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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 -

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