Wie sicher sind unsere Finanzdaten?

Kontodaten werden ausschließlich über verschlüsselte Schnittstellen übertragen und nicht an Dritte weitergegeben. Zugriff auf Analyseergebnisse erhalten nur von Ihnen autorisierte Personen.

Wie genau sind die Modelle wirklich?

Jedes Modell wird vor dem Einsatz gegen historische Daten mehrerer Marktphasen getestet. Wir veröffentlichen keine pauschalen Erfolgsquoten, da Ergebnisse von Marktbedingungen und individuellem Kapitaleinsatz abhängen. Backtesting-Berichte zu einzelnen Strategien stellen wir auf Anfrage zur Verfügung.

Wie lange dauert die Einführung?

Die technische Anbindung ist in der Regel innerhalb weniger Tage abgeschlossen. Die erste belastbare Analyse liegt vor, sobald ausreichend historische Kontodaten vorliegen, üblicherweise nach wenigen Wochen laufender Erfassung.

Teilpragur data analysis visualization for corporate liquidity

For SMEs and those responsible for finance

Liquidity analysis based on historical data, not gut feeling

Teilpragur evaluates your account data and capital flows in real time and shows how much unused capital is in your company. Each recommendation is based on strategies that have been back tested over multiple market cycles.

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Initial situation

Manual liquidity checking costs time and returns

Many companies manage their cash reserves through spreadsheets and gut decisions. That's enough as long as nothing goes wrong. It is not enough to allow capital to work actively and in a risk-conscious manner.

Teilpragur replaces this routine with a model that continuously evaluates account movements, payment cycles and market conditions. The result is an assessment of how much liquidity you actually need and how much you could invest.

Account statements are usually only evaluated at the end of the month, not on an ongoing basis.
Spreadsheet-based planning rarely takes seasonal payment fluctuations into account.
Decisions about cash reserves are often based on experience rather than data.
Risks are often only recognized when they have already occurred.

Teilpragur team analyzing financial data in office

Methodology

Back-tested models instead of aerial forecasts

Each recommendation is checked against historical market data before delivery. Only when a model remains stable over several cycles is it released for customer accounts.

Backtesting over market cycles

Strategies are tested against data from different interest rate and economic phases before they are used.

Real-time risk assessment

Liquidity requirements and market risk are recalculated daily, not once every quarter.

Transparent decision logic

Each recommendation shows which data points and assumptions led to it.

Scalable portfolio models

The analysis adapts to company size and capital volume without changing the methodology.

The underlying models are regularly validated against new market data. Deviations between expected and actual development are included in the next calibration. This means the methodology remains comprehensible and verifiable, rather than being based on a one-off assumption.

Process

Three steps from account connection to implementation

The process is deliberately kept lean. You retain control over decisions and approvals at every step.

Integration

Accounts and payment data are connected via a secure interface. Existing accounting systems remain in use unchanged.

Analysis

The model calculates liquidity requirements, payment cycles and available surpluses. Results are presented with justification, not just as a number.

Implementation

You will receive concrete allocation suggestions. The approval of each action remains with you or your finance team.

Use cases

Where the analysis specifically begins

Scenario 1

Optimize cash reserves

The majority of companies hold more liquidity than is necessary for ongoing operations, usually out of caution. Teilpragur calculates the actual minimum requirement based on payment cycles, seasonality and open liabilities. The remaining surplus can flow specifically into low-risk, back-tested strategies instead of sitting in the business account without interest.

Liquidity buffer Calculated from 12 months of payment history, not flat rates.

Scenario 2

Identify risk early

Market changes do not immediately affect every position in the same way. Ongoing risk assessment reports deviations as soon as volatility or correlations within the portfolio shift. This allows positions to be adjusted before a loss occurs, not after.

Risk signal Daily recalculation based on current market data.

Questions & Answers

Transparency on data, methodology and introduction

How secure is our financial information?

Account data is only transmitted via encrypted interfaces and is not passed on to third parties. Only people authorized by you have access to analysis results.

How accurate are the models really?

Each model is tested against historical data from multiple market phases before use. We do not publish blanket success rates as results depend on market conditions and individual capital investment. We provide backtesting reports for individual strategies upon request.

How long does the introduction take?

The technical connection is usually completed within a few days. The first reliable analysis is available as soon as sufficient historical account data is available, usually after a few weeks of ongoing recording.