True Meritbanwick data visualisation representing unified crypto exchange analysis

Complexity managed through unified intelligence.

We built True Meritbanwick to consolidate holdings across exchanges into one data layer, so decisions rest on consistent, risk-adjusted information rather than scattered balances.

Most students holding cryptocurrency today are not short on opportunity. They are short on a single, coherent view of what they actually own. A position on one exchange, a smaller allocation on another, and a third account opened out of curiosity rarely combine into anything resembling a portfolio. Each platform presents its own interface, its own notion of risk, and its own version of performance.

The result is not recklessness but fragmentation. Decisions get made exchange by exchange, often late at night, often without the context that a unified ledger would provide. For someone balancing coursework, a part-time role, and a limited budget, this fragmentation carries a real cost: time spent reconciling screenshots instead of understanding exposure.

We think the more useful question is not which exchange to trust, but how to see across all of them at once.

Note: True Meritbanwick does not custody funds or execute trades on a user's behalf. It aggregates read-only data to produce a single analytical view.

One dashboard, built on predictive modeling.

True Meritbanwick connects to exchange accounts through read-only API access and maps every holding into a single, risk-adjusted view. The underlying model does not forecast price direction; it quantifies volatility, correlation, and concentration across the assets already held.

From that baseline, the system surfaces where a portfolio is overexposed to a single asset or exchange, and where diversification would meaningfully reduce drawdown risk. The output is a set of observations, not instructions.

Dashboard — Risk Overview
  • Portfolio volatility (30d)Moderate
  • Exchange concentration42% single venue
  • Correlation to BTC0.81
  • Risk-adjusted return (Sharpe-style)0.63
  • Rebalancing suggestionReduce by 8%

A plain-English account of the underlying logic

01

Aggregation

We connect to supported exchanges through official, read-only API keys. No withdrawal or trading permissions are requested at any point. Balances, trade history, and fee data are pulled on a scheduled basis.

02

Normalization

Each exchange reports data differently. Before analysis, figures are converted into a common currency basis and a shared time resolution, so a position on one venue can be compared fairly against another.

03

Risk Modeling

The model calculates historical volatility, drawdown patterns, and cross-asset correlation for the specific holdings in the account. It does not attempt to predict future prices; it describes the risk structure of what is already held.

04

Presentation

Findings are translated into the dashboard as plain metrics and short written observations, avoiding technical jargon wherever a clearer phrase exists.

Technical disclaimer: Outputs are informational and reflect historical and current data. They do not constitute investment advice and carry no guarantee of future performance.

Security brief: API credentials are encrypted at rest and in transit. Data processing takes place on infrastructure located within the EU, consistent with GDPR requirements applicable to users in Germany.

A student portfolio spread across three exchanges

A common starting pattern: a small holding opened on a first exchange, a second account used for a specific token, and a third kept for occasional transfers. Individually, each balance looks modest. Combined, concentration risk is often higher than any single screen suggests.

True Meritbanwick consolidated the view and flagged that 61% of total value sat on a single exchange, prompting a deliberate decision to redistribute rather than an accidental one.

Comparing fee structures before adding a fourth exchange

Before opening another account to access a specific asset, a user can review projected fee drag and liquidity differences inside the dashboard, rather than estimating manually across separate fee schedules.

The comparison showed a 0.4 percentage point difference in effective trading cost between two candidate exchanges over a simulated holding period, informing the choice made.

On risk, and what we will not promise

We built this platform because we were frustrated by dashboards that implied certainty where none exists. Cryptocurrency markets remain volatile, and no model, including ours, removes that volatility.

What a unified, risk-aware view can do is replace guesswork with a consistent reference point, so that decisions are made with full visibility into what is actually held.

Does True Meritbanwick require access to withdraw funds?

No. Connections use read-only API permissions provided by each exchange. Trading and withdrawal functions are never requested or enabled.

Is this suitable for a small starting portfolio?

The analysis scales with whatever is connected, including modest holdings. The value lies in visibility and risk context rather than portfolio size.

How is data handled under German and EU privacy rules?

Account data is processed on infrastructure located within the EU. Encryption is applied both in transit and at rest, in line with GDPR obligations.

Does the platform recommend specific coins to buy?

No. The model describes the risk and correlation characteristics of existing holdings. It does not issue buy or sell signals for specific assets.

Which exchanges are currently supported?

Support is limited to exchanges offering stable, documented read-only API access, prioritised by relevance to the platforms most commonly used by our current user base.

Begin with a clearer picture of what you hold.

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