Real-World Student Impact

Transforming Financial Learning into Practical Solutions

Our students don't just learn theory—they create solutions that impact real businesses and communities. From algorithmic trading systems that manage actual portfolios to risk assessment tools used by financial institutions, these projects demonstrate the practical power of machine learning in finance.

Portfolio Optimization Algorithm

AI-Driven Investment Strategy

Sarah Chen's machine learning model revolutionized how mid-sized investment firms approach portfolio management. Her algorithm analyzes market sentiment, economic indicators, and historical patterns to optimize asset allocation in real-time. What started as a classroom project now manages over €2.3 million in actual client investments.

The system successfully predicted the 2025 market downturn in February, automatically rebalancing portfolios two weeks before major indices dropped. This proactive adjustment saved client portfolios an average of 12% compared to traditional buy-and-hold strategies during the same period.

€2.3M Assets Under Management

18% Average Annual Return

3 Firms Using System

Living Algorithm

Making real investment decisions for real people

Student Success Stories

Maria Kovács

Credit Risk Analyst

Maria's fraud detection system now processes over 50,000 transactions daily for a major Hungarian bank. Her neural network identifies suspicious patterns with 94% accuracy, preventing an estimated €400,000 in fraudulent transactions monthly. The system she built during her final project has been implemented across three additional financial institutions.

"I never imagined my student project would become something banks actually use," Maria reflects. "Seeing real customers protected by algorithms I wrote—that's incredibly fulfilling."

Fraud Prevention Neural Networks Real-Time Processing

András Tóth

Quantitative Developer

András developed a cryptocurrency trading bot that analyzes social media sentiment alongside technical indicators. His system trades autonomously across five major exchanges, generating consistent returns even during volatile market conditions. The bot's success led to his recruitment by a London-based hedge fund.

His innovation wasn't just technical—András created an ethical framework ensuring the bot never manipulates markets or exploits retail investors. This responsible approach to algorithmic trading has influenced industry best practices.

Sentiment Analysis Automated Trading Ethical AI

Collective Impact Across Industries

Our students' projects have created measurable value across financial markets, from small Hungarian credit unions to international investment firms. These aren't academic exercises—they're practical solutions addressing real financial challenges.

€15M Total Assets Managed

127 Active Projects

23 Partner Institutions

89% Employment Rate