Steuruck Holdings – Analyst works with data-based investment strategies on the screen

Data intelligence for capital preservation in retirement

Steuruck Holdings combines historical market data with AI-supported analysis models to make investment decisions understandable and risk-aware - without speculation and without empty promises.

Backtesting over multiple market cycles Transparent methodology Human approval of every recommendation
Initial situation

Why classic portfolios reach their limits in retirement

Anyone who lives from their own capital carries a different risk than someone who is still actively earning income. A price decline at the beginning of the withdrawal phase has a greater impact than the same decline ten years later - an effect that experts refer to as “sequence of returns risk”. Classic buy-and-hold strategies rarely take this difference into account.

This is where Steuruck Holdings comes in: Instead of relying on blanket diversification, our system continuously evaluates market data and identifies phases of increased instability before they become clearly visible in the common key figures. The information derived from this does not replace advice, but rather supplements it with a data-supported perspective.

Steuruck Holdings – Evaluation of market data to assess risk in the investment process
Methodology

How the analysis works – in three steps

In this context, artificial intelligence is not an opaque mechanism, but a tool that processes large amounts of data faster than a single analyst could.

1

Data collection

The system continuously collects price, volume and volatility data from multiple market segments and compares it with historical patterns. The basis is publicly available market data, not internal insider sources.

2

Pattern recognition

A statistical model (machine learning) compares current market conditions with past situations of similar structure. This allows recurring risk patterns to be identified long before they appear in the headlines.

3

Risk assessment & recommendation

The recognized patterns result in a concrete assessment of the risk situation of the portfolio. The final decision always lies with you and your advisor.

Evidence

Historical backtests as a basis for trust

Before a strategy is used in the real portfolio, we check how it would have behaved in past market phases - including times of crisis with sharp price declines.

The backtests cover periods with different interest rate levels, recessions and recovery phases. The goal is not the highest retrospective return, but rather an understanding of how stably a strategy would have responded under changing conditions.

Historical results are a guide, not a guarantee for the future. Market conditions change, and past patterns do not repeat themselves in identical form. We expressly point this out before a strategy is discussed.

Transparency

How AI supports without taking control

STEP 1

Ongoing observation

The system monitors relevant market indicators at short intervals and reports abnormalities as soon as they exceed a defined threshold. This observation does not replace the personal conversation, it provides the basis for it.

STEP 2

Risk management with clear boundaries

Limits are set in advance for each portfolio - such as maximum fluctuation range or minimum proportion of safe asset classes. The model suggests adjustments once these limits are reached; Nothing is changed automatically without approval.

STEP 3

Real-time insight

You can see in a comprehensible overview which factors currently influence the risk assessment. This makes it clear why a recommendation is made at a certain point in time, instead of having to accept it as a “black box” result.

Frequently asked questions

Answers to technical and security-related questions

Does AI replace personal advice?

No. The system provides a data-based assessment of the risk situation. You make the decision about specific steps together with a consultant who will classify the recommendation and adapt it to your personal situation.

How is my data processed and protected?

Only the portfolio and market data necessary for the evaluation are processed for the analysis. Personal data is stored separately from the analysis models and is only used for the agreed consultation.

What happens if there are strong market fluctuations?

The risk management module detects unusual fluctuations at an early stage and reports them to the consulting team. We check together whether the previously set limit values ​​apply or whether an adjustment makes sense.

How independent are the analysis results?

The models are based on historical market data and statistical patterns, not on product recommendations from individual providers. Conflicts of interest due to commissions are openly explained in the consultation.

Do I have to understand the technology myself to use it?

No. The results are explained in understandable language, with brief notes on the technical terms used. Previous technical knowledge is not a prerequisite for a strategy discussion.

Our consulting team will answer any further questions as part of a personal strategy discussion - please use the contact form at the end of this page.

Ready for a data-based assessment of your investment strategy?

In a non-binding strategy discussion, we will show you what the analysis would look like for your specific portfolio, what data will be included and what the limits of the model are.

Request analysis