Publications

We gebruiken het allemaal: artificiële intelligentie, oftewel AI, wordt steeds vaker in het bedrijfsleven ingezet om werkzaamheden te versnellen en te automatiseren. AI wordt gebruikt voor het schrijven van analyses, het genereren van beelden, het opstellen van artikelen en zelfs voor het screenen van sollicitaties. Deze technologie belooft efficiëntie, maar roept ook vragen op over betrouwbaarheid, eerlijkheid en verantwoordelijkheid.

Wat als de technologie die bedoeld is om te helpen, onbedoeld discrimineert? In 2014 ontwikkelde Amazon een geautomatiseerd systeem om sollicitaties te beoordelen. Het doel was om het wervingsproces efficiënter te maken door cv’s automatisch te scoren. Echter, het systeem leerde zichzelf om vrouwelijke kandidaten te benadelen. Dit kwam doordat het algoritme was getraind op historische data, waarin vrouwen ondervertegenwoordigd waren in technische functies. Uiteindelijk werd het in 2018 stopgezet toen bleek dat het systeem niet genderneutraal functioneerde.

The asset manager’s competitive landscape has intensified, and traditional investment factors – such as value, momentum, and quality – are increasingly well-understood, resulting in diminished returns (e.g. McLean & Pontiff, 2015; Calluzzo, Moneta, & Topaloglu S., 2019; Jacobs, Kenneth, & Lee, 2025). One promising yet still underutilized source of alpha lies in textual data (e.g. see review by Sun et al. 2024). While traditional investment strategies rely on structured financial data, a vast amount of valuable and complementary information remains hidden within unstructured textual sources, such as annual reports, patents, earnings calls transcripts, and employee reviews. Until recently, systematically leveraging these textual sources for investment signals remained impractical, due to technological and infrastructural limitations.

“This article is not written by a large language model (LLM) but by a real human.” That one has to put that statement above is an astonishing fact that, even five short years ago, most people would have thought laughable. Of course, technology and its rapid advances and pervasiveness have dramatically impacted every facet of our lives and society. In one way or another, almost all industries and economic activities have been impacted by technology. Finance is no exception. In recent years, a particularly powerful form of technology, namely AI (of which LLM is the latest example), is poised to cause disruptive change on par with, if not more than, the steam engines during the industrial revolution, the computers in the information revolution, and the internet during the communication revolution. 

In this article, we look at how technology has changed the institutional asset management industry in recent years. We look at this from the perspective of both fundamental and quantitative investors, in addition to non-investment functions such as marketing, operations, etc. We also offer a few hypotheses on how technology may further impact institutional investment practices in the near future. First, we briefly discuss three major technological trends driving such secular change.

An interview with APG's Maikel Dullens and Naveep Singh, and DMFCO's Rogier van der Hijden. Recently, APG and DMFCO signed the CFA Institute DEI Code for Europe, joining earlier signatories PGGM and MN. An increasing number of investment managers are recognizing the importance of diversity, equity, and inclusion (DEI) for their organizations. The initiative is now backed in the Netherlands by over €1 trillion in assets under management. The international, voluntary Code offers concrete guidelines to promote DEI within investment organizations and their practices.

De grootschalige afbouw van de rentehedge door pensioenfondsen bij de transitie naar de WTP biedt risico’s én kansen. Hoe handel je integer wanneer belangen botsen, informatie asymmetrisch is en de markt krap?