“Can this really give me 7–8% long term?”

That’s probably one of the most common questions I hear — especially when clients are reviewing illustrations or comparing different policies.

And to be fair, the numbers do show up.

You’ll often see:

• 7%
• 7.5%
• Sometimes even higher

On paper, it looks compelling.

But this is usually the point where I pause and ask a different question.

Where Is This Number Coming From?

Because before accepting any projected return…

👉 it’s worth understanding how that number was derived.

What Illustrations Are Designed to Do

Illustrations are not predictions.

They are:
👉 projections based on assumptions

These assumptions can include:

• Expected market returns
• Index performance
• Bonus declarations
• Policy charges

👉 In other words:

Illustrations show what could happen
—not what will happen.

Why 7–8% Shows Up So Often

This is not random.

In many cases, higher projected returns come from:

• Optimistic assumptions
• Backtested index performance
• Smoother hypothetical outcomes

Especially when custom indices are involved.

👉 Which means:

The number looks precise —
but the foundation behind it may not be as firm as it appears.

A Gap That Builds Over Time

This is where things become more significant.

Let’s say a policy is illustrated at:
👉 7.5%

But over time, actual performance comes in closer to:
👉 4–5%

At first, the difference doesn seem large.

But over:

• 10 years
• 20 years

👉 that gap compounds.

And eventually, it starts to affect:

• Policy sustainability
• Cash value growth
• Overall outcomes

This Isn’t About Being Negative

To be clear — this isn’t about saying:

👉 “7–8% is impossible”

It’s about recognising:

👉 It’s not guaranteed
👉 And it’s not always realistic across all market conditions

What Drives the Difference

From what I’ve seen, the gap usually comes from a few key areas:

1. Market Reality vs Assumptions

Markets move in cycles.

Some years:

• Strong performance

Other years:

• Flat or negative

Illustrations tend to smooth this out.

2. Index Construction

As discussed earlier:

• Custom indices may rely on backtested performance
• Volatility controls can limit upside

👉 So even if the illustration shows 7%…

👉 real participation may differ.

3. Policy Charges

Over time:

• Costs increase (especially in IUL structures)
• Charges impact net returns

👉 Which means:
Gross return ≠ Net outcome

Where I See Clients Get Caught

Clients sometimes come in with expectations like:

“This should grow at around 7%.”

And that expectation becomes:

• A mental benchmark
• A planning assumption

But when actual performance differs…

👉 it creates confusion.

A More Grounded Way to Approach It

Instead of anchoring on a single number, I usually guide clients to think in ranges.

For example:

• Conservative scenario
• Moderate scenario
• Optimistic scenario

👉 This creates:

• More realistic expectations
• Better long-term planning
• Fewer surprises

Why Conservative Assumptions Matter More

This is something I’ve found consistently.

Clients who plan based on:
👉 conservative assumptions

Tend to:

• Stay more confident
• Make better decisions
• Experience fewer disruptions

Because Ultimately…

The goal isn’t to:
👉 maximise projected returns

The goal is to:
👉 build something that actually works over time

A Different Way to Think About It

Instead of asking:

“Can this give me 7–8%?”

A more useful question is:

“What happens if it doesn’t?”

Final Thought

High numbers can be attractive.

But in long-term planning:

👉 What’s realistic matters more than what’s possible.

Because expectations shape decisions —
and decisions shape outcomes.

If you’re currently reviewing illustrations or comparing different policy projections, it may be worth stepping back to understand how those numbers are derived — and how they may play out over time.

👉 If you’d like a clearer breakdown of your policy projections and what they mean in practical terms, feel free to reach out via WhatsApp