Category Archives: InsurTech

How can predictive analytics enhance group life and disability insurance?

The group life and disability insurance sector has been slower to adopt predictive analytics than other lines of insurance. One reason for the sector’s lag is because insurers often have limited information on who they are insuring. However, there are still many ways to incorporate predictive modeling technology to improve results. Milliman consultant Jennifer Fleck provides some perspective in her article “Group insurance ‘Project Insight’.”

Flood warning: Working to provide better coverage

Flood is one of the most devastating catastrophic perils, in which a single event can create tens of billions of dollars of loss. It is also one of the least insured perils, affecting people in every part of the United States. Advanced risk models now provide granularity, assessing flood risk at local levels. Such technological development presents insurers the opportunity to offer affordable, risk-based coverage within a private insurance market. Milliman colleagues Nancy Watkins, Matt Chamberlain, Andrei Stoica, and Garrett Bradford offer perspective in this video.

To learn more about Milliman’s flood expertise, click here.

MillimanMAX, a Milliman predictive analytics platform, renamed “gradient A.I.” to reflect advanced analytic techniques

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.

Milliman’s Arius named “Best reserving solution” in 2017 InsuranceERM Awards

Milliman has announced that Arius®, Milliman’s advanced analytics loss reserving software for insurers and reinsurers, was named “Best reserving solution” in the 2017 InsuranceERM awards. Senior industry experts from across Europe and the UK served as judges for the award.

The recognition comes as Milliman launches Arius 3.0, which provides significant enhancements to the software’s automation capabilities, together with key additions to its reporting tools. This is the 13th major release of new functionality since Arius’s introduction four years ago.

“Our goal with Arius is to provide an InsurTech solution that will increase efficiency and streamline insurance companies’ reserving processes,” said Ken Scalf, Property & Casualty Software Products Manager at Milliman, “and we’re thrilled it’s being recognized as ‘Best reserving solution’ by InsuranceERM. Arius provides much-needed reliability and efficiency in this era of increased industry disruption.”

In addition to the industry’s leading desktop loss analysis toolset, Arius 3.0 debuts as the centerpiece of Milliman’s just-released Arius Enterprise solution. The new Enterprise system provides reserving departments with cloud-based centralized data, department-wide project management, automation, governance tools, and sophisticated reporting and data visualization. Arius Enterprise, which runs on the Microsoft Azure platform, specifically addresses the challenges faced by mid- to large-sized insurance companies.

Milliman debuts Arius Enterprise, next generation loss reserving software for insurers and reinsurers

Milliman has announced the release of Arius® Enterprise, the next generation of advanced analytics software for loss reserving for the insurance and reinsurance industry. Arius Enterprise is part of Milliman’s Arius family of solutions and relies on the industry-leading Arius software to provide the analysis and modeling tools that today’s sophisticated actuarial departments have come to depend on to keep their business ahead of the competition.

The release of Arius Enterprise specifically addresses challenges facing actuarial departments in mid-to-large insurance companies, including process inefficiencies, data management, workflow, reporting, and compliance. Key features of Arius Enterprise include:

• Easy access to data using Microsoft’s secure cloud-based Azure platform
• A centralized database that stores, shares, and manages data for accurate and effective analysis
• Automated tasks throughout the reserving cycle, including automatic roll-forwards
• Proper internal controls and tracking of all user activity through audit trails
• Consolidated reporting together with executive-level dashboards and exhibits generated in Microsoft Power BI, promoting greater transparency and more informed decision-making for both analysts and other stakeholders

As the insurance industry faces disruption from evolving technology, our goal is to provide a cloud-based solution that will streamline companies’ reserving processes and create much needed efficiencies. With Arius Enterprise, we have an InsurTech system that provides consistency, reliability, and control, so that actuaries can focus their time where it’s most needed.

Wireless connectivity can produce intelligent transportation systems and smart cities

Connected and automated technologies have the potential to revolutionize transportation systems into safer, cleaner, and more efficient systems. That transformation will center on vehicle-to-vehicle (V2V) as well as vehicle-to-infrastructure (V2I) connectivity. While some cities have already taken the first steps in this process, there are several issues that interested municipalities must consider to create fully functional connected cities—also known as smart cities.

The following excerpt from Milliman consultant Christine Kogut’s article “Connected cities: A path for local governments” highlights these issues. In the article, she also discusses the benefits of creating connected cities and possible sources of funding for them.

Enormous improvements in transportation are within reach, but for these gains to be fully leveraged, local municipalities will need to start considering a range of issues that cut across technology, infrastructure, budgeting, zoning, social balance, and risk management among others.

Connected vehicle infrastructure. These elements typically focus on deploying roadside communications equipment, installing a fiber backbone in roads, implanting street and traffic signals with sensors or other connective devices, expanding broadband capacities, developing detailed road mapping services, and having data services to collect and process vehicle data.

Zoning and land use. As shared ownership and on-demand ride services become more popular, the space needed for parking could decline, but the need for pick-up and drop-off areas could increase. Further, fully automated vehicles that can park themselves tightly together may mean that smaller parking facilities will be required in downtown or congested areas. Municipalities may be able to repurpose these facilities or rezone them for other commercial or business use.

Changes in revenue streams. Revenue from moving violations and parking may also fall as connected and automated vehicles with system controls linked to motor vehicle laws and speeds come on the road. Municipalities that depend heavily on these sources of revenue will likely need to rethink their funding models, perhaps shifting to sources other than the transportation industry or to more mileage-based user fees, congestion pricing, and/or use of tolls.

Staffing. With safer connected and automated vehicles that less frequently stray from motor vehicle laws on the roads, fewer on-the-beat police will likely be needed to patrol the roads, but more human resources would be needed to support back-office and in-the-field traffic and system operations.

Condition of current infrastructure. Municipalities with well-maintained road stock have an advantage over their counterparts that have pot-holed and poorly marked roads, which have and continue to be an obstacle to developing fully automated vehicles.

Legal and regulatory issues. While federal and state officials unravel issues related to CAV [connected and autonomous vehicles] safety standards, cyber risks, and privacy, local officials will also have to grapple with more grassroots issues such as determining procedures for ticketing an automated or driverless vehicle.

Public benefit. For a city’s entire population to benefit from advances in transportation, municipalities will also need to make accommodations for bike and ride sharing and on-demand rides–services on which mass transit users typically rely.

Planning. Because of the long lead time to full automation, planning needs to be flexible. For example, a 30-year municipal bond issued today to fund a parking garage may not deliver on the revenue stream if only current use patterns are considered in modeling the revenue streams. Likewise, transportation needs and vehicle miles driven could be affected by the adoption of financial incentives like pay-per-mile driving, increased vehicle occupancy from shared rides, increased appeal of public transit stemming from new first-and-last mile solutions, the public’s willingness to commute longer distances in hands-free automated vehicles, increases in empty passenger or cargo loads on return trips, or reduced bundling of trips.