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Björn Preuss

Teaching Assistant Professor

Subjects
Investment Securities Artificial intelligence Machine learning Data Quantitative methods

Primary research areas

AI Governance and risk management

AI governance and risk management ensure AI is used responsibly, ethically, and safely. As AI advances, it brings risks like bias and misuse. Governance offers oversight, while risk management mitigates harm. Key strategies include transparency, accountability, and regulation. Policies like the EU AI Act aim to guide safe, value-aligned AI use.

Finance and Investments

Recent investment research explores how AI enhances strategies, market analysis, and decision-making. Tools like machine learning and big data are reshaping portfolio management and trading. Traditional areas—like asset allocation and pricing—remain vital, as researchers study how classic models adapt to AI-driven, data-rich financial markets.

Quantitative risk management

Quantitative Risk Management uses math, stats, and computing to assess and mitigate financial risks. This research focuses on models for market, credit, operational, and liquidity risks, using tools like VaR, CVaR, and stress testing. It aims to improve accuracy, address model risk, and support stronger, more transparent risk practices.

How to govern AI in an efficient way

My work in AI governance develops frameworks for accountability, transparency, and ethical oversight in AI systems, aiming to reduce bias, enhance fairness, and ensure AI serves the public good. It supports trust by aligning technological progress with democratic principles. 

In quantitative risk management, I create advanced models to measure and mitigate systemic financial risks, improving the resilience of financial institutions and markets. This helps prevent crises, protects investors, and contributes to global economic stability. 

For algorithmic investments in equities, my research designs responsible, data-driven trading strategies. It also addresses environmental impact by optimizing trading algorithms to reduce energy consumption and computational waste, promoting sustainable financial technologies. 

Politically, my work informs regulations by providing evidence-based tools to guide policymaking, ensuring AI and financial markets are effectively regulated, with standards for risk management and ethical AI use, and innovation is balanced with public accountability. 

Recent research projects

ETAPAS project

This project explores the ethical, social, and legal implications of AI, robotics, and big data in the public sector, aiming to develop frameworks for responsible, transparent, and accountable implementation.
ETAPAS project

Nordic Finance and the Good Society

The project aims to lead the frontier of research on financial institutions, markets and sustainability in the Nordic region. With 6 research streams we aim to tackle current challenges of the financial sector’s future.
NFaGS

Applied Ethical AI on Nordic Patient Records

The goal of the project is to develop an ethical algorithm capable of reading both digital and analogue patient journals, across medical health record systems and across Nordic borders and Nordic languages.
Nordic Innovation

Outside activities

VP of Product and Advisory, 2017–present

Leading product management and advisory function in 2021.AI related to AI governance. 2021.AI is a Danish AI software vendor with a specific focus on Governance and risk management of AI.
2021.AI Homepage