Tag Archives: actuarial modeling

How can actuaries reflect investment risk in funding liabilities for pensions?

The launch of Actuarial Standard of Practice (ASOP) No. 51, Assessment and Disclosure of Risk Associated with Measuring Pension Obligations and Determining Pension Plan Contributions, offers retirement actuaries the opportunity to help employers better understand the risks associated with the pension plans, which may result in better decision making when managing these plans.

Until now, explicit disclosures about plan-specific risks have rarely been included in funding valuation reports. While ASOP 51 has changed this, it would not be surprising if some employers find it difficult to grasp their plans’ risks from non-numerical assessments and plan maturity measures.

By tweaking existing familiar concepts—the funding liabilities—actuaries can leverage the understanding that employers already have about their pensions plans to explain various risks, some of which are very pertinent to plan decision making.

Milliman actuary Bryan Jones provides more perspective in his paper “Stochastic modeling to reflect investment risk in funding liabilities for pension plans.”

Dependable data and analysis helps pension sponsors make decisions in today’s low interest rate environment

The low interest rate environment presents defined benefit plan sponsors with considerable challenges they must address. Because every pension plan’s situation is unique, sponsors need plan-specific data in order to make informed decisions. One of the only things that’s true across the board is that better decisions are made when sponsors have reliable and updated financial data.

In this article, Milliman’s consultants William Strange and Arthur Rains-McNally offer their perspectives on the challenges of the current interest rate environment. They also discuss how technological advances enable actuaries to generate and deliver realistic estimates of actuarial valuation results, funded status, expected investment returns, and other key factors in real-time to support critical business decisions.