Etoro AI Automatic — artificial intelligence-powered cash flow analysis dashboard

Predictive models tested on historical data for your excess cash flow

Etoro AI Automatic continuously analyzes your SME's available liquidity and offers documented allocations, based on backtesting and risk management rules defined with your financial department.

Analytical engine

A predictive engine designed for cash management

Three technical building blocks work together: predictive modeling, real-time analysis of positions, and a risk management framework applied before any recommendation.

Predictive modeling

Models trained on long series of market data

The engine relies on statistical models trained on extensive market histories. It identifies regularities in the behavior of liquid asset classes and adjusts its recommendations as market conditions change, without daily manual intervention from your team.

Each recommendation is accompanied by a summary of the assumptions made, so that your financial management can assess the logic before any decision.

What the model takes into account

  • Asset classes analyzedCash, short-term bonds, money market funds
  • Recalibration frequencyAccording to observed volatility
  • Human reviewWith each change of recommendation
Real-time analysis

Continuous monitoring of liquidity and alert thresholds

The dashboard updates at regular intervals during market hours. It tracks available liquidity, exposure by instrument and alert thresholds defined with your finance department, so that deviations from the initial plan are reported quickly.

Continuously monitored indicators

  • Liquidity positionPeriodic update
  • Exposure by counterpartyContinuously monitored
  • Threshold alertsConfigured by your team
Risk management

Risk limitation rules applied before each recommendation

Each proposed allocation is subject to rules defined in advance with your company: exposure ceilings per counterparty, maximum tolerated loss thresholds, and frequency of re-simulation in the event of a market shock. No recommendation is transmitted without going through this filter.

Applied control framework

  • Exhibition ceilingDefined by counterparty
  • Tolerated loss thresholdValidated with your company
  • Re-simulation in case of shockTriggered automatically
Methodology

The backtesting process, step by step

Before a strategy is proposed to a client, it is compared with historical data and then reviewed by a technical team. Here are the main stages of this control.

01

Data collection

Creation of historical data series specific to each asset class analyzed.

02

Retrospective simulation

The strategy is simulated over past periods, including contrasting market phases.

03

Stress tests

Tension scenarios are applied to observe the behavior of the model in unfavorable conditions.

04

Human review

An analyst reviews the results before making a recommendation available to clients.

Example of restitution structure (illustrative — report format, not a guaranteed result)
Scenario tested Simulated period Nature of the test Status
Figure ABull market cycleHistorical simulationDocumented
Figure BCorrection phaseStress testDocumented
Figure CStable rate marketHistorical simulationDocumented
Methodological transparency note: a historical return, even from rigorous backtesting, does not constitute a guarantee of future performance. The detailed methodology, including the data sources used, is communicated upon request to your financial department before any implementation.
Use cases

Three concrete applications for an SME

The same analytical foundations serve different needs, depending on the decision horizon and level of risk accepted by your business.

Cash

Excess cash management

Identification of the share of liquidity which exceeds current operational needs, and proposal of allocations adapted to a horizon of a few months.

  • Separation of operational reserve/surplus
  • Monitoring of minimum liquidity thresholds
  • Monthly report for financial management
Planning

Market development analysis

Provision of structured market data to support an expansion decision, without replacing your team's strategic analysis.

  • Macroeconomic context indicators
  • Rate sensitivity scenarios
  • Comparative restitution by period
Wallet

Optimization of the reserves portfolio

Adjustment of the distribution between liquid instruments according to the validated risk profile, with periodic re-simulation.

  • Diversification by counterparty
  • Rebalancing according to predefined rules
  • History of decisions preserved
About the process

A technical team, a documented method

Etoro AI Automatic was designed to meet the requirements of Swiss financial departments: traceability of assumptions, documentation of risk rules, and availability of a contact person for any methodological questions.

The platform does not replace regulated financial advice. It provides structured analysis that powers your business decision.

Learn more about our approach →
Etoro AI Automatic — team analyzing market data for cash management
Frequently asked questions

The technical points our customers check first

A selection of questions regularly asked by financial departments of Swiss SMEs before integrating the platform.

Where is my company data hosted?

The data transmitted for analysis is processed according to a framework defined contractually with each client. The precise hosting and storage arrangements are detailed in the contractual documentation provided before any implementation.

Can the platform integrate with our accounting tools and bank accounts?

The analysis can work from data transmitted manually or by connection to your existing systems, depending on the configuration chosen with your technical team. The scope of integration is defined on a case-by-case basis during the initial analysis.

What does backtesting on our data actually mean?

This means that the planned strategy is simulated over past market periods before being proposed. This step allows you to observe its behavior in different conditions, but it does not guarantee an identical result in future conditions.

How specific are the recommendations?

The model provides recommendations with a level of confidence and assumptions made. A human review takes place before any transmission to the client, in particular when market conditions go beyond the scenarios already tested.

Let's discuss the allocation of your excess cash

An initial analysis allows you to identify the portion of your liquidity available for allocation, as well as the risk framework adapted to your business. No commitment is required at this stage.