TFinance analyzes market data in real time and applies backtested algorithms to build family wealth in a structured and low-risk way. You get comprehensible results instead of guesswork.
Request analysis accessThe platform combines three core processes that together enable a strategy without manual administration effort.
Our models continuously evaluate global market data and identify patterns that would be difficult to detect through manual observation.
Each strategy is tested against historical market phases over several decades before it is used in practice.
Automated adjustments respond to volatility, eliminating the need to manually adjust your portfolio to daily market movements.
TFinance was developed for people who combine professional and family obligations with the desire to build wealth in a structured manner. Instead of daily market observation, you get a system that makes and documents decisions based on tested models.
The process follows a fixed sequence so that every decision is based on the same review criteria.
Macro data and market signals from various sources are brought together and structured in a unified model.
Machine learning processes identify optimization potential within defined risk limits.
The validated strategy is implemented automatically and continuously monitored against current market data.
We rely on comprehensible testing procedures instead of assessments. Each strategy is continually tested against a benchmark and against its own historical backtest model.
| Key figure | Static portfolio strategy | AI-optimized strategy (backtest) |
|---|---|---|
| Rebalancing frequency | Annually, set manually | Continuous, data-based |
| Reaction to volatility | Delayed, after consultation | Automated, almost in real time |
| Model testing period | Mostly viewed in the short term | Multi-year historical backtest |
| Documentation of decisions | Partially recorded manually | Completely, automatically logged |
Presentation of the methodological differences between static portfolio management and the AI-powered approach of TFinance. Specific performance depends on the individual investment horizon and risk profile.
After the initial setup, the system works autonomously. An occasional look at the monitoring log is usually enough to understand the progress.
Predictive models do not provide guarantees, but rather statistically tested probabilities. That is why every strategy is coupled with risk management that is intended to limit losses in the event of unexpected market movements.
The approach is designed for compound interest and stability over several years, not short-term speculation. This corresponds to the time horizon that many families set for building wealth for the next generation.
You will receive an analysis of your existing asset list based on our predictive models - as the basis for a non-binding consultation.
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