Autonomous decision-making with AI.
TOWA is an autonomous engine that recalibrates your risk tolerance as the market changes. We support the construction of a stable revenue base regardless of location.
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TOWA is an autonomous engine that recalibrates your risk tolerance as the market changes. We support the construction of a stable revenue base regardless of location.
Start your analysis for freeProfessionals who make asset and business decisions remotely are constantly faced with time differences and information constraints. Delays in decision-making turn into lost opportunities.
Even if the market changes suddenly, it will take time to check and recalculate, and you will miss the optimal timing.
If multiple positions and indicators are monitored in parallel, judgment criteria will become individualized and accuracy will decrease.
Continuous monitoring is itself physically difficult when you're on the move or in a time zone environment.
Learn your individual decision-making patterns and continually redefine your risk tolerance. The foundation is predictive modeling based on behavioral data rather than fixed rules.
Compare past decision history and market reactions to quantify the individual's acceptable swing range.
When market fluctuations are detected, the tolerance threshold is updated instantly. No human intervention required.
Based on the updated standards, we will recalculate and present the balance between expected return and risk.
It shows the actual state of the process, not a hypothesis or performance. The logic of TOWA operates in the following steps.
Integrate and normalize market data, trading history, and external metrics for analysis.
A statistical model classifies sources of variation and matches them against historical tolerance data.
Immediately reflect proposed adjustments within defined tolerances. Processing speed is in milliseconds.
This configuration allows continuous monitoring and adjustment even when you are traveling or in an environment with time differences.
Keep portfolios spanning multiple currencies and markets unsupervised while on the move. Recalculation of tolerances is completed on the engine side, reducing the frequency of opening the terminal. Even if you stay in different time zones, your standards of judgment will not change.
Learn each client's risk tolerance individually to ensure the accuracy of your recommendations. The variable factors shown by the predictive model can be used as evidence before the interview. This makes it possible to provide explanations that do not rely on personal rules of thumb.
The fee structure varies depending on the scale of use and the number of assets to be analyzed. Details will be provided at the pre-implementation hearing.
Input data will be processed in an encrypted state and will not be provided to third parties. The location and scope of data management will be clearly stated at the time of contract.
If an event exceeding the normal fluctuation range is detected, the engine is designed to temporarily stop automatic adjustment and prompt for human confirmation. It is a safety mechanism to prevent excessive automatic reactions.
The learning model is revalidated periodically. Updated content is recorded as a change history and can be referenced by users at any time.