For years, industry experts have predicted that artificial intelligence (AI) would have a profound impact on the investment industry. Investment managers, on the other hand, have been skeptical of the hype in the absence of substantial use cases. Fast forward a few years and AI has not only arrived but is already having a transformative impact on virtually every facet of investment accounting and middle-office operations.
Today’s investment managers need the agility and scalability to adapt quickly to new regulatory, accounting and reporting requirements, not to mention unforeseen market shocks and accelerated trading volume. Operational costs remain critical as regulations, fee pressures and other risks evolve.
As a result, outsourcing and process automation are more important than ever. Different variants of AI, such as machine learning (ML), are already being implemented to streamline and accelerate typical investment processes, many of which are still highly manual.
Artificial intelligence and machine learning are often used interchangeably which begs the question, do you really know the difference? While closely related, ML is a subset of the broader category of AI and differs in several ways, including scope and applications.
