Harnessing the power of data with AI

A variety of financial services companies have started to incorporate artificial intelligence (AI) into their operations-- ranging from quantitative asset managers that use machine learning (ML) models to predict price movements in securities to roboadvisor systems that use AI to help investors decide on their asset allocation. More broadly, companies are increasingly using AI to both analyze structured data, (e.g., asset flows, performance) and extract information from unstructured/alternative data (e.g., images, documents, social media posts) through image recognition and natural language understanding capabilities. The greater volume of data, along with AI and ML tools that can provide automated insights and analytics, offers significant opportunities for asset owners and asset managers to increase operational productivity, improve cybersecurity and manage risk, among other benefits. Currently, more than half of asset managers are in the early stages of AI initiatives, according to a Sapient Global Markets survey.1 And almost one-quarter of asset owners who invest in hedge funds use alternative data and big data analytics/AI to support their investment processes, according to an EY/Greenwich Associates survey.2