Investment Returns for Participating Endowment Plan — How are they determined?
Anyone in Singapore who has bought or considered buying a Participating Endowment Plan in recent past must be familiar with seeing benefit projection at two investment returns — 3.25% p.a. and 4.75% p.a. Ever wondered how these rates are chosen? Yes, these are prescribed by Life Insurance Association Singapore but how do they determine these rates? This article is an attempt to the answer the question. Thanks to one of our readers who asked the query after reading the last week’s article on jargons, which defined investment returns in simple terms apart from many other life insurance jargons
Coming back to the two investment returns also known as lower investment return and upper investment return, which correspond to 3.25% p.a. and 4.75% p.a. respectively. These rates are not cast in stone and reviewed by Life Insurance Association (LIA) each year. These were last revised on 1 July 2013 and the corresponding rates before the revision were 3.75% p.a. and 5.25% p.a. Before 2002 the higher investment return was at 6% p.a.!
Now that we know LIA actively reviews these rates the important question is what forms part of the review process? The review process involves a three-step approach and I would now describe each of them.
1. Survey of long-term investment outlook: LIA conducts a survey to seek the views of member companies on returns of long-term asset classes like equities, bonds and properties (which typically form part of the participating fund). The factors considered in determining the outlook include macroeconomic climate, GDP growth and inflationary expectations.
For the purpose of the survey, two different scenarios are considered i.e. central and negative scenario. The central scenario refers to the most probable scenario whereas the negative scenario is the conservative outlook of the future returns. In order to understand this better, let’s consider the following example
Once the estimate from every member is received, LIA identifies the most common return (which in statistical parlance is called the median) for each asset class and for both the scenarios. The median may or may not be the average of estimated returns received from the member companies. Continuing with the example and for the sake of simplicity, let’s assume that the following are the median estimate of returns
2. Asset Allocation: LIA also determines the average proportion of assets for each asset class. This is based on past trend and future outlook. After the considerations, LIA identifies the benchmark portfolio. To make things clearer, let’s assume the benchmark portfolio has following asset allocation
1. Portfolio Returns: The final step is to determine the upper and lower investment returns. This step is straightforward and is based on the first two steps of the process. Investment returns are determined by multiplying the median returns (identified in step 1) and proportion of assets (identified in step 2) and summing them across the asset classes.
· Upper Investment Return = 10% x 30% + 1.9% x 50% + 4% x 20% = 4.75% p.a.
· Lower Investment Return = 6% x 30% + 1.7% x 50% + 3% x 20% = 3.25% p.a.
Now we know the process behind the two investment returns. Well, does that mean if an insurer consistently achieves 4.75% p.a. during the policy term, the policyholders would get the benefit as identified in the benefit illustration? The answer is may or may not as investment returns are just one of the several factors determining the bonuses. The other considerations are identified in this article!
Before I sign off I wish to thank you again for the encouraging feedback and invite you to #AskTheActuary, wherein I would be answering to life insurance related queries in real time. Every alternate Monday, starting 20th August at 8 PM SGT!
Disclaimer: The article has been written with an aim to broadly explain an otherwise complicated and technical topic for readers with little or no insurance background. Hence, it doesn’t have finer details but is still broadly correct. The article is based on the limited information available on the public domain for determining the lower and upper investment returns. The example used in the article is fabricated and is targeted to simplify the concept.
About the writer: Mr Sumit Ramani is the Chief Actuary of fidentiaX. He is a qualified Life actuary and a computer science engineer with over a decade of experience in (re)insurance business with focus on modelling of life and health products, peer review and business analysis.