AI-Guided Capital Deployment
Cedar Fundhaven applies predictive data modelling to identify favourable market entry points for surplus business cash, then executes a disciplined, automated dollar-cost averaging strategy within parameters your finance team sets.
The Timing Gap
Sustained inflation erodes the real value of cash reserves held in standard business accounts, even where nominal balances appear stable. Many SME finance teams are aware of this, yet hesitate to act because deploying capital in a single lump sum exposes the business to whatever conditions happen to prevail on that particular day.
This is the timing gap: the distance between knowing that idle cash should be put to work and having the operational capacity to monitor markets closely enough to choose sensible entry points without diverting attention from core business activity.
Conceptual illustration of fluctuating entry conditions over time. Not derived from live client data.
Core Technology
Three components work together: a predictive layer that reads conditions, an execution layer that acts within limits, and a mitigation layer that constrains downside. None of them operate on guesswork.
The platform ingests macro indicators, interest rate trajectories, and short-term volatility signals to build a rolling assessment of market conditions. This is referred to internally as predictive liquidity modelling: an estimate of how favourable current conditions are for deploying capital relative to recent history, rather than a forecast of future prices.
Rather than committing capital in fixed, evenly spaced instalments, the execution engine adjusts the size and timing of each tranche according to current volatility. In calmer conditions, allocations proceed on a steadier schedule; during periods of elevated volatility, tranche sizes are reduced and spaced further apart, a method the platform calls volatility-weighted entry.
Every account operates within pre-agreed exposure ceilings, maximum single-tranche size, and a daily deployment cap. If market conditions move outside the bounds your business has configured, the system pauses deployment automatically and flags the position for review, rather than continuing to allocate capital unattended.
Methodology
The platform is designed to be inspected, not trusted blindly. Each stage below produces an output your finance team can review before capital moves.
Macro-economic releases, interest rate data, and market liquidity signals are pulled from established data providers on a continuous basis and normalised into a consistent internal format.
The predictive model scores current conditions and filters out noise, surfacing only signals that meet a minimum confidence threshold before they are allowed to influence execution.
The AI suggests an entry window and tranche size; the execution system then acts only within the risk parameters your business has pre-set. The AI does not override your limits — it operates inside them.
Strategic Outcomes
These are the operational effects the methodology is built to produce. They describe process improvements, not guaranteed financial results.
Allocation Efficiency
Capital is released in proportion to prevailing volatility rather than on a fixed calendar, reducing the likelihood that a full allocation lands during an unfavourable window.
Risk Reduction
By spreading entry across multiple tranches governed by pre-set limits, the strategy lowers reliance on any single day's market conditions compared with a lump-sum approach.
Operational Time
Finance teams no longer need to track markets daily to decide when to act. Oversight shifts from constant monitoring to periodic review of system activity and parameters.
About Cedar Fundhaven
Cedar Fundhaven was built on the premise that the methods used by institutional treasury desks to manage entry risk should be accessible to smaller businesses, without requiring an in-house quantitative team.
The platform combines established market data infrastructure with a predictive model and a rules-based execution engine, giving finance directors a documented, repeatable process for deploying surplus cash rather than an ad-hoc decision made under time pressure.
Frequently Asked Questions
Data in transit is encrypted using TLS, and data at rest is encrypted within our storage provider's infrastructure. Access to account configuration and execution parameters is restricted to authorised users on your account, with activity logged for audit purposes.
Most businesses complete onboarding, including account verification, risk parameter configuration, and connection of funding sources, within one to two weeks. Timelines vary depending on internal approval processes on the client side.
Yes. Deployed and undeployed balances remain under your business's control. Withdrawal requests are processed according to the standard settlement timeframes of the underlying custodial and execution infrastructure, which are disclosed during onboarding.
Get Started
Replace ad-hoc cash deployment decisions with a documented, parameter-driven process. A member of our team will walk through the methodology and configure initial risk settings alongside your finance function.