Tag Archives: actuarial science

What is a Critical Point anyway?

How did Milliman’s podcast get its name? In this episode of Critical Point, Hans Leida and Doug Norris—both health actuaries and math PhDs—discuss how they decided on “Critical Point” for the name of the podcast. Hans and Doug talk about various aspects of mathematics, including topology, optimization theory, and chaos—and why the term “critical point” is so relevant in the actuarial world today.

To listen to this episode of Critical Point, click here.

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.

America’s relationship status with healthcare: It’s complicated

Financing and regulating healthcare in the United States is complicated. Fortunately, actuaries understand the intricacies and can provide unique perspectives to address the system’s complex challenges. In the article “Healthcare: It’s complicated,” Milliman’s Hans Leida and Lindsy Kotecki discuss issues related to reform that actuaries have helped navigate.

Here is an excerpt:

Besides predictability problems caused by regulatory or political factors, two challenges facing health actuaries during these transitional years have been (1) the lag between when market changes are implemented and when data on policies subject to the new rules becomes available, and (2) the difficulty in predicting consumer behaviour in reaction to major changes in market rules such as guaranteed issue and community rating. How many of the uninsured would sign up? How price-sensitive would members be when they renewed their coverage each year? How will changes in other sources of coverage (such as Medicaid expansion) impact the individual market? How will potential actions by competitors affect an insurer’s risk?

Despite the daunting nature of these challenges, actuaries have, out of necessity, found ways to try to address them. For example, faced with the data lag problem, they explored ways to augment traditional claim and enrollment data with new data sources such as marketing databases or pharmacy history data available for purchase. Such sources can be used to develop estimates of the health status of new populations not previously covered by an insurer. Many actuaries also developed agent-based stochastic simulation models that attempted to model the behaviour of consumers, insurers and other stakeholders in these new markets. Such models continue to be used to evaluate the potential outcomes of future changes to the healthcare system, and will probably be essential should efforts to repeal and replace the ACA prove successful.