Cognitive Technologies Making Small Commercial Coverage More Accessible
In a roundtable dialogue, NeuralMetrics CEO, Prakash Vasant, and technical co-founder, Marcus Daley, discuss how cognitive technologies benefit underinsured and uninsured commercial enterprises and what technological enhancements mean to the future of underwriting.
How can AI and other cognitive technologies benefit uninsured and underinsured commercial enterprises?
Prakash Vasant (PV): The small and medium business (SMB) sectors represent a significant force in the economy, and may have unique risk profiles and face a variety of hazards and exposures. From the insurer’s perspective, the task of its underwriters – who must assess risks for all types of small/medium and larger businesses, and reliably collect an array of information – can be an enormous challenge. Overall, in the commercial sector, not just small and medium businesses, there is often a limited amount of readily available risk data, which can be a significant roadblock for fast, complete underwriting.
At our company, we leverage AI and natural language processing to address this challenge effectively. With very little identifying input, we can extract critical information to classify businesses and ascertain their risks. Our innovative and transparent approach to risk data extraction from public sources in real time adds value to an evolving commercial underwriting process and competitive environment where traditional tools do not suffice.
Marcus Daley (MD): Small and medium-sized businesses present an intriguing opportunity for agents and insurers. This market segment is often neglected and can encounter difficulties obtaining insurance. Insurers may not have the tools and data for accurate risk assessment, and the businesses may not have the knowledge and motivation to secure appropriate coverages, especially if they perceive comprehensive insurance as an additional expense.
At our company, we view SMBs as a high-volume market that can generate high-margin profits for insurers, while providing suitable coverage for policyholders. Through our open and unbiased processes, we can offer a solution to insurers looking to serve uninsured and underinsured SMBs. We can help drive insurance adoption by SMBs and support the growth of insurance organizations by streamlining underwriting processes, boosting straight-through processing, and ensuring accurate and fair premium pricing based on transparent and verifiable data sources. It’s also worth noting many of the same benefits apply to workflows for large commercial lines of business, where underwriters are much more hands-on for personalized coverages and pricing, but nevertheless still require real-time access to reliable and transparent risk data.
Q: What do these technological advancements mean for the future of underwriting?
MD: When conducting risk assessments, underwriters usually analyze historical trends to determine loss incidences, exposures, and risk characteristics related to a line of business. However, the next step in underwriting evolution may involve shifting from exclusively focusing on historical loss information to adopting a more data-driven decision-making process. This approach can allow underwriters to leverage data analytics to identify viable price points for accepting and writing specific risks, rather than avoiding business classes altogether.
AI-enabled technology can offer access to vast reservoirs of structured and unstructured data, mostly available in the public domain and easily accessible to underwriters. As a result, insurance organizations could more accurately classify their markets, identify risk attributes, and confidently decide their appetite for expanding or competing in diverse business classes to boost productivity and profitable growth