Integrating Human Intelligence with AI Capabilities: The Evolution of Commercial Underwriting

The digital transformation of commercial underwriting is gathering momentum. Manual processes and legacy systems no longer afford insurers the speed and efficiency to compete in the new economy. With the evolution and maturity of intelligent technologies, we are now well into the next generation of underwriting, where human expertise is integrated with data and automation to provide faster, more precise underwriting decisions across the demands of commercial risk evaluation.

Sathish Kumar Manimuthu, Chief Technology Officer at NeuralMetrics, shares his thoughts on how AI- and data-driven underwriting is evolving.

Can you describe the overall impact of modern technology on commercial underwriting?

Commercial underwriting used to be very labor intensive. For comprehensive risk assessment, especially in the small and medium business segment, underwriters need as close to a full 360 degree view of insurable businesses as possible. Such requirements can be  time consuming, including manual and methodical research to gain information on the location and its surroundings, in-person or virtual line of sight on the property, business operations and practices, and much more. Now, by just inputting a business name and email address, technology enables underwriters to access significant amounts and layers of risk information in seconds.

AI-driven technology can also make inferences about a business’s risk for the underwriter to validate. At NeuralMetrics, we provide full transparency about the data our platform uses to determine risk factors. Underwriters can review risk assessment questions and if they have any concerns, they can click on each information source and confirm suitability of the data.

Does transparent data sourcing mean underwriter expertise is further enhanced with the speed and accuracy of technology?

Yes. Basically, AI technology is enabling underwriters to direct their attention where it is needed most — assessing complex risks. And data transparency allows underwriters to confidently trust the accuracy and reliability of data for risk assessment of disparate businesses. Additionally. for businesses with fairly standard risk factors, AI-driven data access and transparent sourcing can elevate straight-through processing.

The downstream impact means underwriters can have time and flexibility to focus on more complex elements of their portfolio. AI-based technology can still help gather verifiable information, but underwriters can use their expertise to determine the nuances and pricing parameters for potentially multifaceted commercial and specialty risk profiles.

Where do you see underwriting technology headed? What will be the next evolution?

When conducting a risk assessment, typically underwriters review historical loss trends to determine loss incidences, exposures, and risk characteristics for that specific line of business.

One next step in underwriting evolution could well be moving away from just focusing on historical loss information and adopting a more data-driven decision process. In this approach, insurers and their underwriters can rely on data/analytics to no longer categorically avoid specific business classes, but rather evolve towards leveraging near real-time data to determine viable price points for the willingness to accept and write certain risks.

AI-enabled technology helps to open up vast reservoirs of structured and unstructured data — with much of it available in the public domain, and readily accessible to underwriters. Insurance organizations can therefore better classify their markets, accurately identify risk attributes, and more confidently determine their appetite to expand or compete in diverse classes of business to boost productivity and profitable growth.


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