New capability supports continuous improvement of predictive scoring performance
RICHMOND, VA, UNITED STATES, April 14, 2026 /EINPresswire.com/ — Fenris, a provider of real-time insurance data and predictive intelligence, is pleased to announce the immediate availability of the company’s Outcomes Service, a new capability designed to help insurers, managing general agencies (MGAs), and distribution platform partners continuously improve predictive model performance by reporting what happens after predictive scores are used in production workflows.
Fenris’ predictive models support decisions across intake, quoting, underwriting triage, lead routing, and retention workflows. As market conditions shift and customer behavior evolves, models can drift without consistent feedback. Fenris’ Outcomes Service closes that loop by allowing clients to easily submit real-world results back to Fenris using two simple values: the Submission ID returned in the original scoring request and a short outcome label, such as “bind,” “decline,” “lapse,” or “churn.”
These outcomes are used to refine and retrain models in alignment with each client’s own results, ensuring performance improves without relying on or exposing another client’s data.
Additionally, Fenris reached a significant predictive analytics milestone, noting that more than 100 million outcomes supplied by clients have now been reinvested into Fenris’ suite of predictive algorithms to support ongoing training and retraining. These outcomes strengthen the underlying modeling framework while enabling client-specific models to continuously adapt to their own performance data. Fenris uses these client-supplied results to improve scoring performance over time without requiring customers to rebuild models or resubmit application data.
“Predictive scoring improves when it reflects real outcomes,” said Jen Linton, CEO of Fenris. “Outcomes Service gives clients a clean feedback loop using the Submission ID, so our models can retrain on what actually happened within their own workflows and stay aligned as conditions change.”
“One of the biggest challenges in maintaining predictive models is assembling clean training data from disparate systems,” said Jay Bourland, CTO of Fenris. “As a result, models often stay in production longer than they should. Outcomes Service removes that friction by creating a direct, structured feedback loop, making it easier for models to stay aligned with real-world results.”
Outcomes Service is designed to fit normal operational workflows and automation patterns. Clients store the Submission ID returned during scoring and later submit an outcomes event when it becomes known. Outcomes can reflect a wide range of measurable events, including bind or decline, renewal or lapse, churn, fraud flags, and client-defined outcomes.
The Outcomes Service expands Fenris’ broader investment in infrastructure for AI-driven insurance workflows, following the company’s recent announcement of an MCP Server designed to enable AI systems and automation platforms to securely access Fenris intelligence through standardized protocols.
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About Fenris
Fenris provides real-time data enrichment and predictive intelligence through a suite of APIs that deliver quality information about individuals, households, vehicles, properties, and businesses. Insurers, MGAs, agencies, and platforms use Fenris intelligence to improve automation, decision-making, and customer experiences. Learn more at www.fenrisd.com.
Jennifer Overhulse
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