Tag Archives: Nodal

Milliman wins three InsuranceERM Americas Awards for its insurtech products and risk consulting services

Milliman is pleased to announce that the firm has won three 2020 InsuranceERM Americas Awards for its insurtech products and risk consulting services. The goal of the IERM Americas Awards is to highlight enterprise risk management leaders in the Americas.

In the technology category, Milliman’s Nodal™ was named “Analytics Solution of the Year” while Milliman’s Arius Enterprise® won “Cloud Technology of the Year.” Awards in these categories recognize insurtech solutions that enable strategic decision-making and provide risk insights that can improve efficiency and operations for (re)insurers. For instance Nodal, Milliman’s predictive modelling platform for early claim intervention, uses machine learning to comb through unstructured data and identify high-risk claims, and has helped clients reduce claims severity by 15% and overall losses by 41%. Meanwhile, Milliman’s Arius, one of the industry’s most comprehensive reserve analysis solutions, has saved clients hundreds of hours per year while simultaneously improving analyses and governance over data and processes.

Milliman was also recognized with a 2020 InsuranceERM Americas Award for its risk consulting services, with three members of the firm’s Chicago Life ERM practice taking home “Risk Team of the Year.” Anthony Dardis, Ariel Weis, and Chloe Lau have, combined, over 60 years’ experience on both the assets and liabilities sides of life insurance, and are well-known for their benchmarking capabilities and “practical-first” approach to risk management.

“Transformation in the insurance industry begins by leveraging new technologies in conjunction with the latest data and expert analysis, three areas in which Milliman excels,” says Milliman President and CEO Steve White. “Managing complex risks requires both the best expertise and the most innovative tools, so we feel gratified to have won IERM Americas Awards for both our risk consulting and technology solutions.”

For more information on Milliman’s insurtech products, including Nodal and Arius, click here. For more information on Milliman’s enterprise risk management solutions, click here.

Predictive modeling can forecast workers’ comp claims and increase efficiency

Identifying workers’ compensation claims with potentially high costs—before those costs have developed—has, for the most part, eluded insurance and self-insured companies, even though they pay more than $60 billion in workers’ compensation benefits every year. Over 80% of all workers’ compensation costs come from a small number of unpredictable, high-cost claims. Conversely, lower-cost med-only claims account for 75% of total claims but only 5% of the cost.

These hard facts are the claims reality that insurers and self-insurers like the Intergovernmental Risk Management Agency (IRMA) face daily. Focused on improving performance and reducing costs for its 70-plus members organization, the Chicago-area member-owned public risk pool had been looking for a way to increase efficiency regarding workers’ compensation losses while improving accident prevention and claims responses for its members’ workforces.

A major challenge to peeling back the mystery in its “unknown high-cost claims” was finding a way to access the predictive data in adjusters’ notes, case manager notes, and other sources of text data. This unstructured, free-form data could provide an early warning of potentially costly claims, but requires claims managers to read through reams of adjusters’ notes. This manual process typically delays identification of potentially problematic claims and the assignment of appropriate resources, and, given the glut of material to sift through, can lead to hit-or-miss results.

In this case study written by Michael Paczolt, learn how Nodal™, Milliman’s web-based predictive modeling and decision-support system, sped up the process and accurately identified 95% of high-cost claims for IRMA before they happened, reducing costs by over 15%.