Structuring Desk · FX Derivatives

Institutional FX risk transfer.
Engineered for the middle market.

J. López Cubas operates a tokenized structuring desk that aggregates wholesale FX derivatives and distributes fractional hedging positions to corporates whose exposures fall below traditional institutional minimums. The platform delivers bank-grade pricing and execution at a fraction of the cost.

Explore the platform
$1MWholesale contract
1,000Tokens at $1K each
30 bpsTotal spread
Δ ≈ 0Market risk for JLC

Platform Walkthrough

Trade lifecycle

A representative transaction from wholesale acquisition through settlement. The interactive panel below illustrates each stage of the structuring workflow. Adjust client notional amounts in stages 3 and 4 to model different scenarios.

JLC purchases a wholesale contract

Deutsche Bank sells JLC a EUR/USD 3-month forward for $1,000,000 notional at institutional rates. The minimum size for this market is $500K — no SME can access it directly. JLC aggregates demand.

Instrument
EUR/USD
3-month forward
Notional
$1,000,000
Institutional price
Wholesale rate
1.0850
Counterparty: Deutsche Bank
Why can only JLC do this? Banks require $500K+ minimums for OTC derivative access. An SME with $50K of exposure simply cannot enter. JLC aggregates demand from many SMEs to justify the institutional minimum, then distributes fractional positions.

Tokenization — 1 contract → 1,000 units

The $1M contract is divided into 1,000 standardized units of $1,000 each. The grid below reflects the current allocation across active counterparties.

Token pool — each cell represents 10 tokens
Available (800)
Counterparty A (80)
Counterparty B (120)
Analogy: A hotel with 1,000 rooms. The owner holds the building (wholesale contract). JLC is Booking.com — selling individual rooms (tokens) to different guests (SMEs) who each need only a portion of the capacity.

Counterparty A — Spanish exporter

A wine exporter with $80,000 in dollar receivables due in 90 days. Risk profile: appreciation of EUR against USD reduces euro-denominated proceeds. The client locks today's rate by acquiring tokens against the wholesale contract.

USD exposure
$
Editable · SELL direction · receivables in 3 months
Tokens purchased
80
Risk tier: Low · 1 token = $1,000
ComponentValueLogic
Wholesale rate1.085000Price obtained from Deutsche Bank
Base spread40 bpsJLC base margin
Risk adjustment (Low)−5 bpsEstablished client, strong history
Volume discount (1M–10M)−5 bpsLoyalty pricing
Total spread30 bps = 0.30%40 − 5 − 5
Retail rate guaranteed1.081745Locked rate for García
retail_rate = wholesale × (1 − spread_bps / 10,000) = 1.0850 × (1 − 30 / 10,000) = 1.081745 jlc_revenue = spread_rate × notional = 0.003255 × 80,000 = $260.40

Counterparty B — German importer

A machinery importer with $120,000 in dollar payables due in 90 days. Risk profile: depreciation of EUR against USD increases euro-denominated cost. The client locks today's rate by acquiring tokens against the same wholesale contract.

USD exposure
$
Editable · BUY direction · payables in 3 months
Tokens purchased
120
Risk tier: Medium · 1 token = $1,000
ComponentValueLogic
Wholesale rate1.085000Same underlying contract
Base spread40 bpsJLC base margin
Risk adjustment (Medium)0 bpsStandard client
Volume discount (10M–50M)−10 bpsHigher volume tier
Total spread30 bps = 0.30%40 + 0 − 10
Retail rate guaranteed1.088255Locked rate for Schmidt
retail_rate = wholesale × (1 + spread_bps / 10,000) ← BUY: worse rate = 1.0850 × (1 + 30 / 10,000) = 1.088255 jlc_revenue = spread_rate × notional = 0.003255 × 120,000 = $390.60

Risk dashboard

The structuring desk operates a delta-neutral book by construction. Opposing client flows offset within the same underlying contract; only residual exposure requires active hedging.

SELL side — Counterparty A
$80,000
80 tokens · exporter
BUY side — Counterparty B
$120,000
120 tokens · importer
Net delta — desk
$40,000
4.0% of contract — residual
Delta-neutral positionNet exposure: 4.0% of contract
Residual exposure management: Net delta is hedged via spot positions or absorbed by incoming opposing flow. With sufficient client volume, the matching engine prioritizes contracts with existing opposite-side demand, driving the book toward natural balance and minimizing hedging cost.
Tokens distributed
200 / 1,000
20% of contract placed
Pool remaining
800
Available for new clients

Settlement at maturity

At contract maturity, P&L is calculated against each counterparty's locked rate. Both clients obtained certainty regardless of market direction. The desk's revenue is captured at the point of sale, independent of outcome.

Desk revenue — this batch
$651.00
Captured at point of sale · Delta-neutral
Step 1 of 6

Platform Architecture

Capabilities

The platform automates the end-to-end workflow of an institutional structuring desk: wholesale sourcing, fractionalization, risk-based pricing, counterparty matching, and residual delta management.

Wholesale sourcing
Direct access to tier-1 bank liquidity for OTC derivatives across major currency pairs and standard tenors. Institutional minimums absorbed at the platform level.
Fractionalization
Each wholesale contract is divided into standardized units fully backed by the underlying position. Clients access exposure-sized portions without bearing the full institutional minimum.
Risk-based pricing
Dynamic spread calculation incorporating client risk tier, transaction volume, and tenor. Pricing transparent and consistent across counterparties.
Counterparty matching
Real-time matching engine pairs opposing flows (importers and exporters) within the same underlying contract, naturally reducing the desk's directional exposure.
Residual delta management
Net exposure after matching is hedged via spot positions or absorbed by incoming flow. The desk maintains a delta-neutral book by design.
Settlement & lifecycle
Automated settlement at maturity. Client P&L calculated against locked rates. Full audit trail and position reporting available throughout the contract lifecycle.
What this replaces: the workflow above traditionally requires a structuring desk, a sales team, a middle office, and a risk function inside an investment bank. The platform consolidates these into a single automated pipeline, allowing institutional-quality execution to reach clients that have historically been excluded from this market.

Commercial Model

Revenue architecture

The platform is structured as a non-directional intermediary. Revenue is generated through spread capture at execution, not through proprietary risk-taking. The desk is structurally agnostic to market direction.

01 — Spread capture
30 bps per trade
Wholesale liquidity sourced at institutional levels and distributed at risk-adjusted retail rates. The differential is locked at execution, independent of subsequent market movement.
02 — Volume aggregation
Wholesale → fragmented demand
A single wholesale contract serves multiple corporate clients whose individual exposures fall below institutional minimums. Aggregation is the platform's structural advantage.
03 — Delta-neutral matching
Δ ≈ 0
Opposing flows from importers and exporters offset within the same underlying contract. Residual exposure is managed via spot hedging. The book carries no directional FX risk.
Unit economics — representative contract
Wholesale notional: $1,000,000
Average utilization: ~80%
Captured spread: 30 bps on placed volume
Gross revenue: ~$2,400
Wholesale & infrastructure cost: ~$400
Net contribution: ~$2,000 per contract
Client value proposition
Mid-market corporates currently face three options: (i) bear unhedged FX risk; (ii) negotiate with a bank at 80–120 bps spreads contingent on credit lines and operational onboarding; or (iii) access the platform at 30 bps with no credit dependency, settling within minutes.
Scaling vector — instruments
Multi-asset
The fractionalization model extends to interest rate swaps, commodity forwards, and credit derivatives — any wholesale instrument with retail demand below institutional minimums.
Scaling vector — coverage
Multi-pair, multi-tenor
Parallel wholesale contracts across major currency pairs and standard tenors. Each contract operates as an independent revenue stream with its own matching pool.
Scaling vector — network
Compounding efficiency
Higher client volume improves matching efficiency, reduces residual delta, lowers hedging cost, and enables tighter spreads. The matching engine becomes more effective as the pool grows.
Summary: the platform delivers a function previously contained within investment bank structuring desks as a self-serve service to mid-market corporates that have historically been excluded from this market. It captures the same economic spread, with materially lower overhead, and is profitable on the first matched transaction.