Traditionally, insurers have relied heavily on data they have collected as well as industry-specific data to inform their business decisions and strategy. However, data science techniques have become more sophisticated, allowing insurers to better understand the relationship between internal and external data sources. Predictive analytics, machine learning, data mining, and artificial intelligence are helping companies extract value from both sources.
In this article, Milliman’s Cormac Gleeson and Eamon Comerford discuss how the use of external data can complement a company’s wider data science initiatives. They also explore some of the challenges posed by working with external data.
Insurance customers expect personalized, agile, and on-demand delivery from carriers nowadays. Insurers must keep up with technological advances and implement them to provide solutions that address these expectations. In her Best’s Review article “Mind your ABCs,” Milliman’s Pat Renzi explores why insurance companies must center their strategic initiatives on using emerging technology like artificial intelligence (AI), blockchain, and the cloud. She also explains how partnerships that feature diverse experts will see faster, smarter, and more successful disruption.
Milliman has announced that gradient A.I., a Milliman predictive analytics platform, now offers a professional employer organization (PEO)-specific solution for managing workers’ compensation risk. gradient A.I. is an advanced analytics and A.I. platform that uncovers hidden patterns in big data to deliver a daily decision support system (DSS) for insurers, self-insurers, and PEOs. It’s the first solution of its kind to be applied to PEO underwriting and claims management.
“Obtaining workers’ compensation insurance capacity has been historically difficult because of the lack of credible data to understand a PEO’s expected loss outcomes. Additionally, there were no formal pricing tools specific to the PEO community for use with any level of credibility—until gradient A.I. Pricing within a loss-sensitive environment can now be done with the science of Milliman combined with the instinct and intuition of the PEO,” says Paul Hughes, CEO of Libertate/RiskMD, an insurance agency/data analytics firm that specializes in providing coverage and consulting services to PEOs. “Within a policy term we can understand things like claims frequency and profitability, and we can get very good real-time month-to-month directional insight, in terms of here’s what you should have expected, here’s what happened, and as a result did we win or lose?”
gradient A.I., a transformational insurtech solution, aggregates client data from multiple sources, deposits it into a data warehouse, and normalizes the data in comprehensive data silos. “The uniqueness for PEOs and their service providers—and the power of gradient A.I.—emerges from the application of machine-learning capabilities on the PEOs’ data normalization,” says Stan Smith, a predictive analytics consultant and Milliman’s gradient A.I. practice leader. “With the gradient A.I. data warehouse, companies can reduce time, costs, and resources.”
For more on how gradient A.I. and Libertate brought predictive analytics solutions to PEOs, click here.
Milliman has announced the launch of gradient A.I. (formerly MillimanMAX), an advanced analytics platform that uncovers hidden patterns in big data in order to improve workers’ compensation claims management. The gradient A.I. platform is a transformative InsurTech technology built on the latest advanced techniques and artificial intelligence (A.I.), and delivers a daily decision support system (DSS) for insurers and self-insurers.
Milliman has been conducting research and development in the most advanced areas of artificial intelligence—also known as “deep learning”—for over five years, and the rebranding of gradient A.I. is a reflection of that enhanced experience. Our goal with gradient A.I. is to deliver the most actionable intelligence to our clients in the form of “decision support—and we’re pleased to note that so far clients have seen underwriting profit improvements of 3% to 5% and claim cost reductions in the neighborhood of 5% to 10%.
The key differentiator of gradient A.I. is its ability to identify relationships between structured and unstructured data, unlocking powerful and previously unknown information to deliver a competitive advantage to self-insured groups, carriers, and third-party administrators within the property and casualty (P&C) market. Additional product features include a custom data warehouse, easily identifiable and actionable risk drivers, dynamic reporting, and customizable reports and dashboard.
To learn more, click here.
Applying for a mortgage loan is a process that requires a lot of information to make an informed decision. Even in this digital age the process of obtaining a mortgage remains complex. Can artificial intelligence (AI) technology that makes recommendations based on research from consumer organizations and federal agencies help? Milliman consultant Madeline Johnson looks at the question in her article “Couch surfing for mortgage loans.”