Güvenlik önlemleri nasıl işliyor?

Hesap verileri aktarım sırasında şifrelenir ve erişim, yetkilendirilmiş oturumlarla sınırlandırılır. Hassas hesap bilgileri, analiz modelinin çalışması için gereken asgari veri setine indirgenerek işlenir.

Model hangi veri kaynaklarını kullanıyor?

Analizler; halka açık piyasa fiyat verileri, kullanıcının bağladığı hesap hareketleri ve genel makroekonomik göstergeler üzerinden yürütülür. Kullanılan veri setleri, her öneri ekranında kaynak bazında belirtilir.

Ücretlendirme mantığı nedir?

Ücretlendirme, yönetilen portföy hacmine ve aktif olarak kullanılan analiz modülü sayısına göre ölçeklenir. Temel izleme ve öneri modülleri, ek analiz katmanlarından ayrı değerlendirilir; güncel kapsam, hesap paneli üzerinden görüntülenir.

Interface visual showing the portfolio recommendation and risk indicators of the Verimdaş platform

Build Your Portfolio in 60 Seconds, Turn Data into Action

Verimdaş processes market data with Predictive Analytics models and produces portfolio recommendations tailored to your risk profile. Installation is completed in a few steps; No manual analysis or chart comparison required.

Optimize Your Portfolio Check out the Features

The dashboard combines your risk score, recommended asset allocation, and updated recommendations based on recent market movements on a single screen.

From Data to Action

Scattered Data, Delayed Decision

Most investors have access to accurate data but fail to interpret that data in a timely manner. Verimdaş bridges this gap with modelling.

Market data from different sources makes it difficult to create a consistent strategy.
Manual risk assessment reacts slowly to sudden volatility.
Pursuing diversification among dispersed investment instruments takes time.
Emotional decisions can override data-based signals.

Verimdaş processes high volumes of market data through Data Mining techniques; It then transforms that data into meaningful, actionable recommendations. The model evaluates past price movements and current macroeconomic indicators together.

Sample Dashboard Reading

panel; It shows the risk contribution by asset class as a bar chart and the return fluctuation over time as a line chart. Each recommendation is presented with a brief explanation of what data points it is based on.

Basic Abilities

Technical Infrastructure, Comprehensible Result

Three components work together: forecasting, risk control and continuous adaptation.

Predictive Analytics

Evaluating Market Trends in Advance

The model scores possible scenarios by processing past price movements and current indicators together. This allows you to base your decision on an updated probability distribution, not on hindsight data.

Risk Optimization

Risk Optimization Engine

The contribution of each asset in your portfolio to the total risk is calculated separately. The engine flags positions that exceed the risk tolerance you set and offers a rebalancing recommendation.

Real Time

Real-Time Optimization

Recommendations are automatically recalculated when market conditions change. Thus, your portfolio maintains its compliance with current data without requiring daily manual checks.

Process

Three Steps from Installation to Application

On average, it takes less than 60 seconds after registration for a recommendation to arrive on your screen.

Data Entry

Link your existing investment accounts or enter your portfolio information manually. The system validates the inputs and prepares them for analysis.

Artificial Intelligence Model Selection

You choose a model profile based on your risk tolerance: conservative, balanced or growth-oriented. The model adjusts recommendation weights based on this profile.

Application and Monitoring

Recommendations are implemented with your approval; Portfolio performance and risk indicators are constantly monitored on the panel. You'll be notified when changes are needed.

Areas of Use

Corporate Treasury and Individual Savings

Corporate Strategy

Efficient Management of Excess Cash

Companies want to maintain risk limits while distributing short-term cash surplus to different instruments. Verimdaş recommends asset allocation taking into account the identified liquidity need and reports each change with justification.

Individual Investor

Diversification in Additional Income Streams

For individual investors focused on a single asset class, the system analyzes existing savings and comes up with complementary position recommendations at different risk levels. Thus, the diversification decision is based on data, not guesswork.

About us

Where Data Science Meets Financial Decisions

The Verimdaş team was developed by a team of experts from the fields of data engineering and financial risk analysis. The platform is designed to process large data sets and turn them into understandable recommendations.

Our aim is to present the results in a clear and traceable way, without hiding the complex modeling processes from the user. Each recommendation shows what data points and what assumptions it is based on.

Office environment where the Verimdaş team works on data analysis and portfolio modeling

transparency

Frequently Asked Questions

Brief explanations about security, data sources and pricing logic.

How do security measures work?

Account data is encrypted in transit and access is limited to authorized sessions. Sensitive account information is processed by reducing it to the minimum data set required for the analysis model to work.

What data sources does the model use?

Analyzes; It is carried out based on public market price data, user-connected account movements and general macroeconomic indicators. The datasets used are specified on a source-by-source basis in each recommendation screen.

What is the pricing logic?

Pricing scales based on portfolio volume managed and number of analysis modules actively used. Core monitoring and recommendation modules are evaluated separately from additional analysis layers; The current scope is displayed via the account panel.