Optimal Pacing for Private Assets: An Example

The FRG Private Capital Forecasting (PCF) solution recently released a module for optimal pacing.  Pacing refers to the planning of future commitments. Future commitments encompass a decision on commitment size as well as a decision on commitment timing. This is done to help balance a portfolio’s needs to achieve or maintain allocations to private capital vehicles.

Creation of pacing plans is not straightforward. The plan should consider not just the allocations to private asset classes, but to other asset classes as well. It also needs to balance these commitments with liquidity constraints and the need to keep all asset classes from breaching risk limits.

The Pacing Module combines the class-leading PCF forecasting simulation with stated portfolio goals for allocation and limits with a non-linear optimizer to create optimal pacing plans.

This blog posts walks through an example pension fund that is in a net distribution scenario.  They are actively selling down the portfolio to fund retirements. Further, they have only recently begun to invest in private capital. Their allocations are low and need to be brought up to target.

PCF has been configured with this information. The fund manager has specified semi-annual rebalancing for the public side of the portfolio.

The simulation will run through 2027 and the plan will be created for vintage years 2020 – 2024.  Investments will be planned in the sub-asset classes of Private Equity (Buyout and Fund of Funds), Real Estate, and Venture.

The fund is experiencing outflows.  Overall NAV of the portfolio is declining.

Charts showing allocation and NAV

 

The first graph shows the expected cash needs per quarter to fund employee retirements.  This represents cash leaving the portfolio and leading to a decline in total NAV.

The second chart shows the NAV growing out of the pandemic recession and then beginning to decline as cash requirements outstrip fund growth.  The mean and inner quartile range from the simulation are plotted.

Because NAV of the portfolio is declining pacing is extremely challenging. Investing too much risks an illiquid portfolio, unable to be sold to meet retiree needs.  Investing too little might mean that the portfolio does not reach its allocation target and undershoots the expected return.  The portfolio manager is in a bind.

Graphs shows portfolio allocation total before PCF optimization

The fund is underweight to private assets.  The manager needs to build the portfolio allocation to meet the expected return target, but as stated above, investing too much could cause liquidity problems down the road.

The Pacing module takes the simulation of the portfolio and optimally chooses which and how much vintages to invest in.  Once the optimization has been run, we can see the allocations through time are better in line with the targets:

Chart showing improved allocations after optimization has been run.

 

If you would like more information about VOR Private Capital Forecasting or the VOR Pacing Optimization Module, please download our white papers here or reach out to Dominic Pazzula.

Dominic Pazzula is FRG’s Director of Risk and Asset Allocation. He is a specialist in investment management, asset allocation, portfolio construction, and risk management. 

The 5 Ws and H of IFRS 17 (Part 2)

Previously, we talked about the 5 Ws of IFRS 17. This blog post (Part 2) will discuss the H: How does IFRS 17 replace IFRS 4?

A Consistent Model

Figure 1: The components that make up IFRS 17 insurance contract liabilities.[1]

IFRS 17 introduces the General Measurement Model (GMM) to calculate insurance contract liabilities for all insurance and reinsurance contracts. It is made up of three components:

  1. Present Value of Future Cash Flows (PVFCF)
    1. Expected future cash flow – The current estimates of cash inflows and cash outflows e.g., premiums, claims, expenses, acquisition costs, etc.
    2. Discount Rates – Current market discount rates, which are used to normalize the present value of expected future cash flows.
  2. Risk Adjustment (RA) – The compensation a company requires for bearing insurance risk. Insurance risk is a type of non-financial risk and may consist of the uncertainty of cash flows, the timing of cash flows, or both.
  3. Contractual Service Margin (CSM) – The equal and opposite amount to the net cash inflow of the two previous components. This ensures there is no day-one profit recognized in Profit or Loss (P&L) for all contracts.

 

More Transparent Information

Figure 2: How IFRS 17 recognizes profit in P&L.[2]

IFRS 17 only allows insurers to recognize profit once insurance services are provided. This means that insurers can no longer recognize the premiums they receive as profit in P&L. Rather, at the end of each reporting period, insurers will report the portion of the CSM remaining as Insurance Revenue after they fulfil obligations such as paying claims for insured events.

Insurance Service Expenses reflect the costs incurred when fulfilling these obligations for a reporting period. This consists of incurred claims and expenses, acquisition costs, and any gains or losses from holding reinsurance contracts. The net amount of Insurance Revenue and Insurance Service Expenses make up the Insurance Service Result. This approach differentiates the two drivers of profit for the insurer: Insurance Revenue and Investment Income. Investment Income represents the return on underlying assets of investment-linked contracts, and Insurance Finance Expenses reflects the unwinding and changes in discount rates used to calculate PVFCF and CSM.

Better Comparability

Figure 3: A comparison of IFRS 4 and IFRS 17.[3]

Regarding presentation of financial statements, IFRS 17 requires more granularity in the balance sheet than IFRS 4 (Figure 3), specifically on the breakdown of insurance contract liabilities: PVFCF, RA, and CSM. This allows for improved analysis of the insurer’s products and their business performance.

On the statement of comprehensive income, IFRS 17 has removed Premiums and replaced Change in Insurance Contract Liabilities with the new components introduced in the balance sheet – PVFCF, RA and CSM. Now, the first items listed present the insurance components that make up Insurance Service Result. This is followed by Investment Income and Insurance Finance Expenses, which together determine the Net Financial Result. With a clear distinction of the different sources of profit, this framework allows for better comparability among industries.

Conclusion

In summary, IFRS 17 is the accounting Standard that introduces a consistent model for measuring liabilities for all insurance contracts. It also increases the transparency of the source of insurance-related earnings by separating insurance services from investment returns, which provides global comparability for the first time in the insurance industry.

[1] Appendix B – Illustrations, IFRS 17 Effects Analysis by the IFRS Foundation (page 118).

[2] Preview of IFRS 17 Insurance Contracts, National Standard-Setters webinar by the IFRS Foundation (Slide 9).

[3] Preview of IFRS 17 Insurance Contracts, National Standard-Setters webinar by the IFRS Foundation (Slide 11).

Carmen Loh is a Risk Consultant with FRG. She graduated with her Actuarial Science degree in 2016 from Heriot-Watt University before joining FRG in the following fall. She is currently the subject matter expert on an IFRS 17 implementation project for a general insurance company in the APAC region.

RELATED:

The 5 Ws and H of IFRS 17 (Part 1)

 

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