AI-driven data transparency enables more accurate, efficient underwriting, superior policyholder service, and more business.
What happens when underwriter expertise is combined with transparent data to assess a client’s risk? The answer: You get more accurate, efficient underwriting, better customer service, and more business.
Carriers should be advocating for data transparency. It can save their underwriters significant time and help fuel business. Here are three reasons why data transparency is critical to insurance risk assessment:
1. It builds customer trust. “That is what our underwriting program determined,” is not going to suffice if a policyholder is wondering why they were denied coverage, or their premium ended up being significantly higher than what was quoted. Insurance customers understand businesses use algorithms to speed up processes, but they also know the algorithms can be inaccurate. Being able to ascertain exactly where the information comes from and how it is used can help underwriters give policyholders clear answers to their questions.
2. The human-computer combination enables faster, more efficient interactions. Carriers get the best of both worlds: the speed of automation coupled with risk-evaluation expertise means underwriters can make decisions faster. If there is a discrepancy, they can easily resolve it by checking the sources for themselves, eliminating the need for manual research. Underwriters can have confidence the information they are using is accurate. Without transparency built into a data real-time platform, if an underwriter determines the solution answered a question incorrectly, it could well erode trust in other critical data elements within the application, requiring redundant and unproductive manual reviews by underwriting teams.
3. The company’s data compliance obligations are timely and proficient: Consider California’s Consumer Privacy Act or Connecticut’s Personal Data Privacy and Online Monitoring. More and more states are enacting data privacy legislation, while the federal government is also working on similar legislation. Data privacy issues and unintended bias in data analysis are growing concerns throughout the insurance industry. Are solutions using personal information about a company’s leaders or employees that could infringe on their privacy rights? Are algorithms delivering different results for different demographics of people? Carriers that can show exactly what information was is to underwrite a business can more easily satisfy regulatory concerns. If there is an issue raised about the fairness of price, for example, the carrier can easily pinpoint the data and source materials used to determine the premium and overcome regulatory concerns about bias, overreach, or access to personal information.
For more insights into the value of data transparency, and how it can improve processes for carriers, agents, and MGAs, check out this article in Insurance Thought Leadership.