FIS is pushing to add greater automation for its private-equity business in an effort to streamline workflows.
The regulator already uses machine learning to identify spoofing and layering activities.
BlackRock, MSCI, and La Française are some of the firms looking to replace traditional, linear risk models.
Finance firms and regulators are beginning to assess the ethical implications of artificial intelligence.
The immense growth of online data is driving an increasing number of asset managers to deploy web-scraping tools to find unique investment insights.
Artificially intelligent algorithms are not infallible—as Jo Wright explains, it’s quite the opposite.
Asset managers wanting to thrive in today’s landscape of squeezed margins must learn how to capitalize on innovative AI tech to deliver top-line growth, according to SS&C Technologies.
The call of artificial intelligence and machine learning is alluring. However, Wei-Shen says they can be tough to deal with, especially when shooting at invisible targets.
The Japanese bank has already automated handwritten form processing and is experimenting with AI to make use of its unstructured data.
Despite technological advancements, the onboarding process is still a slog. Banks and vendors are trying to change that.
The quant firm’s Seth Weingram lays out his principles for the effective use of machine learning.
The bank is also looking at using AI for intelligent IOI suggestions based on clients’ trading profiles.
The pace of change—in politics and in fintech—over the past few years has been breathtaking. Jo finds out at NAFIS, however, that some things never change.
Machine learning can tell stories from large datasets to drive alpha, say quants.
The company is leveraging AI to make investment suggestions and dig out sentiment from spoken announcements.
As ESG data becomes more of a commodity, firms are struggling with how best to incorporate carbon data.
The firm is developing machine learning models internally to optimize the reconciliation process and detect price anomalies.
The bank plans to expand a program that uses machine learning to pull out key terms for contracts.
Buy-siders have limited their usage of deep learning techniques due to haziness over their inner workings.
A look at the massive tech projects (and legal battles) underway at the NYSE, which are being led by Stacey Cunningham.
A substantial amount of vendors are making misleading claims about AI capabilities, experts say.
As nations and markets become increasingly interconnected, geopolitical risk has become top of mind for portfolio managers.
Humans, and not robots, will still be required for the foreseeable future, say trading vets.
Assuming that automated artificial intelligence holds the key to unlocking fragmented datasets, the absence of standardized models coupled with regulatory concerns remain barriers to adoption.