Pääsevätkö Tilinsto tai kolmas osapuoli käsiksi varoihini?

Yhteys pörssitiliin tehdään API-avaimella, jolle annetaan ainoastaan kaupankäynti- ja lukuoikeudet. Nosto-oikeutta ei myönnetä, eikä Tilinsto säilytä varoja omalla tilillään.

Mitä tapahtuu, jos pörssiyhteys katkeaa?

Automaatio pysähtyy ja odottaa yhteyden palautumista. Suunniteltua ostoa ei suoriteta osittain tai arvioiden varassa — järjestelmä odottaa vahvistettua dataa.

Voinko keskeyttää automaation milloin tahansa?

Kyllä. Automaation voi pysäyttää tai muuttaa asetuksia hetkenä minä hyvänsä. Keskeytys ei vaikuta aiemmin tehtyihin ostoihin.

Mitä palvelu maksaa?

Hinnoittelu ja mahdollinen palvelumaksu näytetään aina ennen automaation käynnistämistä. Käyttäjä hyväksyy kulut erikseen — ei piilokuluja tilausaikana.

Sopiiko palvelu ensikertalaiselle?

Kyllä. Käyttöönotto ei vaadi aiempaa sijoituskokemusta. Käyttäjä määrittää budjetin ja riskitason; malli vastaa ajoituksesta sovitun kehyksen sisällä.

Tilinsto — AI-assisted market data analysis for crypto investing

Smart DCA automation

Artificial intelligence schedules purchases. You build a portfolio systematically.

Tilinsto analyzes market data in real time and calculates timed buy moments for an automatic DCA strategy. No daily monitoring, no emotional decisions.

Start the analysis

24/7 Continuous data processing

Automatic Purchases are scheduled according to the model

Open Logic visible to the user

Starting point

Manual scheduling leads to inconsistent purchases.

The student budget is limited, and the time to follow course curves is even more limited. Many buy crypto randomly — sometimes at the peak of the price, sometimes in panic. Decisions are born from feeling, not from data.

The solution

Tilinsto transfers the timing to the template.

The service collects market data, calculates likely favorable purchase moments and completes purchases according to the agreed schedule. You define the budget and frequency — the model takes care of the timing.

The result: fewer decisions, more consistency.

Method

Four steps behind every purchase

Every purchase is based on the same repeatable process — no guesswork.

Data collection

Price, volume and volatility data are collected from multiple sources on an ongoing basis.

Model analysis

The forecast model evaluates the market situation and calculates the probability of a favorable purchase moment.

Timing decision

The time of purchase is adjusted to the agreed DCA schedule and the user's risk settings.

Automatic execution

The purchase is made within the agreed limit. The event is logged in the user's view.

Logic does not seek a perfect base. It reduces the average purchase price by spreading the purchases over a longer period of time and emphasizing them at times when the model estimates the risk to be lower than average.

The strategy is designed for low-risk, long-term growth — not short-term trading.

Minimizing risk in practice

One-time investmentHigh timing risk

Manual DCAAverage risk

Tilinsto Smart DCAReduced timing risk

Data and transparency

The analysis is based on a continuous flow of data

Tilinsto does not promise returns. It shows how decisions are made.

Continuous Market data is processed around the clock, not just during trading hours.

Multiple sources Price, volume and volatility signals are combined into one model.

In minutes The analysis is updated and the next buying window is recalculated.

The model makes probability estimates based on historical and real-time data. It does not predict the future price with certainty, and past performance does not guarantee the future. The user can always see on what basis the purchase was made.

In practice

Two typical situations

The examples describe how automation works in different market situations.

Tilinsto — long-term savings plan for students

Scenario 1 — Long-term breeding

Fixed monthly amount, distributed timing

The student allocates part of the monthly budget to crypto and sets Tilinsto to make the purchases every month. The model divides the amount into several smaller purchases and emphasizes them at times when the short-term risk is estimated to be lower.

The goal is not to time the market perfectly, but to reduce the impact of a single bad buying moment.

Scenario 2 — Market volatility increases

The automation reacts, the user is not stressed

When volatility rises rapidly, the model recognizes the changed risk level and can move or reduce individual purchases within the agreed schedule. The user does not make reactive decisions in the middle of the day.

All changes are shown in the user's log with reasons.

Technical implementation

Performance frequencyUser Defined

Risk limitAdjustable from the settings

LoggingEvery purchase with reasons

Account linking

Connects to a supported exchange account with an API key that does not have withdrawal rights.

Automation control

The user sets the budget, frequency and risk limit. Automation can be stopped at any time.

Reporting

All completed and skipped purchases are shown on the timeline with reasons.

Frequently asked questions

Safety, technology and costs

Can Tilinsto or a third party access my funds?

The connection to the stock exchange account is made with an API key, which is given only trading and reading rights. Withdrawal rights are not granted, and Tilinsto does not keep funds in its own account.

What happens if the exchange connection is lost?

The automation stops and waits for the connection to be restored. The planned purchase is not carried out partially or based on estimates — the system is waiting for confirmed data.

Can I stop automation at any time?

Yes. You can stop the automation or change the settings at any moment. Suspension does not affect previously made purchases.

What does the service cost?

Pricing and a possible service fee are always displayed before starting the automation. The user accepts the costs separately — no hidden costs during the order period.

Is the service suitable for a first-timer?

Yes. Implementation does not require previous investment experience. The user defines the budget and risk level; the model is responsible for the timing within the agreed frame.