Faster onboarding of tokenized commercial bank deposits accelerates the depletion of central bank settlement liquidity by driving higher transaction churn across the network. Without proportional replenishment flows, increased activity rapidly drains available balances. In this Play, illustrative data shows that On-Chain Settlement Liquidity falls from 38 to 3 at step 15 as onboarding speed increases.
Key takeaways
- Raising Tokenization Rate from 2 to 6 tokens per day reduces On-Chain Settlement Liquidity from 38 to 3 tokens at step 15.
- Increasing Replenishment Rate from 3 to 7 tokens per day boosts On-Chain Settlement Liquidity from 38 to 98 tokens at step 15.
- On-Chain Settlement Liquidity drains rapidly in this model when accumulated deposits generate more daily settlement churn than central bank injections replenish.
- System operators should evaluate daily settlement churn before expanding deposit onboarding to ensure reserve injections can maintain adequate buffer levels.
How fast does on-chain settlement liquidity drain?
A manager overseeing wholesale financial infrastructure faces a trade-off between expanding tokenized deposit volume quickly and preserving adequate central bank reserves for daily payment clearance. In this illustrative model, setting the tokenization pace higher leaves On-Chain Settlement Liquidity at 3 tokens at step 15 compared to 38 tokens in the baseline setting, whereas expanding the daily injection raises it to 98 tokens.
These figures represent an illustrative scenario designed to show how settlement churn scales against replenishment flows. Without balancing these two forces, rapid deposit onboarding can deplete settlement liquidity buffers faster than anticipated.
What happens when you adjust the policy levers?
The first lever is Tokenization Rate, which controls how many commercial bank deposit tokens enter the network each day. In the baseline setting, this lever is set to 2 tokens per day, leaving On-Chain Settlement Liquidity at 38 tokens at step 15. When this lever is increased to 6 tokens per day, the final liquidity drops to 3 tokens.
Early in the timeline, the difference appears small. At step 1, both paths hold 52 tokens in On-Chain Settlement Liquidity. By step 5, the baseline level reaches 56 tokens while the faster onboarding path slips to 48 tokens. By step 8, the faster onboarding setting drops to 33 tokens, showing that deposit accumulation accelerates liquidity outflow over time.
The second lever is Replenishment Rate, which governs daily central bank liquidity injections into the settlement pool. It begins at a baseline of 3 tokens per day, ending with 38 tokens in On-Chain Settlement Liquidity at step 15. Raising this lever to 7 tokens per day lifts the step 15 liquidity level to 98 tokens.
This injection immediately changes the trajectory of the settlement buffer. At step 1, liquidity reaches 56 tokens under the higher injection compared to 52 tokens in the baseline. By step 8, the higher injection path climbs to 87 tokens while the baseline holds 55 tokens, demonstrating sustained reserve accumulation across consecutive settlement days.
The card also has two more sliders. Onboarded Tokenized Deposits → Settle sets the size of the link from the Onboarded Tokenized Deposits pool to the Settle flow: when that pool gains or loses Deposit, Settle goes up or down by this amount, 0.2 in the baseline, adjustable from 0.01 to 1. On-Chain Settlement Liquidity sets how many tokens the settlement pool holds before step 1: 50 in the baseline, adjustable from 0 to 500.
How do deposits and liquidity interact in the model?
The model connects two primary asset tracks across daily settlement steps. Deposit Mint creates new tokenized commercial bank balances according to Tokenization Rate and feeds them into Onboarded Tokenized Deposits. As this deposit balance grows, it drives gross interbank payment activity.
Settlement demand pulls directly from On-Chain Settlement Liquidity, which empties into Gross Settlement Sink based on the volume of active deposits. Central Bank Injection adds fresh reserves into the settlement pool each day according to Replenishment Rate. When deposit growth outpaces daily central bank injections, the settlement pool drains.
What do these settlement results mean for liquidity planning?
These findings show that deposit onboarding speed exerts compounding pressure on central bank settlement buffers. In this model, expanding deposit onboarding triples the depletion pressure because each added deposit increases daily settlement churn. Planners looking to scale deposit tokenization must evaluate gross clearing demands before speeding up onboarding.
The results also demonstrate that replenishment flows can offset heavy payment churn if scaled early. When central bank injections outpace the daily gross settlement demand, liquidity reserves expand steadily even as transaction activity grows. Balancing these flows prevents sudden reserve shortfalls during high-volume periods.
What does the model leave out?
This model relies on several simplifying structural assumptions. Each step of Play represents exactly one business day of interbank settlement activity. Daily replenishment injections and tokenization flows occur at constant rates throughout the timeline without spontaneous fluctuations.
The diagram tracks two pools, two sources and one sink, using a proportional relationship between deposit volume and settlement drain. All initial values and flow rates are illustrative model parameters rather than real-world measurements. Real systems are more complicated than any model.
Where does the topic come from?
This playable model was inspired by the publication Isabel Schnabel: Central banks on-chain, published by the European Central Bank on 1 October 2026. The specific numbers, baseline settings and outcomes presented in this essay reflect the model's own illustrative scenario.
Can you test different onboarding and replenishment speeds?
You can explore these settlement dynamics directly by adjusting the levers in the playable model. Try setting Tokenization Rate to 4 or Replenishment Rate to 5 to observe how intermediate speeds influence reserve stability across fifteen settlement steps.
The parts of the model
The question it asks: How does the onboarding speed of tokenized commercial bank deposits affect the depletion rate of on-chain central bank settlement liquidity?
- Deposit Mint · Source
- Mints newly tokenized commercial bank deposits into the on-chain network each business day.
- Onboarded Tokenized Deposits · Pool
- Stores the accumulated volume of tokenized deposits active on the distributed ledger in tokens.
- Central Bank Injection · Source
- Supplies central bank wholesale liquidity replenishments each business day.
- On-Chain Settlement Liquidity · Pool
- Stores available central bank on-chain settlement liquidity buffers in liquidity tokens.
- Gross Settlement Sink · Sink
- Absorbs central bank liquidity consumed by daily interbank gross settlement churn.
- Tokenization Rate · Lever
- Sets the daily onboarding rate of commercial bank deposits in tokens per day.
- Replenishment Rate · Lever
- Sets the daily central bank liquidity replenishment injection in liquidity units per day.
Assumptions and limits
- Each step of Play represents one business day of interbank settlement activity.
- Gross Settlement Outflow increases proportionally with the stock of Onboarded Tokenized Deposits.
- All initial stock and flow values are illustrative.
A teaching model with illustrative values; each Play is a scenario, not a forecast.
Sources
- European Central Bank (ecb.europa.eu)
Topic source: European Central Bank.
About this model
Machinations makes these models with AI from a public source, and each one is a teaching scenario: its numbers are illustrative values chosen for the model, not measurements or forecasts. You can open this diagram in the Community to remix it and change it.