August 22, 2021
Underwriting Small Business Post-COVID
Carriers must go beyond traditional data sources to minimize the information gap and transform the underwriting of small businesses.
Despite the impact of COVID-19, the commercial insurance marketplace must provide the proper insurance coverage for small businesses that have survived, morphed, jump-started or stalled. Insurance carriers have needed to assemble a more complete snapshot of each small business’ individualized risks, but now that’s more important than ever. To do so, carriers need to go beyond traditional data sources to minimize the information gap and help to transform the underwriting of small businesses.
Assessing risks more accurately
One of the challenges in underwriting a small business is finding sufficient financial data about the business. According to a 2019 internal study conducted by LexisNexis Risk Solutions, approximately half of small businesses have a credit profile only in a single commercial credit bureau. When insurers exclusively use commercial credit for commercial rating, they are likely missing the true risk profile of the small business in their book.
To properly protect a small business customer, insurance carriers need to make sure they’re collecting and analyzing available data. Fortunately, there is an abundance of data and analysis available to overcome this problem; it just needs to be aggregated, analyzed and provided in a readily digestible way.
Gain from a multi-source strategy
A multiple-source approach can address the gaps, but identifying and evaluating the right data sources is critical for pricing a risk fairly, for both the customer and the insurer. Our internal analysis shows that when insurers use three financial data sets in their underwriting, it results in an average scorable rate of 74% compared with just 52% with only one source.
Leveraging small business credit data also provides insurance carriers with extended visibility and financial data insights on small and micro businesses, and combining small business credit data with other available business data makes it even more powerful. Providing predictive modeling makes it easier for carriers to evaluate a business by its loss propensity at the point of quote, underwriting or renewal.
With financial data from millions of small businesses, carriers can benchmark a customer against the industry at large and have financial insight that may not be found in commercial credit sources. This approach, with an incremental model of business data and small business credit data, can provide up to an 88% scorable rate coverage on small businesses and can match up to 96% when combined with business owner financial data.
See also: COVID-19 Trio Tops Global Business Risks
Create an inclusive approach
For commercial carriers looking to improve their book of business, begin by understanding your current and future target market. How do these types of businesses compare with similar entities in your book of business, and what financial products do they use?
Next, select the right sources of data for a particular business. Credit bureaus, non-traditional financial sources and personal financial data can all be used to better align to your book of business.
Lastly, create an underwriting program that leverages these data sources to better segment small businesses based on a more precise view of the business’ or business owner’s financial profile. This design, a predictive model, is built specifically to help you more quickly and confidently assess risks. Taking advantage of segmentation can increase the effectiveness of your program and improve your loss ratio contingencies.
Insurers looking to remain competitive within the small business market need to evaluate the right mix of information on both the business and its owner to price the risks of each small business they insure more accurately. Embracing change and seeking predictive models with industry data can improve risk assessment and support more dependable decision-making.