Finance / Our flagship
Financial intelligence beyond the consolidated number.
Counterfold builds custom financial data intelligence around the decisions of family offices, funds, management companies and banks. Connect cash, commitments, positions and operational evidence, then trace a result to the records and assumptions behind it.
Family offices: entity-level liquidity
A group may hold sufficient cash while a particular legal entity cannot meet a capital call within its permitted funding routes. Custodian exports, account restrictions, currency balances and settlement dates belong in the same review.
A first workflow can reconcile positions and commitments, separate available cash from noncash valuations, and compare timing scenarios. The output is a reviewable cash path and a decision brief, with transfer authority kept separate from economic need.
Funds and ManCos: a review that can be reproduced
Administrator, depositary and internal risk records can describe the same exposure differently. Start with a recurring oversight question such as valuation exceptions, subscription and redemption pressure, settlement delays or service-provider dependencies.
We scope the data model, source reconciliation, exception ownership and approved scenario calculations. The responsible control functions retain ownership of assumptions, regulatory interpretation and acceptance.
Banks: connect an issue to its dependencies
Counterparty, collateral, treasury and operational records can be connected around a defined question. A workflow might trace a settlement delay to funding needs or assemble evidence about a critical third-party dependency.
A bank engagement starts with data classification, access boundaries and the accountable business owner. It may require more extensive procurement, security and domain review than a small demonstration. Timelines follow that scope.
What the first pilot delivers
- A source inventory, entity map and explicit definition of available data.
- Reconciliation rules with exceptions and evidence lineage.
- A deterministic baseline and agreed scenario inputs.
- A review interface, decision brief and measurable acceptance criteria.
- A documented operating boundary covering access, approvals, retention and support.
Explore a working example
Our public Icarus liquidity demonstration uses three invented entities and five fixed scenarios. In the combined stress, one entity has a €60,000 buffer shortfall for ten days even though the group retains over €1 million. A separately permitted €60,000 transfer removes that simulated breach.
The example is a working deterministic model with synthetic records. It is not a client case study, investment advice or evidence of a validated production deployment.
Practical answers
Questions before the first conversation.
Do we need to send real portfolio data for the first discussion?
No. Start with the decision, source types and constraints. The public example uses invented records. Any client sample follows agreed access, confidentiality and processing arrangements.
Does an AI model calculate or authorise transfers?
The public demonstration uses deterministic calculations and a fixed brief template. It makes no payments. In a client build, calculations, AI interpretation and authority to act are separately designed and validated.
How is a finance pilot priced?
The estimate follows discovery of the data, integrations, users and acceptance criteria. Engineering, hosting, model usage and any legal or specialist validation are identified separately. There is no universal licence price for these custom engagements.