Automated underwriting can help homeowners insurers maintain thoroughness and consistency in an accelerating marketplace, drawing from a growing array of actionable data and analytics delivered at the right time to support critical workflows. As automation helps to ease throughput for the majority of applications that are suited to low-touch handling, it can clear the way for underwriters to focus on the risks that truly need their attention.
Questions that no longer need to be asked can make room for new underwriting checks and questions.
The need for automation flows from consumers’ appetite for digital insurance transactions that mirror their other online experiences. Pricing can become the top priority in a low-friction sales model, and many insurers may feel pressure to eliminate difficult underwriting questions that applicants and agents often don’t answer correctly. A better alternative may be to better use the resources that help insurers stay grounded in their data-driven business fundamentals.
Best of both worlds
Basic information such as the insured’s name and the property address can trigger data pulls that help answer those “hard” questions without inconveniencing the customer or agent. These data points can be integrated to speed up underwriting workflows and decision-making—except when caution is warranted.
The questions that no longer need to be asked can even make room for new underwriting checks and questions that yield deeper insight. And while well-qualified risks can move quickly through the underwriting process, others may experience more resistance when additional qualification is required.
A range of automation applications
A data-driven strategy can help guide new approaches to multiple aspects of property risk, powered by an expanding universe of continually updated digital sources.
- Property condition: Automated data feeds powered by unique data sources, such as imagery analytics, nontraditional homeowner data, and permit information, can help insurers assess the condition of the overall property and identify specific features that require inspection, additional information, or more questions for the applicant or agent.
- Perils and mitigation: Data on location-specific perils and community- and property-level mitigation and hardening can help capture both the type and magnitude of exposure and how well the risk is prepared for the natural catastrophe perils specific to the location.
- Ownership, occupancy, and usage: Ownership characteristics and other situations that may indicate increased risk or sub-substandard maintenance can provide a different perspective for risk classification.
- Property features and replacement costs: Knowing information such as core property characteristics, alterations and improvements, and liability hazards is critical to supporting insurance-to-value for each property.
The sooner, the better
Reliability and timeliness matter, but where insurers use data in the quote flow can be just as important to maintaining efficiency and a satisfying customer experience. More accurate initial pricing based on fewer underwriting questions can add up to a process that keeps customers in the pipeline. Meanwhile, a better handle on the knowns and unknowns of a risk, right from quote start, can allow insurers to make more consistent, fact-based decisions and more efficient use of their underwriting staff, inspection tools, and other resources.
This kind of data-forward strategy may be best executed within an ecosystem of data, analytics, and technology built to work seamlessly together. A single application programming interface, delivering actionable data when it’s needed for automated underwriting, could be a critical step in digital transformation for homeowners insurers.
Learn more about Verisk’s LightSpeed for Homeowners and see how it could help power your journey toward automated underwriting.