More than a year after the COVID-19 pandemic began, its effect on small businesses lingers. Many small businesses closed their doors, while others had to change their business model quickly to survive. This, in turn, has affected commercial insurers, who must now transform their own underwriting practices to make better risk decisions. Many carriers use small business credit data and scores when underwriting risk, but these scores are designed to predict financial rather than insurance risk. However, by going beyond traditional credit data and leveraging additional data sources, insurers can get a true risk profile of a small or micro business.
Writing for the risk
To help commercial insurers leverage multiple financial data sets in their underwriting processes, LexisNexis® Risk Solutions launched a new insurance model for the Attract™ for Commercial Underwriting platform. This new model leverages our relationship with the Small Business Financial Exchange (SBFE), a nonprofit trade association that advocates for the safe and secure growth of small businesses. How will this benefit commercial carriers? By combining business credit data from SBFE with our own data, we can provide insurance carriers with a more complete risk picture on small and micro businesses.
The Attract for Commercial Underwriting platform provides predictive modeling that enables insurers to evaluate a business by its loss propensity at the point of quote, underwriting or renewal to obtain more accurate, consistent loss prediction and policy pricing.
These models use business credit type data to deliver an insurance score derived from business credit, model indicators/reason codes to provide the context of the score, as well as attributes from the credit report. Sometimes referred to as the “secret sauce” that runs through many insurance products and services, Attract commercial models combine the most predictive data elements across multiple sources, including:
- Commercial credit data
- Business demographics
- Business owner data, including personal credit and claims
Increase lift over traditional processes
Adding SBFE data, which includes more than 39 million small and micro businesses to the platform brings additional financial data not found in other sources today. Simultaneously, data from LexisNexis Risk Solutions, such as public records and other alternative data, supplements the model when a business has a limited financial footprint. This new model can provide up to 82% scoreable rate coverage on businesses, almost doubling the lift of traditional processes.