Funding Optimization and Guaranteed Issue

One of the greatest advantages of non-qualified deferred compensation (NQDC) plans is the degree of flexibility they offer the plan sponsor. Take plan funding, for example. There is no single required funding approach. Plans may be unfunded, or they may be funded with mutual funds, other taxable investments, or corporate-owned life insurance (COLI). In fact, the plan sponsor may choose to informally fund the plan, in whole or in part, with life insurance.  Using the specifics of the plan sponsor’s proposed plan design, the AFS financial model will measure the efficiency of covering each proposed insured and allocate the insurance coverage to the most efficient lives.

Utilizing Optimization and Guaranteed Issue

What is policy optimization and how is it used within a non-qualified deferred compensation plan? For the purposes of funding a non-qualified plan, policy optimization can be best described as:

“A multi-faceted funding technique that uses the most efficient schedule of death benefits across the defined group of insured participants in order to maximize product efficiency within Corporate Owned Life Insurance policies that are being used to informally fund a non-qualified benefit plan.”

Since liabilities and assets operate independently within an NQDC plan, maintaining an equitable Liability to Asset ratio is much more difficult than in qualified plans. With that in mind, it is incumbent upon the plan sponsor, or their third party administrator (TPA), to monitor this ratio on a regular basis. The goal of any plan sponsor or TPA is to make sure that the assets needed to fund the NQDC plan will be there when needed to meet benefit obligations. Policy Optimization is a funding method used to allow for cash values to grow at the peak efficiency, while maintaining the tax advantages and cost recovery aspects of life insurance funding.

Policy Optimization is a multi-faceted approach to achieving policy efficiency and consists of the following:

  •  Flexible Participation Minimums, and
  • Face Amount or Net Amount at Risk Deviation.

Participation Minimums: As the number of participant lives increases, minimum participation requirements become more liberal. This allows for the plan sponsor and TPA to select younger participants that have lower insurance costs and exclude older participants whose cost of insurance is higher.

 Face Amount Deviation: When the participant group is large enough, Face Amount Deviation may also be used to optimize policy efficiency. Face Amount Deviation involves the relationship of face amounts between insured participants. It can be used within a guaranteed issue program and can be combined with the minimum participation factor to boost product efficiency. For instance, a “deviation factor” of 25% would allow for face amounts on younger lives to increase by 25% over the guaranteed issue amount, while decreasing face amounts by 25% on older, more expensive participants.

The chart below illustrates the difference in a 20-life Guaranteed Issue underwritten model versus an 18-life Guaranteed Issue model using a 90% Participation Minimum Percentage and a Standard Deviation of 30%. By eliminating two of the older participants, then using the 30% deviation rate for face amounts on the remaining 18, the product efficiency was enhanced significantly in early years and for the life of the plan.

Criteria

20 Lives GI w/o Optimization

18 Lives GI w/ Participation Minimum & 30% Deviation

Difference 

CSV Year 1

$     734,084

$     740,171

$       6,087
CSV Year 5

$   4,221,405

$   4,257,455

$     36,050
CSV Year 10

$   9,389,505

$   9,502,141

$   112,636
CSV Year 20

$ 18,357,595

$ 18,809,068

$   451,473
Total Plan Impact

$ 37,259,875

$ 38,426,641

$ 1,166,766

 

  Census & Face Amount Deviations

Participant

Age

GI Face Amount

Face Amount w/ 30% Deviation

Executive 1

46

$ 769,600 $ 1,220,400
Executive 2

55

$ 769,600 $    657,200
Executive 3

43

$ 769,600 $ 1,220,400
Executive 4

52

$ 769,600 $    657,200
Executive 5

39

$ 769,600 $ 1,220,400
Executive 6

41

$ 769,600 $ 1,220,400
Executive 7

46

$ 769,600 $    657,200
Executive 8

46

$ 769,600 $    657,200
Executive 9

41

$ 769,600 $ 1,220,400
Executive 10

45

$ 769,600 $    657,200
Executive 11

59

$ 769,600 $              0
Executive 12

56

$ 769,600 $              0
Executive 13

56

$ 769,600 $    657,200
Executive 14

49

$ 769,600 $    657,200
Executive 15

37

$ 769,600 $ 1,220,400
Executive 16

44

$ 769,600 $ 1,220,400
Executive 17

49

$ 769,600 $    657,200
Executive 18

35

$ 769,600 $ 1,220,400
Executive 19

47

$ 769,600 $ 1,220,400
Executive 20

52

$ 769,600 $    657,200
Total $15,392,200 $16,242,000

Assumptions

No. of Lives

20 (16m, 4f)

Salary Def

10%

Corp Tax Br

40%

Avg. Age

47

Bonus Def

25%

EE Tax Br

35%

Ret. Age

65

Corp Match

5%

Benefit Period

1 year

Mort. Age

80

Salary Increase

3%

Earnings Rate

8% net, Not Guaranteed

We have much more extensive examples that we can walk through to demonstrate the benefit of this approach.  In summary, actively measuring the funding efficiency of the census can lead to significant improvements and the lives that the system does not always choose the youngest as you would suspect.

No comments yet... Be the first to leave a reply!

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: