Asset and wealth management firms have conventionally not been at the forefront of technological innovation. This probably reflects the conservatism of the sector. Some would also say that innovation is, perhaps, at odds with the cautious and reliable image that an asset manager wants to portray to customers.
But this situation is not tenable. It is well documented that active asset managers are finding it more and more difficult to attract funds. The movement of money to passive funds and the squeezing of margins is predicted to continue.
Morgan Stanley recently estimated that there would be a further 36% drop in revenue from active asset management by 2023.
To create new, more personalized products to go after broader segments of the market, to more intelligently manage real estate, to offer a more digital experience and, ultimately, to generate more alpha, firms must get smarter about their use of technology and, in particular, data.
Fortunately, this challenge is recognized within the industry. I was recently at the 2019 InvestOps investment management technology conference in Tampa, Fla. Time and time again, data was cited as providing the foundation for making existing operational processes more efficient, for creating new types of products and distribution channels and providing the underpinning use of technologies such as robotic process automation and artificial intelligence.
All financial services firms, including those in institutional asset management, are increasingly using data, next-generation database technologies, machine learning and artificial intelligence to better manage risk, spot opportunities and deliver more personalized products to customers, whether that's a high-net-worth individual or a pension fund manager.
Here are three core requirements necessary within any data infrastructure in order to deliver what institutional asset managers need: