Denver, CO – Valen Technologies, an advanced data and predictive analytics provider for property and casualty insurance leaders, recently announced a new customer engagement with FFVA Mutual Insurance Company (FFVA). As part of this partnership, FFVA has integrated Valen’s latest predictive analytics product suite, InsureRight 2.0, into the organization’s underwriting practices for workers’ compensation services, helping to make loss ratio improvements and more accurately set risk-based pricing. FFVA is utilizing Valen’s proprietary Premium Impact Model, Risk Model, Misclassification Model, portfolio management and production monitoring reporting, as well as the improved class fit analysis available with this solution.
InsureRight makes predictive data easily accessible to underwriters in real-time so that they can better assess and price risk on each policy within the underwriting workflow. Valen provides the only proof of concept benchmark in the industry that demonstrates how predictive analytics will perform on a book of business, delivering an average 5.4 loss point reduction for Valen customers. With a foundation powered by Valen’s proven predictive models, InsureRight allows organizations to leverage data and analytics to more accurately manage risk in workers’ comp.
“We believe that predictive analytics is becoming a necessity for carriers to succeed in today’s marketplace and are excited to partner with Valen to launch this key business strategy,” said Donna Grier, Vice President of Underwriting for FFVA. “Data is one of our most important assets and the InsureRight product will allow us to effectively and strategically use that data to improve risk selection, pricing, consistency and overall underwriting outcomes.”
FFVA is utilizing the full InsureRight feature set including the Premium Impact Model, a first-to-market model built from ValenNetworks® contributory database, comprised of more than 4 million recent policies. The Premium Impact Model allows underwriters to identify policies with a high likelihood of exposure misclassification that leads directly to additional premium or return premium associated with exposure shifts across classes from pre- to post- audit. This model can also help to increase the accuracy and actionable rate of insurers’ decisions to perform physical audits during a policy term or at policy expiration.
“We have a proactive and holistic approach to risk management, and by adding our newly released Premium Impact Model, along with the Risk and Misclassification Models, to FFVA’s underwriting workflow, the InsureRight 2.0 product allows the organization to target their resources and serve their customers with the most appropriate level of resource and coverage,” said President and CEO of Valen, Dax Craig.
FFVA will benefit from InsureRight’s most advanced 2.0 features by implementing Valen’s portfolio management and production monitoring reporting functionality, and enhanced class fit analysis. The portfolio management reporting from InsureRight 2.0 delivers a first-to-market suite of reports designed to give underwriters, managers, and executives deeper insights into their overall portfolio risk. This empowers them to make more proactive, actionable decisions to defend against adverse selection, capitalize on market position strengths and opportunities, and allocate resources more effectively and efficiently. Portfolio Management Reporting uses Valen’s InsureRight predictions to identify trends, opportunities, and threats in the marketplace in as close to real-time as possible. FFVA will now be armed with advanced intelligence, including trend analysis, governing class insights, distribution analysis and monitoring, and market analysis.
Furthermore, with InsureRight 2.0, FFVA can take advantage of Valen’s enhanced class fit reporting, which provides underwriters with an increased focus on the most relevant questions and potential risks associated with misclassification. This upgrade enforces consistency in underwriting questions related to class fit and establishes a consistent baseline for underwriting to class fit.
Source: Valen Technologies