevalent in handling endorsements to existing policies, where we find most manipulations occur.

Regrettably, contemporary core transactional systems overlook behavioral cues, often missing critical indicators of potential excessive losses. In today’s fiercely competitive landscape, where agents have been reduced to mere order processors in the pursuit of market share, carriers urgently require cost-effective digital solutions capable of detecting issues, defining the relevant questions and data for resolution, and swiftly feeding decision codes back into their policy systems for processing. Moreover, these solutions must navigate dozens of different scenarios in each personal insurance line without violating regulatory standards.

This is the role played by idFusion’s idRuleBuilder and idResolve solutions. They empower carriers to craft, assess, and deploy intricate business rules, requests, and forms without the need for extensive programming, facilitating immediate passive testing and rapid deployment to tackle emerging issues. These rules extend beyond factual assessments to encompass evaluations of customer behavior at both the point of sale and during endorsements.

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