We work closely with clients to make our analytics and technology fit their investment process. That can mean tailoring portfolios, benchmarks and objectives, extending asset coverage, integrating with existing systems, or developing new capabilities around a specific investment problem.
For a select group of institutional investors and partners, we also undertake joint research and development projects led directly by our founding team. Examples include designing scenarios around a specific portfolio, reviewing capital market assumptions ahead of a strategy decision, and reviewing benchmark-relative allocations.
Every project runs on the same underlying engine as our core technology, so bespoke work remains consistent with the institution's analytical approaches. The examples below outline how we combine the platform, our research and close client collaboration to solve specific questions.
Modern CMAs
Benchmarking Capital Market Assumptions
An investment team wanted an independent reference point for its existing Capital Market Assumptions and a clearer way to understand where its internal views differed from current market pricing.
We benchmarked the team’s assumptions against our market-implied expected returns and decomposed the differences into their underlying valuation and economic drivers. This helped separate deliberate investment views from methodological differences, giving the team a more credible and transparent basis for challenging its assumptions, defending them in investment committee discussions and explaining why its views differed from the market.
Scenario Lab
Scenario analysis and portfolio construction
An investment team wanted to develop a set of key upside and downside scenarios and understand how each could propagate through the portfolio. The objective measure potential losses, and to understand which exposures were driving the outcomes and what changes to the asset allocation could improve resilience or preserve upside.
We worked with the team to construct the scenarios around their key risks and narratives, using the Scenario Lab to carry those assumptions consistently across asset classes and into portfolio outcomes. This allowed the team to compare alternative allocations under each scenario and identify practical portfolio changes that could improve the balance of risks, with a clear rationale that could be taken into investment committee discussions.
ATLAS Platform
Making total portfolio decisions
A portfolio team wanted a common framework for evaluating opportunities across a broad range of asset classes while balancing several measures of success: achieving its long-term CPI-plus objective, remaining competitive with peers and managing performance relative to a regulatory benchmark linked to its strategic asset allocation.
We worked with the team to bring expected returns, risk, benchmark-relative analysis and portfolio construction into a single decision process in ATLAS. This allowed the team to compare opportunities on a consistent basis, construct appropriate funding portfolios and test how allocation changes affected expected return, performance relative to the regulatory benchmark and the likelihood of meeting its long-term objective.
ATLAS Platform
Managing liquidity across a multi-year horizon
A corporate pension team wanted to allocate liquid capital across external managers while retaining sufficient flexibility to meet cash and liquidity needs over a multi-year horizon. The challenge was to balance expected return against the timing and uncertainty of future outflows, rather than treating the liquid portfolio as a single static allocation.
We worked with the team to evaluate manager allocations alongside horizon-specific return assumptions, liquidity requirements and potential cash-flow paths. This allowed the team to test how different allocations could support near-term funding needs while keeping more capital invested where the horizon allowed, and to understand the trade-offs between return, liquidity and portfolio resilience over time.