Cross-Asset Thematic Strategy, Edelscourt

Albert Maass

Albert brings over three decades of experience from the financial industry, having worked with top institutions across the UK, Americas, and Asia. His broad expertise spans investments in multiple asset classes and extends to risk management.

In a previous role, Albert served as the Head of Alternative Investments at Shinsei Bank in Japan, where he oversaw a varied portfolio comprising private equity, hedge funds, reinsurance, credit, and other assets. His distinguished career has seen partnerships with prestigious institutions such as HVB, the European Bank for Reconstruction and Development, Nomura International, Mariner Investment Group, Allied Capital Asset Management, and the Central Bank of Chile.

Albert is a certified Financial Risk Manager (FRM) and is an alumnus of the Universidad Católica de Chile, with a degree in Business and Economics

Cross-Asset Thematic Strategy

Edelscourt

Established in 2014, Edelscourt combines cutting-edge technology with deep industry knowledge. We specialise in risk management solutions for a diverse range of clients, from financial institutions to family offices.

Cross Asset Strategy

Multiple Countries / Cross Asset Strategy

<ul>
<li>Artificial Intelligence (AI) has made incredible progress in various industries, providing opportunities for business growth and innovation while introducing new risks.</li>
<li>AI risk encompasses categories such as cyber risk and operational risk, along with unique dimensions like ethical risk, bias risk, transparency risk, autonomy risk, and long-term existential risk.</li>
<li>While new AI regulations are still being discussed, managing AI risk requires a comprehensive approach, including defining risk, establishing tolerance, conducting assessments, implementing mitigation strategies, establishing governance, and monitoring processes.</li>
</ul>


Artificial Intelligence (AI) has made incredible progress in various industries, providing opportunities for business growth and innovation while introducing new risks.
AI risk encompasses categories such as cyber risk and operational risk, along with unique dimensions like ethical risk, bias risk, transparency risk, autonomy risk, and long-term existential risk.
While new AI regulations are still being discussed, managing AI risk requires a comprehensive approach, including defining risk, establishing tolerance, conducting assessments, implementing mitigation strategies, establishing governance, and monitoring processes.


Securing the Future: Managing and Regulating AI Risk