Milliman receives actuarial firm of the year award

Milliman was named actuarial firm winner by this year’s U.S. Captive Review Awards. These awards recognize captive insurance products and services providers offering high levels of excellence over the past year.

“We are extremely grateful to judges of the 2018 awards for recognizing the efforts of our team at Milliman over the past year. With a firm-wide focus on providing exceptional service, we continually strive to develop cutting-edge solutions to our clients in the captive industry,” said consultant Mike Meehan, who was named to the Captive Review Power 50 list in 2016 and 2017.

Employment practices liability considerations in the #MeToo generation

Public attention from U.S. athletes and celebrities and movements like #MeToo and #TimesUp have drawn increased awareness of—and action around—sexual harassment.

As employers work to improve existing sexual harassment training and policies, they continue to find themselves dealing with the repercussions of past incidents, often through lawsuits or insurance claims that are typically covered under their employment practices liability (EPL) policies. These policies provide employers with liability insurance covering wrongful acts arising from the employment process, one of the most common of which is sexual harassment.

When pricing for an EPL policy, actuaries typically use historical claims experience to predict the emergence of claims in the future. Similarly, actuaries estimate incurred but not reported reserves on existing claims to account for growth in the claim value expected above that contemplated in the claims adjusters’ case reserves. To the extent that trends in claim frequency and severity are changing, the historical claims experience may no longer be an accurate predictor of future claims experience. It is essential for companies writing these policies to consider this level of uncertainty in their estimates.

Legislative changes are also introducing a level of uncertainty to claims that may affect pricing and reserving in the future. And now more than ever, companies must find the right balance of coverage and retention limits as well as establish a plan and budget for prevention. This includes sexual harassment training, policy establishment, and enforcement. With this evolving climate, it is also essential for employers to closely monitor their EPL coverage.

To read more about the current state of EPL in the age of #MeToo, read Maigh Wright’s article here.

Risk management is key when appetite for risk increases

Insurers increasing their appetite for risk when markets climb pose challenges when markets begin to experience corrections. Behavioral finance lessons apply now more than ever as markets continue to climb and risk appetite increases by investors and institutions.

Individuals behave in ways that often run counter to their self-interest—something that sophisticated life insurers would never succumb to. As some companies turn their backs on well-planned risk management strategies to manage product volatility, the question arises whether some life insurers are also acting against their better nature.

Like individual investors who have lost sight of their goals only to return to a prudent investment strategy after a financial crisis, some life insurers, which were exposed to the effects of the 2007-2008 recession, returned to the risk management fold at the bottom of the recession, often redoubling their risk management programs at a hefty price just after the tail event.

In this article, Milliman’s Ghalid Bagus and Suzanne Norman explore the drivers of this behavior and the impact it had during the last crisis.

Market risk benefits: What is in scope?

The Financial Accounting Standards Board recently approved changes to the accounting for long-duration insurance contracts. This included the creation of a new category of benefits called market risk benefits. This paper by Milliman consultant William Hines discusses market risk benefits and contract features that might be within their scope.

Milliman awards 16 Opportunity Scholarships in the program’s second year

Milliman is pleased to announce the recipients of this year’s Opportunity Scholarship program. This scholarship program, now in its second year, was created to assist students from ethnic groups and races that are under-represented in the fields of actuarial science, data science, computer science, economics, programming, mathematics, statistics, data analytics, or finance.

This year, the Opportunity Scholarship recipients include 16 students from colleges and universities across the United States, Australia, South Africa, and the United Kingdom who have demonstrated academic excellence and plan to pursue a career in actuarial science or related fields. Last year, which was the inaugural year of the scholarship, 12 scholarships were presented.

“Milliman is proud to assist students from diverse backgrounds in achieving their educational goals in fields like actuarial science, mathematics, computer science, and finance,” said Milliman Chief Executive Officer Steve White. “This year’s group of recipients comes from a wide array of backgrounds and has shown that they excel academically, with the drive and knowledge to succeed.”

Below is the list of this year’s Scholarship recipients:

1. Victor Asiwe, actuarial science, at University of Cape Town (South Africa)
2. Aleesha Chavez, computer science, at Northwest Nazarene University (Idaho)
3. Khethiwe Dlamini, actuarial science, at University of the Free State – Bloemfontein (South Africa)
4. Jordan Howell, actuarial science, at Kettering University (Michigan)
5. Jael Kerandi, finance, at University of Minnesota-Twin Cities
6. Rachael King, mathematics, at Macquarie University (Australia)
7. Adam Lathan, actuarial science and data analytics, at Drake University (Iowa)
8. Richard Machivenyika, actuarial science, at University of Cape Town
9. Mapule Madzena, computer science, at University of the Free State – Bloemfontein
10. Jennifer Mora-Amaya, actuarial science, at St. John’s University (New York)
11. Sonia Moreno, computer science, at Carleton College (Minnesota)
12. Sarah Peña, actuarial science, at UCLA
13. Bryce Santiago Badura, computer science, at University of Notre Dame (Indiana)
14. Ayomikun Vaughan, actuarial science, at Queen’s University of Belfast
15. Edwin Villavicencio, actuarial science, at North Central College (Illinois)
16. Mattie Zimmer, mathematics, at University of New Orleans

Five of this year’s recipients also received Opportunity Scholarships last year. Those repeat recipients are Khethiwe Dlamini, Jordan Howell, Sonia Moreno, Sarah Peña, and Ayomikun Vaughan.

How can advancements in predictive analytics help identify reinsurance workers’ comp claims early?

Developments over the past few years in predictive analytics are providing opportunities to improve the early identification of claims with a higher likelihood of piercing workers’ compensation reinsurance layers. Over the past decade or so, the field of claim analytics has moved from performing forensic work on closed claims to analytics that can identify at 60 days from the date of injury (or sooner) claims with a high likelihood of exceeding a retention level.

While an excess loss is obvious for some catastrophic claims, the buildup to the attachment point is less obvious for many excess loss claims due to the subtleties of compounding factors. A significant challenge with early identification analytics for claims that have not reached an excess loss attachment point is that the administration of the claim is often handled by several specialists without any single participant noticing the aggregation of costly factors.

A recent development in predictive analytics is the use of machine learning software that extends the principles of conventional multivariate analyses. In contrast to the conventional analyses, these advanced analytic methods are not limited to linear relationships. Another development is the extraction of text information from claim adjusters’ notes, nurse care manager reports, and medical reports.

The advances with machine learning software and text mining algorithms are necessary tools for the early identification of claims most likely to become excess loss claims. To learn more about how analytics has affected the early identification of claims, read this article by Lori Julga and Phil Borba.