Bardon Insurance Bolsters Medical Stop-Loss for Self-Funded Employers with Gradient AI
Gradient AI’s Solution Provides Larger Datasets and Deeper Insights to Underwriting Process
Boston, MA December 12, 2022 - Gradient AI, a leading enterprise software provider of artificial intelligence (AI) solutions in the insurance industry, announced today that Bardon Insurance Group, a medical stop loss Managing General Underwriter (MGU), is using its SAIL™ solution to better evaluate the risk of medical loss for group health insurance.
Stop-loss insurance protects self-funded employers from unexpected and large employee health benefit claims by reimbursing them for claims over a predetermined amount. The stop-loss market is valued at approximately $25 billion, according to an AM Best report. As employer healthcare costs continue to rise, an increasing number of businesses are turning to self-funded health insurance models. However, lack of access to sufficient historical data leaves many companies unable to purchase stop-loss insurance. These employers are relegated to the fully insured market to provide health benefits, resulting in double-digit annual increases and plan designs that leave employees functionally uninsured.
Determined to provide its self-funded employers with better and more predictable benefits plans, Bardon searched for a solution to expand the limited insights it currently had into the risk of employee groups. After evaluating competitive underwriting solutions, Bardon ultimately chose Gradient AI’s SAIL solution.
“We chose Gradient AI because of its broad and high-quality dataset which provides us with greater insights to evaluate group health risk,” said Byrd Preston, Bardon vice president and chief underwriting officer. “With Gradient AI, we can price more aggressively and confidently because the technology allows us to assess risk at a very nuanced level. We are also able to underwrite more quickly, accurately and provide better customer experience all around.”
By leveraging Gradient AI's SAIL medical underwriting solution, Bardon obtains a greater level of fidelity and resolution for a particular group’s health profile. SAIL’s vast medical dataset coupled with its machine learning and advanced analytics enables Bardon to gain insights never before possible, dramatically amplifying its underwriting assessment accuracy and pricing power. The result is that Bardon has gained a unique competitive advantage with the ability to offer highly customized and cost-effective solutions for the self-insured market. This allows Bardon to provide the stop loss coverage that employers need to provide employee benefits more cost-effectively, enabling many employers to self-insure who may have been unable to do so otherwise.
“We are excited that Bardon is innovating risk management in the employer stop-loss space with Gradient AI’s greater insights,” said Stan Smith, CEO and founder of Gradient AI. “We look forward to our continued partnership with Bardon and support its work to offer its customers high quality, cost-effective and competitive health insurance solutions.”
About Gradient AI
Gradient AI is a leading provider of proven artificial intelligence (AI) solutions for the insurance industry. Its solutions improve loss ratios and profitability by predicting underwriting and claim risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation. Unlike other solutions that use a limited claims and underwriting dataset, Gradient's software-as-a-service (SaaS) platform leverages a vast dataset comprised of tens of millions of policies and claims. It also incorporates numerous other features including economic, health, geographic and demographic information. Customers include some of the most recognized insurance carriers, MGAs, TPAs, risk pools, PEOs and large self-insureds across all major lines of insurance. By using Gradient AI's solutions, insurers of all types achieve a better return on risk. To learn more about Gradient, please visit: https://www.gradientai.com.
Media Contact:
Elyse Familant
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