Category: Uncategorized

The Challenges When Assessing OCIO Performance: Applying Global Investment Performance Standards (GIPS) to OCIOs

Posted on by Chris in Briefings, OCIO Search, Uncategorized

Introduction

Assessing OCIO performance is an important part of evaluating OCIOs as candidates for our clients.  The task also has many imbedded complexities.  The CFA Institute has taken steps to address some of these complexities. 

We explain here why we think the CFA Institute is moving in the right direction, but we still believe that GIPS Standards do not provide a complete picture of #OCIO performance.  Instead, when we evaluate OCIO performance we assess performance by asset class, looking both at performance relative to client specified asset class benchmarks, and also performance driven by asset class selection.

Background

The CFA Institute and its predecessor AIMR set the foundation for assessing investment performance of individual investment managers.  They created the Performance Presentation Standards, which evolved into the Global Investment Performance Standards or “GIPS,” an acronym trademarked by the CFA Institute. 

In a world where the foundation for almost all investments were liquid, publicly traded securities, GIPS’s uniform methodology revolutionized the asset management industry.  GIPS created standardization in performance reporting and disclosures, which greatly increased transparency and comparability in our industry.  The standards allowed allocators to access improved and objective information about the investment performance of their investment managers.[1] 

[1] To improve reliability and lessen dependence on investment managers’ own self-reporting, an ecosystem of independent GIPS compliance developed.  The audit industry started to provide GIPS attestations which are basically two main levels of independent, third-party attestations. Verification (firm-wide) and Performance Examination (composite-level), These attestations simply assert whether or not the investment manager calculated and presented their performance in compliance with GIPS standards. The auditor verification does not provide assurance on the accuracy, validity, or performance of any specific composite report. A firm cannot claim that a specific composite is “verified”.   The GIPS standards merely tell the investor that the performance has been calculated and presented in compliance with GIPS standards.

The Initial Application of GIPS to OCIOs Created Confusion

It is understandable that the CFA Institute would wish to extend GIPS to cover OCIOs, since OCIOs are becoming increasingly important in the institutional asset management marketplace. However, OCIOs seeking to comply with GIPS faced a major challenge: GIPS did not sufficiently allow differentiation of client-types in the OCIO managers’ composite returns.  The result was a mixing of low-risk, immunized pension plans with return-seeking foundations into composite returns.  Only when an OCIO’s client mix was relatively uniform did the GIPS standards offer any hope of being a meaningful measure of an OCIO’s skill in advising clients.

Another major challenge with computing GIPS returns for OCIOs is the fact that OCIO strategies are not directly comparable across OCIOs.  For example, some OCIOs pursue 100% liquid investment strategies into equities and bonds, while others will allocate up to 50% in private strategies.  It would be difficult to assess the performance of the liquid OCIO strategy against the OCIO with the 50% private strategy.

Moreover, within equities are sub-asset classes with vastly different risk profiles.  Within liquid equity strategies, OCIOs may present choices of value equities versus growth equities. More broadly, OCIOs may offer relatively low-risk consumer staple equity strategies, versus highly illiquid venture capital investments into AI and biotech.  Comparing an OCIO that is offering a high proportion of venture strategies with a 10-year commitment, with an OCIO that offers a high proportion of value equity strategies would create complications, since the underlying question is the asset allocation choice and the relative success within those choices.  The relative performance comparison only scratches the surface of the OCIO performance analysis.

Challenges from Including Illiquid Private Strategies in GIPS

OCIOs present challenges that stretch the limits of GIPS.  At its inception, GIPS primarily addressed investment strategies consisting of liquid securities with transparent pricing.  That is not the case for many OCIOs that may have 10% to 50% of the portfolio invested in semiliquid or illiquid strategies.  The pricing transparency of those assets can range from high for many hedge funds, to very low for venture capital investments. 

So how does GIPS handle this transparency challenge?  It does so indirectly, by implicitly relying on valuations provided by the managers of the underlying private strategies.  This method is called the “practical expedient” valuation method.  With current market conditions, the “practical expedient” tends to have the following attributes:

  • Understated volatility: Valuation changes are driven by major, infrequent events, like pricing for latest capital raises, or private corporate sales.  Thus, the volatility of valuations from the “practical expedient” method are greatly dampened compared to publicly-traded investments. 
  • Overstated valuations: We believe that managers of private strategies have a tendency to be optimistic in the face of distressed market conditions.  That appears to be the case for private credit managers, where the private credit funds have de minimis losses over the last year, whereas their publicly-traded analogs are often trading around 25% lower. Older private equity funds also face a similar dynamic in private markets, where investors will trade their 5- to 10-year-old vintages at times with discounts of 25% to 50% off of the values stated by the managers.
  • Overstated private returns:  If the valuations are overstated, so are the returns. 

CFA Institute Seeks to Implement Better OCIO GIPS Standards

The most recent proposed GIPS standards present a material improvement over the initial GIPS standards, because they allow for the breaking out of “growth assets” from “capital preservation” or “liability management” assets:

Required OCIO Composites for Total OCIO Portfolios

Required OCIO CompositesAllocation to
Liability-Hedging
Assets		Allocation to
Growth Assets
Liability-Focused Aggressive
Liability-Focused Moderately Aggressive
Liability-Focused Moderate
Liability-Focused Moderately Conservative
Liability-Focused Conservative		0–20%
21–30%
31–50%
51–75%
76–100%		80–100%
70–79%
50–69%
25–49%
0–24%
Required OCIO CompositesAllocation to
Risk-Mitigating
Assets		Allocation to
Growth
Assets
Total Return Objective Aggressive
Total Return Objective Moderately Aggressive
Total Return Objective Moderate
Total Return Objective Moderately Conservative
Total Return Objective Conservative		0–20%
21–30%
31–50%
51–75%
76–100%		80–100%
70–79%
50–69%
25–49%
0–24%

Source: CFA Institute “Exposure Draft of the Guidance Statement for OCIO Strategies” from October 16, 2023

Challenges from Including Heterogeneous Strategies in GIPS Composites

As can be seen from the #CFA Institute’s proposal, #OCIOs will be permitted greater gradation of risk appetite by client type, which is a helpful improvement over the GIPS standards for traditional liquid managers.  However, the new standards do not distinguish for:

  • Volatility dampening and income smoothing of “growth asset” strategies that are private assets, nor the valuation risks assumed by using the “practical expedient” valuation method.
  • Gradations of risk, primarily in the Growth Asset category, which inappropriately places venture capital and value investing in the same risk bucket.
  • Differences in liquidity across #OCIO clients.

We note that the Alpha-NASDAQ OCIO benchmark generally accepts these flaws, but provides gradations of 10 risk-appetite buckets of 10% allocation differences between Growth Assets and Capital Preservation assets.  Like the CFA Institute OCIO GIPS standard, the #Alpha-NASDAQ OCIO benchmark approach does not correct for illiquidity difference, use of the “practical expedient” accounting practice, volatility dampening or income smoothing. 

Conclusions

#GIPS standards for OCIOs are evolving.  We believe the CFA Institute is taking a step forward by recognizing that not all OCIO clients are identical, and allowing OCIOs greater ability to distinguish among them by broad bucketing. 

Unfortunately for us as #OCIO search consultants, we cannot rely on these standards, nor the AlphaNASDAQ approach, because neither account for the use of “practical expedient” accounting, volatility dampening and income smoothing, or differences in liquidity. 

We encourage the CFA Institute to continue to consider evaluation of GIPS practices for OCIOs, while realizing that they may want to consider additional disclosures covering liquidity, asset class performance, and percentage use of “practical expedient” accounting methods in portfolios. 

In the meantime, our approach is to gather asset-class level performance, and information on liquidity restrictions and valuation practices, to help us assess performance at a deeper level. 

#OCIO Search

#OCIO Evaluation

#Investment Adviser Search

#Investment Consulting

#Investment Consultant Search

Are OCIOs Ready For AI-Driven Volatility?

Posted on by Chris in Briefings, Family Office, OCIO Search, Uncategorized

Epic changes to equity market structure have occurred over the last five years that challenge key tenets followed by OCIOs.  The ascension of the Magnificent Seven to market supremacy has been a major theme where OCIOs have struggled, along with other sophisticated asset allocators.  Collectively the Magnificent Seven rose 111% from December 31, 2023 to December 31, 2025, compared to 48% for the S&P 500, yet OCIOs were substantially underweight the Magnificent Seven.  We will discuss the reasons they missed it.

The rise of AI-related businesses presents the next epic change, and the emergence of hierarchies within AI-related industries should be a key focus.  OCIOs and institutional investors seem to be missing this important nuance as well, treating AI-related businesses very differently based on their asset class [public equity, private equity, venture, or real estate] without having a strategy of how to discern how these investment opportunities relate to the broader AI theme.

I. How did OCIOs miss the Magnificent Seven opportunity in 2023 and 2024?

1. The Quest to Avoid Concentrated Single-Stock Exposures and an Implicit Value Bias Blinded OCIOs to the Opportunities

Many OCIOs adhere to an asset allocator’s perspective when viewing stock concentrations, and they surrender any role in actually analyzing individual stocks to the equity managers they select.  Those equity managers usually wish to prove their excellence with a diversity of ideas, not by concentrating in mega cap stocks that are widely held.  Moreover, a very superficial view of Magnificent Seven P/E valuations implied that they were overvalued, which reinforced the conviction of many equity managers to underweight the Magnificent Seven. 

By contrast, our February 2024 briefing “You May be in VC but not know it: OCIOs versus “The Magnificent Seven”” showed that the Magnificent Seven were actually undervalued. They have since outperformed the S&P 500 cumulatively by 63% for 2024 and 2025. They now represent an astounding 39% of the S&P 500, but their growth premiums have also risen, as depicted in the charts below:

Sources: data derived from publicly available sources, including financial statements of issuers and finance.yahoo.com

2. Did OCIOs Surrender Responsibilities as Financial Analysts?

We believe that, if there are less than 10 mega cap stocks driving much of the market, conducting some of your own financial statement analyses of these stocks themselves can yield helpful insights in your asset allocation strategy.  That’s why we took a contrarian position in our February 2024 review of the Magnificent Seven stocks.  Our review found that Magnificent Seven balance sheets were conservatively valued, and earnings materially understated. A big portion of the cost–R&D employee expenses–for developing their main asset–intellectual property–is expensed rather than capitalized. Thus earnings were materially “understated” because GAAP categorizes such investments as expenses, and assets did not reflect the full value committed to product development over time. 

These big stock returns were not anomalies.  The Seven generate substantial cash flow and profits with substantial growth, and they represent a meaningful part of the U.S. economy. Viewing them as n=7 out of 500 in a diversification framework was a risk manager-driven error.

II. Looking Forward – The Changing Market Narrative and AI-Led Volatility

Massive investments in AI technology and infrastructure are rapidly reshaping investment markets.  We no longer hold a view on whether the valuation of the Magnificent Seven is rich or cheap.  Instead, the AI activities of the Hyperscalers [Amazon, Microsoft, Alphabet, and Meta] have become the key market narrative.  These companies have historically been heavy investors in research and development.  Those R&D budgets are now much higher, and together with heavy investments into physical plant for cloud computing sites, total Hyperscaler investments now substantially exceed earnings in many cases.

Why are Hyperscalers investing so heavily in AI?  Current AI-related earnings do not appear to justify the investments.  If the rapid growth assumptions presented by OpenAI and others come true, the total rate of return on a $1 trillion + investment might make sense, but much can also go awry.

Consider the following perspective: “spending too much on AI is a profitability risk while spending too little on AI is an existential risk.”  Falling behind your competitors could lead to being surpassed in a transformational stage of the cloud computing marketplace, thus jeopardizing your immensely valuable cloud computing business.  At the same time, it’s hard to imagine a better formula to create an environment for massive overinvestment. In 2025, the Magnificent Seven’s R&D was 35% of their net income, and property, plant and equipment investments represented an astonishing 62% of net income. We’ll return to that topic soon. 

III. The Emerging Hierarchy in the AI Industry

I’ll quote the insightful commentary of one of those rare trust portfolio managers that outperforms the S&P 500 by a few percentage points per year, and who prefers to remain anonymous:

“As the hyperscalers (e.g., Amazon, Microsoft, Google) accelerate datacenter growth to support the offerings of first tier AI developers (i.e., OpenAI, Anthropic, Alphabet, Meta) and lesser entrants (e.g., DeepSeek, Mistral, xAI), and as they and others infuse their products with generative AI, they have spurred GDP growth in an otherwise lackluster economy, with consequential impact on a growing set of industries.  For example, Caterpillar, typically known for its bulldozers and backhoes (useful for construction) also makes big generators required for datacenter backup power during electrical blackouts.  As these companies see increased demand from datacenter builds, it increases costs and reduces availability for other industries including any attempting to reshore to the USA.

More importantly, there is an expanding list of late-to-market and/or unsophisticated money starting “neocloud” companies including CoreWeave, Nebius, and Fermi, which seek to create datacenters campuses to lease to the hyperscalers, finance companies such as Blue Owl Capital providing funding for such endeavors, and then there is Oracle, a once first tier and now second tier tech company which was late to cloud and now late to AI.  These late entrants have higher costs and lower margins than the owned capacity of the hyperscalers, and with the exception of Oracle have no end customers and no intellectual property.  When there is eventually some correction or reckoning, it will be felt here first and very painfully, so we’re staying well clear.  The hyperscalers have end customers, intellectual property, and the revenue to fund their datacenter builds, so while there is risk to profitability, there is as yet no risk to survival of these companies.”

IV. Hyperscalers and AI Developers: Considerations for OCIOs Positioning Portfolios

We see here a hierarchy of AI-related businesses that OCIOs could use to position their investments in the AI ecosystem.  We believe the Hyperscalers are the best tier, closest to the ultimate clients and having the most robust business models.  They outsource the largest risks and potentially a substantial amount of upside returns to the first tier AI developers that the Hyperscalers partially own. Some of the AI developers [particularly Open AI] are also spending massively on data centers in addition to AI R&D.  They have also sourced investor capital from sovereign wealth funds and other large institutions, providing leverage to expand their buildout rapidly.  Their success would drive business to the hyperscalers, fortifying the early-investor advantage that Hyperscalers had by investing early in the AI enterprises while providing strong investment returns.[4]  Second tier Hyperscalers like Oracle and, much further down the food chain CoreWeave and others, have very high elasticity to the success of the AI business model but would also be most likely to fail in an AI downturn.  Venture firms building AI applications for clients also have substantial upside, but they may also find themselves competing with the technology development arms of the Hyperscalers. 

We see much value creation coming from building AI applications but we struggle to justify valuations of $50 billion and up for de novo ventures. 

  1. Real Estate Data Centers

Farthest away from the true end-customers are the data center-focused real estate investors.  We view data centers as having the worst return for risk in the AI industry vertical.  We understand that the real estate fund sponsors negotiate long term contracts with the Hyperscalers and others for capacity use, but we suspect that in a downturn the Hyperscalers will find ways to use their own PP&E first, rather than pay real estate investors for use of unneeded capacity.  Institutional real estate investors have a strong tendency to overinvest wherever they see opportunities, damaging their track records.  We see no reason why datacenter-focused real estate investments will be any smarter this time.  If a conservative real estate investor thinks they can achieve better returns allocating to datacenter-focused investments, we would suggest that they instead consider investing directly in the liquid stocks of the Hyperscalers. 

2. Venture Capital

Where do venture capital firms stand in this hierarchy?  First we note Pitchbook’s 2025 Q4 statistic that 71% of new venture commitments were made into AI-focused ventures.  That statistic indicates that diversification benefits from venture investing could also be lower than investors might hope for.  Another finding from our Magnificent Seven review was that the Magnificent Seven are the most prominent venture investors, and their R&D budgets overwhelm the size and scope of all venture firms put together.  They are also far better venture capital investors than most of the VC industry, because they have better and more comprehensive tech know-how and they are closer to actual customers.  Thus, an investor interested in venture should consider the mega cap Magnificent Seven as a liquid substitute for illiquid venture investing. 

Venture Capital’s average performance is also not attractive, but if you are a top quartile investor in venture capital, your returns are far better than this:

V)  How Investing in AI Could Rapidly Go Horribly Wrong

Management of some Hyperscalers and AI ventures tout rapid growth projections for AI revenues.  Alongside revenue growth comes volume growth.  As measured by wattage use, “Global electricity generation to supply data centers is projected to grow from 460 TWh in 2024 to over 1 000 TWh in 2030 and 1 300 TWh in 2035 in the Base Case” according to the April 2025 “Energy and AI” report by the International Energy Agency [IEA].  Other reports project even higher growth in energy use. 

Such volume growth is a strong justification for high valuations, assuming prices and margins are reliable.  But are they reliable?

Financial analysts, not always known for their technological insights, are sometimes unaware of important shifts in the technology landscape.  Consider the 2025 AI Index Report by Stanford Institute for Human-Centered AI.  This report shows a rapid rate of efficiency improvements, as AI models become better trained and focused on relevant data. 

“Driven by increasingly capable small models, the inference cost for a system performing at the level of GPT-3.5 dropped over 280-fold between November 2022 and October 2024. At the hardware level, costs have declined by 30% annually, while energy efficiency has improved by 40% each year. Open-weight models are also closing the gap with closed models, reducing the performance difference from 8% to just 1.7% on some benchmarks in a single year. Together, these trends are rapidly lowering the barriers to advanced AI.”

The following table from the EIA report shows the additional benefits of targeting AI models on narrower, more pertinent data:

We have seen elsewhere that improvements in AI programming could reduce computational costs by 90 to 99%, so the Stanford report is consistent with that experience.   

Let’s consider the scenario where usage rises not just fourfold as implied by IEA, but tenfold, driven by greater client use and launches of increasingly complex top-end AI models.[3]  In this same scenario, the amount of wattage actually needed falls by 90% for that volume of usage, driven by use of more-targeted programming and data sets.  The result is 10x increase in calculations * 1/10th the cost, or no incremental volume to the Hyperscalers.  That scenario would be a disaster for the real estate investors into datacenter REITs, whose properties we would argue would be first to be idled.  But the biggest impact of this scenario is that cloud computing prices and margins would decline sharply over time.

Tremendous uncertainty about volumes, capacity constraints, and costs pervade the AI discussion but one consideration that is not uncertain is that the laws of Economics will

eventually manifest themselves.  If investors are seeing a nearly infinite market with strong margins, and hyperscalers think that “spending too much on AI is a profitability risk while spending too little on AI is an existential risk,” we can be sure that investments will continue until these investors feel the damage of a sharp correction. 

VI. Has This Happened Before?

AI’s eventual sharp correction would not be a first. Another industry also faced an era of rapid technological development, an apparent infinite demand, and strong investment flows.  That industry was the shale gas industry.  Consider its productivity improvements alongside the inflation-adjusted price movement of U.S. Natural Gas. 

      Source: EIA report from Oct 17, 2014              Sources: EIA for price and U.S. BLS for CPI-U

New shale gas rapidly drove down prices from the mid-2000s to the mid-2010s.  For shale gas producers, the major hit occurred in 2015, when prices appeared to be falling below production costs and ultimately fell by more than half.  Widespread industry distress occurred, and once-leading fracking firms like Chesapeake Energy eventually folded. Only a tepid recovery occurred, and natural gas prices never recovered consistently to the levels of the early 2010s.

  • Conclusion – How Should OCIOs Think About the AI Market Shift?

Cloud computing and AI are not the same as shale gas.  Hyperscalers and AI developers will create moats using intellectual property[1][2], long term contracts, and bespoke applications for individual clients that will help protect against commoditization.  Nonetheless, the point will come when overbuilding will create excess capacity.  When that happens, investors should be prepared for a sharp pullback.  Hyperscalers are best positioned for that scenario.  AI developers will be better positioned by developing bespoke solutions for clients.  The least protected will be the commoditized real estate developers of data centers. 

We hold a positive outlook for Hyperscalers and we see a market-weight allocation as sensible. We do not think we are smarter than the market.  Nor do we think this is a time to pull back from market exposure. 

We do think OCIOs should be thinking carefully about the AI industry stack.  That suggests that OCIO real estate teams should avoid data center REITs, OCIOs’ underlying managers should treat second-tier Hyperscalers as highly speculative, and that venture investing to chase AI opportunities as a theme should be avoided.  Instead, OCIOs should focus on venture managers only if the OCIO has strong track records and long-term relationships with the venture managers, or otherwise avoid most venture investing.

We would be pleased to discuss our analysis further.

Chris Cutler CFA

cutler@manageranalysis.com

917-287-9551

[1] OpenAI, Anthropic, and the others are all doing basically the same thing. There are different choices made technically, in terms of training data, and market focus but at present there’s no indication that any one has an insurmountable lead.

[2] Also, historically in tech the companies have many patents but don’t sue each other. The patents are nearly always for defensive purposes. You stay ahead by investing more and wiser in R&D than your competitors.

[3] See also: https://www.npr.org/sections/planet-money/2025/02/04/g-s1-46018/ai-deepseek-economics-jevons-paradox.

[4] Did hyperscalers invest in AI ventures because they wanted returns on their investments, or to drive more traffic to their data centers? For the latest on Musk vs. Open AI et al see https://www.geekwire.com/2026/the-microsoft-openai-files-internal-documents-reveal-the-realities-of-ais-defining-alliance/

Private Credit Strategies Call For Deeper Diligence on Asset Holdings

Posted on by Chris in Briefings, Uncategorized

On Tuesday July 22nd, I spoke at Opal Group’s Public Funds Summit 2025 on “Private Credit,
Debt, and Direct Lending: A Developed Asset Class For Pension Funds” alongside Reid
Bernstein [Amerin Partners], Mike Fang [Maryland State Retirement and Pension System],
and Molly Whitehouse [Newmarket Capital], moderated by Lindsay Powers [NEPC]. A big
thank you to Opal Group for bringing this very talented panel of private credit experts
together, to speak to the many public pension plan officials attending this Summit.

Assessing credit strategies has always been one of my favorite professional endeavors, and
the variety of private credit strategies now available offers institutional investors many ways
to seek attractive returns. Like many of my peers, I have found some compelling private
credit strategies that I think are relatively insulated from most economic downturns. We
have analyzed many of these strategies for our clients, and they have helped my diligence
clients achieve excellent results.

Knowing what to look for is important for analyzing any alternative investment strategy, and
particularly so for private credit strategies. The laws of economics did not evaporate when
investors started making allocations to private credit: Investors would be misleading
themselves to target returns of 10% to 20% net-of-fees, expenses, and borrowing costs,
while overlooking vexing operational risks, illiquidity premia, credit and leverage exposures,
and structural considerations. Apparently smooth return streams in private credit also belie
its nascent volatility: Publicly traded BDC analogs of private credit strategies [like one of
my favorites, GBDC] often exhibit annualized volatility as high as equity market volatility,
albeit with much more mean reversion. Record-low spreads on high yield bonds are
encouraging institutional investors to allocate more into private credit, helping to compress
returns, so the return outlook presented by managers to investors today may not be what
they can achieve in the future, even if credit performance is strong.

One of the gravest oversights I have seen is investors not fully appreciating that many of the
protections present with other strategies are simply ineffective for private credit strategies.
I will highlight one key consideration: we cannot rely on auditors to assess valuations of
private credit holdings reliably, much less validate that the assets even exist. In many cases,
no clear comparables exist to help value debt of private borrowers, and auditors often rely
disproportionately on the honesty of the private credit manager to mark their holdings
appropriately. While auditors should take an additional step of assessing the
creditworthiness of a private credit fund’s underlying borrowers, this onerous step is often
missed or glossed over. The example of the $2 billion failure of Bridging Finance is
impressive not just for the brazen misuse of investor capital causing losses of about 65%,
but also for the apparent oversight of KPMG and E&Y as auditors to uncover this major
fraud over many years:
https://canadianbusiness.com/ideas/what-happened-to-bridging-finance-david-natashasharpe/.

We always encourage investment consultants and OCIOs to take a deep dive in private credit
fund diligence, and to allocate proportionately more resources to review these managers’
individual investments. Private credit managers should offer, subject to a reasonable NDA,
full access to review their investment memoranda, and means to validate the existence and
performance of their funds’ assets from original, independent sources—including by
conducting verification calls with some borrowers directly. Relying on audit reports is not
su􀆯icient, but using a sensible sampling approach to help validate asset valuations and
existence could be sufficient. If you encounter resistance, then I would advise you not to
pursue an investment with that manager. I’ve had many very successful diligence reviews of
very talented private credit managers, and I’ve also had a small number of opaque private
credit managers terminate my reviews of them because I insisted on reviewing sufficient
information, for which I am very proud.


When we evaluate investment consultants and OCIOs, we are particularly focused on
whether these advisers have committed sufficient talent and resources to evaluate the
private credit strategies they recommend to their clients. If your analysts recommend SRT
[structured risk transfer] strategies, we expect that they’ll have a firm understanding of
correlation trading models and that they at least review the SRT reference credit portfolios,
steps we often have seen investors skip. If you invest in trade credits, bridge loans, or
litigation financing, we want to know that you understand enough about those businesses to
ensure that the loan terms make sense for them, as well as validating the existence of these
assets.

While we are very pleased with the development of private credit markets, we do raise
concerns about the rapid growth in private credit allocations. Mistakes in making private
credit investments can be very unforgiving: a portfolio of ten private credit managers
earning 10% net of fees could easily see several years of alpha vaporized by one
meaningful blowout. We would like to see institutional investors take steps to avoid
unpleasant surprises. We would also like investors to develop more rigorous opinions of the
performance of the underlying borrowers and industries selected by their managers. U.S.
middle market companies have yet to recover to their pre-COVID performance. Higher
interest rates, slower private equity exits, weaker earnings and sales growth outside of the
technology sector are harbingers of future performance challenges for private equity
investments.

What do we like? We have helped our clients to source and invest in several interesting
private credit strategies. Right now, we see a few excellent private credit managers lending
to sponsor-backed companies focused on “growth equity” companies, mostly in technology.
We expect that they will earn 10% to 15% per year, with one turn of leverage, provided that
they continue to uphold their underwriting standards. We are concerned about
compromising of credit underwriting standards at the very large “asset gatherers” in
private credit; we avoid them. Conversely, we are interested in seeing upcoming private
credit fund launches by very large insurance companies, which have decades of experience
in this market.

We also like some private credit strategies focused on securitization markets in residential
and commercial real estate markets, but we strongly advise that any investors have
resources to understand securitization markets before approaching this sector. We see
returns there ranging from 10% net with very little leverage, to 15% tax-free for one very
unusual but highly leveraged strategy. On the more conservative end of the markets, we
have seen AA-equivalent consumer securitization strategy that earns well over 2% above
SOFR.

Sophisticated investors have been embracing private credit markets for many reasons. We
encourage all participants to maintain exceptional standards of diligence when examining
private credit strategies. Doing so will help ensure that your institution is getting what they
think they are getting, while also reinforcing good conduct in this important market.

Chris Cutler CFA
President
Manager Analysis Services, LLC
cutler@manageranalysis.com
August 4, 2025

The Future of Private Wealth Management

Posted on by Chris in Uncategorized

On Wednesday I spoke on the CFA Institute’s panel “The Future of Private Wealth Management,” which is part of the CFA Institute’s “Navigating Wealth & Private Markets” series. At Manager Analysis we have been helping wealthy families navigate offerings of private banks, wealth advisers, and Outsourced Chief Investment Officer firms, all of which are now competing against each other in the HNW markets. We are also seeing sophisticated family offices becoming more discriminating in assessing the quality of investment ideas that their advisers bring.

Helena Eaton, CFA from Bedrock Advisers, Peter Went CFA of the CFA Institute, and I spoke on this panel about the rapidly evolving landscape of private wealth management globally. The rise of new sources of wealth from crypto and venture create new dynamics between these new clients and their private wealth managers, who should exercise adaptability and recognize that this “new money” may have entrepreneurial desires that deviate from more traditional portfolio construction. AI tools will materially improve wealth advisers’ internal processes and better prepare advisers for client meetings. Increasing availability of asset allocation and quantitative models, and alternative investment platforms, to smaller wealth advisers narrows the gap in investment capabilities between smaller and larger firms. Challenging private equity market conditions help private wealth managers distinguish themselves for their diligence and skill in selecting investments.

Despite these many changes, the private wealth adviser’s primary goal is unchanged: developing long-term relationships with clients. Having a comprehensive understanding of their goals and desires, and then aligning the client’s portfolio with those goals and desires remains the central role for successful private wealth managers.

Navigating wealth & private markets series — The future of private wealth management

cfainstitute.org

Asset Manager OCIOs Face Conflict Questions from Search Consultants

Posted on by Chris in News Excerpts, Uncategorized

by Sam Heller | FundFire April 17, 2023 [Manager Analysis Services strongly prefers conflict-free OCIO models] – OCIOs are not blind to the concerns around their investment strategies, said President of Manager Analysis Services Chris Cutler. Many of the coverage teams at OCIOs will work with clients to avoid these conflicts altogether, he added.

“There are many very high-quality coverage teams at those firms,… and they proactively avoid any conflicts,” he said. “I’ve seen these cases where they have already avoided all the internal products just because they don’t want these conflicts.”