AI-supported decision optimization
Wachstützung links your financial data from multiple sources into a unified dashboard and uses predictive models to derive concrete recommendations for action - for decisions in real time instead of based on outdated reports.
Preview: consolidated metrics from multiple accounts in one view – liquidity, risk exposure and return potential at a glance.
The challenge
Account movements, market and transaction data are now generated at a pace that can hardly keep up with manual evaluation. Many small and medium-sized companies continue to manage liquidity using spreadsheets and individual account statements, which only reflect the current status with a delay.
It is in this gap between data collection and interpretation that the real costs arise: capital remains unused, risk concentrations are recognized too late, and short-term investment opportunities are lost before an informed decision is possible.
Features
Accounts, depots and trading venues from different providers are brought together in a consolidated view. Liquidity, positions and risk metrics are visible in one place, regardless of the original data source.
Machine learning models evaluate historical patterns and current market data to estimate probabilities of liquidity shortages or price movements. The output is comprehensible scenarios, not blanket forecasts.
Deviations from defined thresholds – for example in concentration risks or volatility – are continuously recorded and reported so that countermeasures can be initiated before a loss occurs.
Evaluations of liquidity status, portfolio development and risk indicators are created systematically and are available without manual compilation effort. The underlying infrastructure is designed to be scalable.
Methodology
Bank details, trading venues and internal accounting systems are connected via standardized interfaces. The raw data is cleaned and converted into a uniform format.
Algorithms identify connections between liquidity trends, market movements and seasonal effects. Abnormalities are marked and compared with reference values.
Prioritized recommendations are derived from the recognized patterns - for example, for reallocating liquidity reserves or adjusting asset allocation. Each recommendation is documented with the underlying database.
About the platform
Wachstützung was developed to give small and medium-sized companies access to analytical tools that were previously reserved primarily for institutional investors. The focus is on connecting data sources that are viewed separately in everyday life: bank accounts, trading venues and accounting.
Every recommendation from the platform is comprehensibly justified and can be traced back to the underlying data points. Users retain control over every decision - the platform provides the basis for analysis, not the final authority.
Use cases
A craft business with several branches previously managed liquid assets using monthly account statements, which only made surpluses visible after a delay. With Wachstützung, daily liquidity levels from all branch accounts are automatically aggregated. Capital that is not needed in the short term can be specifically reallocated into interest-bearing investments instead of remaining unused in a current account.
An investor with positions on multiple trading venues lost track of the actual concentration of individual asset classes. The consolidated view of
Technical basis
Request a non-binding system audit and receive an assessment of where there is unused potential in your existing data.
