info@meradia.com
.svg.png){kind=small}
The first paper in this series examined the questions executives inevitably face in the wake of major macroeconomic events:
- How quickly can we rebalance the portfolio to a new strategic posture without breaching liquidity, leverage, or regulatory constraints?
- How does a shift in emerging markets impact our portfolio over the next 24 hours?
Despite the frequency and significance of these moments, many asset owners still struggle to answer these questions with the speed and confidence required for the answer to matter. The challenge is rarely a lack of investment insight; it is the inability of existing investment data architectures, often designed around Strategic Asset Allocation (SAA), to support a true Total Portfolio Approach (TPA).
In Architecting for a Total Portfolio Approach, Jose Michaelraj explored why SAA native architectures fall short and proposed a pragmatic path forward:
“Rather than waiting for perfect data, Total Portfolio architecture layers calculated assumptions and reasonable models that sit on top of a book of record.”
Building on that foundation, this paper focuses on how asset owners can transform investment data into a competitive advantage. It explores why a Total Portfolio Approach–driven Investment Book of Record (IBOR) is critical to enabling timely, decision insights across the entire portfolio.
Investment Book of Record in Practice
Investment Book of Record remains an ambiguous and often contentious concept among asset owners. Definitions vary widely, and implementations differ even more. To establish a common foundation, Meradia defines IBOR as:
“A data set that represents the investment view, persisted across time with appropriate controls to enable cross‑functional use cases.”
In simple terms, an IBOR should not only show what the portfolio holds, but also preserve the context required for multiple teams to act on that information consistently.
In practice, an IBOR is shaped by the decisions it is designed to support. For many asset managers, this means a trade‑date investment view that enables active portfolio management and reporting. For asset owners operating under a Strategic Asset Allocation model, however, the reality is often quite different.
These firms typically maintain multiple IBORs, each aligned to a specific asset class, embedded within distinct systems, and optimized for local needs. While sufficient for asset‑class management, this structure reinforces silos that limit the firm’s ability to develop a coherent, timely view of the total portfolio.
Total Portfolio Approach Driven Investment Book of Record
A Total Portfolio Approach fundamentally challenges the traditional IBOR, demanding an IBOR designed to support decision-making at the enterprise level. In a TPA context, IBOR design is driven by use cases such as factor-based risk management, liquidity forecasting, and responsiveness to macroeconomic events. These use cases are inherently asset class agnostic and require consistent data standards across both public and private investments.
One of the most persistent challenges is integrating public and private assets with differing valuation cadences. Public markets offer frequent, observable prices, while private asset valuations are often delayed or stale. A cross-asset IBOR cannot allow these gaps to distort the total portfolio view. Instead, it must incorporate reasonable assumptions and modeling techniques to maintain continuous coverage, prioritizing timeliness and completeness over exactness and precision. In this environment, coverage and speed become imperative, while perfection deliberately takes a back seat.
However, even a robust, cross‑asset IBOR may be insufficient for certain Total Portfolio Approach use cases. Liquidity analysis is a prime example. Traditional IBORs are constructed from an asset‑centric perspective, with investment obligations such as unfunded commitments, typically outside the core investment view.
Liquidity Management
Answering liquidity‑related questions requires more than visibility into funded positions. It requires an integrated, dynamic view of investment obligations, the assets that give rise to them, and the funding mechanisms intended to meet those obligations.
Consider the following question: How is the overall performance of my portfolio impacted by the opportunity costs associated with liquidity management?
A traditional IBOR cannot answer this because it is not designed to link investment decisions to their associated liquidity requirements, nor to adapt as underlying assumptions change.
Here is a practical example. An asset owner commits $10 million to a private equity fund, of which $1 million remains unfunded. Based on an initial forecast of capital call timing, the investment team designates $1 million of highly liquid public equities as the preferred funding source. To ensure readiness, capital is intentionally held in a lower‑return, lower‑risk asset rather than allocated to higher‑conviction opportunities elsewhere in the portfolio.
Over time, assumptions and market conditions change. Capital call expectations may shift as deal pacing slows, market volatility increases, or financing conditions tighten. The originally designated liquidity buffer may no longer be required at the same scale or within the same time horizon. Alternatively, stress scenarios may indicate that a larger buffer is needed, or that a different funding source would be more efficient.
In a traditional IBOR, the funded private equity position is visible, and the unfunded commitment may be tracked separately. However, the linkage between the unfunded commitment, the liquid assets held to fund it, and the evolving assumptions that govern that relationship are not captured. The IBOR shows the assets, but not why they are held, what obligation they support, or how that relationship should change as forecasts evolve.
As a result, decision makers cannot continuously reassess opportunity costs, adjust liquidity strategies, or understand the true performance impact of liquidity management at the total‑portfolio level.
Macroeconomic Events
Many Total Portfolio Approach use cases challenge investment tagging and classification frameworks. Conventional IBORs rely on standard classifications such as industry, geography, and currency. While useful for reporting, these views often fail to capture how risk and exposure emerge during real market events.
Consider the question: How exposed is the portfolio to a disruption in the Strait of Hormuz?
A purely geographic view would focus on assets physically located in the region. However, the economic impact would extend well beyond those holdings, affecting assets such as airlines facing higher fuel costs or inflation‑sensitive exposures elsewhere in the portfolio.
A traditional IBOR can report where assets are located, but it cannot easily express these broader, event‑driven relationships. A TPA‑driven IBOR instead supports use‑case‑driven exposure views, allowing assets to be grouped based on the specific risk being analyzed rather than fixed classifications alone.
Interestingly, this presents a natural use case for AI in portfolio management. By analyzing historical market behavior and volatility patterns, AI‑driven models can help identify which assets exhibit sensitivity to specific macro factors and dynamically apply exposure tags as conditions evolve.
| Market Classification | Macroeconomic events | |
| Funded Positions | Traditional IBOR | TPA-driven IBOR |
| Liquidity-linked funded positions | TPA-driven IBOR | TPA-driven IBOR |
Conclusion
A Total Portfolio Approach places different demands on investment data than asset class oriented operating models. Supporting timely, portfolio-level decisions, therefore, requires an IBOR that extends beyond a record of funded positions. Instead, a TPA-driven IBOR emphasizes consistency across asset classes, explicit modeling of assumptions, and the ability to represent obligations and event-driven exposures alongside assets.
Without this shift, firms risk building portfolio views that remain analytically impressive but operationally incomplete when markets move quickly.
Upcoming Conversations
Meradia’s next article in the Total Portfolio Approach series focuses on the notional portfolios and analytics required to enable effective total portfolio analysis. The final piece highlights asset owner journeys, illustrating different paths to the same outcome shaped by each firm’s operating structure and goals.
Download Thought Leadership Article Process Design and Change, Solution Design, System Rationalization Front Office & Portfolio Management, Middle & Back Office Optimization, Performance, Risk & Analytics Asset Owner, Endowments & Foundations, Family Offices, Pension Piers Hansen