Segal Rogerscasey Canada’s dedicated Asset-Liability Modeling (ALM) team continuously enhances our capabilities to provide clients with the latest techniques and tools to better manage their funds or plans. We analyze the impact of allocation changes on key actuarial metrics using a stochastic process. In 2006, The Segal Group acquired Irwin Tepper Associates, Inc., a consulting firm that specializes in asset-liability analysis for employee benefit programs and other organizations.
Each asset-liability study is designed to meet our clients’ specific requirements and uses the fund or plan’s demographics and data. The studies can be used to address a number of factors, including:
For single employer plans:
For multi-employer plans:
ALM provides a platform for decision-making. By analyzing proposed changes in the asset portfolio, investment strategy, plan design or funding policy, our clients can evaluate the trade-offs of the choices. ALM adds quantitative insights to supplement qualitative views, allowing our clients to make better decisions.
The ALM process evidences due diligence in support of fiduciary obligations of the plan sponsor.
As opposed to asset allocation studies, which only measure the variability of portfolio returns, an ALM study recognizes that the long-term success of an institutional investor is measured by the investor’s ability to meet the promised obligations and it allows the trustees to evaluate this.
Our ALM process begins with an examination of fund objectives with the plan’s sponsors. We assess the decision metrics of the plan and how success is determined. While rate of return is important, we work closely with plan sponsors to identify other metrics that are more holistic. We believe that the success of our pension funds should be measured by how well the assets secure the commitments of the liabilities. Examples of these metrics include the plan’s funded ratio, zone status (for multiemployer ERISA plans: green, yellow or red) and the credit balance.
We also identify the important measures of risk for the plan. While measures of downside risk such as standard deviation, value-at-risk and conditional value-at-risk are important, there are other measures of risk that may drive allocation decisions. These risk metrics may include liquidity and concentration risk, funded ratio, zone status (for ERISA plans) and withdrawal liability.
Next, we assess the plan’s overall risk appetite as well as the needs of the plan. We work to understand the current funded status of the plan, its liquidity needs and long-term growth needs. Our experts evaluate the liability side of the balance sheet and determine how liability needs can be met with various asset strategies.
In developing the asset classes to model, we take into account the plan sponsor’s comfort level with various strategies such as alternative investments, long-duration fixed income and derivatives. Many of these strategies are complex in nature and may entail second order risk. We review all options with the client before modeling any of these strategies. Our specialists are skilled at translating quantitative results into clear explanations that plan sponsors can use to make decisions.